RandomForest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import modules\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pyspark.sql import SparkSession\n",
    "\n",
    "# build spark session and spark context\n",
    "spark = SparkSession.builder \\\n",
    "        .master(\"local[4]\") \\\n",
    "        .appName(\"hotel\") \\\n",
    "        .getOrCreate()\n",
    "sc = spark.sparkContext\n",
    "\n",
    "df = spark.read.csv('hotel_bookings.csv',  inferSchema=True, header = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Parameters for defining code below\n",
    "target = 'is_canceled'\n",
    "cancel_label = 1\n",
    "noncancel_label = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Balancing a DataFrame with Downsampling\n",
    "\n",
    "def downsample(df, target, cancel_label, noncancel_label):\n",
    "    \"\"\"\n",
    "    df               spark dataframe\n",
    "    target           str, target variable\n",
    "    cancel_label     int, value of canceled booking\n",
    "    noncancel_label  int, value of non-canceled booking\n",
    "    \n",
    "    \"\"\"\n",
    "\n",
    "    ### ENTER CODE HERE\n",
    "    \n",
    "    from pyspark.sql.functions import col\n",
    "    \n",
    "    #count of canceled and non-canceled labels\n",
    "    cancel_n = df.filter(col(target) == cancel_label).count()\n",
    "    noncancel_n = df.filter(col(target) == noncancel_label).count()\n",
    "    \n",
    "    #df split by having either the poitive or negative labels\n",
    "    df_cancel = df.filter(col(target) == cancel_label)\n",
    "    df_noncancel = df.filter(col(target) == noncancel_label)\n",
    "    \n",
    "    \n",
    "    if cancel_n > noncancel_n:\n",
    "        #amount to sample from is fraction of low noncancel/full cancel\n",
    "        df_a = df_cancel.sample(fraction = (noncancel_n/cancel_n))\n",
    "        #combine df_cancel sample with full df_noncancel\n",
    "        df_b = df_noncancel.union(df_a)\n",
    "    elif noncancel_n > cancel_n:\n",
    "        #amount to sample from is fraction of low cancel/full non-cancel\n",
    "        df_a = df_noncancel.sample(fraction = (cancel_n/noncancel_n))\n",
    "        #combine df_noncancel sample with full df_cancel\n",
    "        df_b = df_cancel.union(df_a)\n",
    "    else:\n",
    "        #if count of df_cancel = df_noncancel, then just use original df\n",
    "        df_b = df\n",
    "\n",
    "    return df_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-----------+-----+\n",
      "|is_canceled|count|\n",
      "+-----------+-----+\n",
      "|          1|44224|\n",
      "|          0|44185|\n",
      "+-----------+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Call your downsample function here, and show the count by label\n",
    "df_downsample = downsample(df, target, cancel_label, noncancel_label)\n",
    "df_downsample.groupBy(target).count().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.functions import col\n",
    "\n",
    "# replace the strings \"NULL\" and \"NA\" with null value\n",
    "df_withNull = df_downsample.replace('NULL', None).replace('NA', None)\n",
    "\n",
    "# replace null values in 'children' to 0 since there are only 4\n",
    "df2 = df_withNull.fillna({'children':0})\n",
    "\n",
    "# replace 'children' datatype to int\n",
    "df2 = df2.withColumn('children', col('children').cast(\"Int\"))\n",
    "\n",
    "# drop 'company' and 'agent' due to high null count\n",
    "df2 = df2.drop('agent', 'company','country', 'arrival_date_week_number', 'reservation_status')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# addressing reservation_status_date, which gives the date at which the last \n",
    "# reservation status was set. I'm transforming it into number of days since reservation\n",
    "# status was set, so day of arrival - reservation_status_date\n",
    "# from pyspark.sql.types import DateType\n",
    "\n",
    "# convert reservation_status_date into datetype dtype\n",
    "# temp = df2.withColumn(\"reservation_status_date\", df2[\"reservation_status_date\"].cast(DateType()))\n",
    "\n",
    "# need to combine arrival_date_year, arrival_date_month, and arrival_date_day_of_month\n",
    "# into one column and cast it to DateType, then replacing reservation_status_date column\n",
    "# with number of days since reservation.\n",
    "# until then, dropping reservation_status_date\n",
    "df2 = df2 .drop('reservation_status_date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#numerically encode all columns of type string\n",
    "from pyspark.ml import Pipeline\n",
    "from pyspark.ml.feature import OneHotEncoder, OneHotEncoderModel, StringIndexer\n",
    "\n",
    "# list of columns to numerically encode\n",
    "col_string=['hotel', 'meal','market_segment',\n",
    "            'distribution_channel','reserved_room_type','assigned_room_type',\n",
    "            'deposit_type','customer_type']\n",
    "col_stringwmonth = col_string+['arrival_date_month']\n",
    "\n",
    "\n",
    "# col_num = list of new column names being changed into numeric\n",
    "col_num=[x+\"_NUMERIC\" for x in col_string]\n",
    "# don't need to change dates into numeric col_num=col_num+['arrival_date_year','arrival_date_day_of_month']\n",
    "\n",
    "# col_oh = list of columns being one-hot encoded\n",
    "col_oh=[x+\"_oh\" for x in col_string]\n",
    "# dont need to ohencode dates col_oh=col_oh+['arrival_date_year_oh','arrival_date_day_of_month_oh']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "indexers = [StringIndexer(inputCol=column, outputCol=column+\"_NUMERIC\").fit(df2) for column in col_stringwmonth]\n",
    "pipeline = Pipeline(stages=indexers)\n",
    "df_indexed = pipeline.fit(df2).transform(df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#one-hot encode all columns in col_num\n",
    "ohe = OneHotEncoder(dropLast=False)\n",
    "ohe.setInputCols(col_num)\n",
    "ohe.setOutputCols(col_oh)\n",
    "model = ohe.fit(df_indexed)\n",
    "\n",
    "df_casted=model.transform(df_indexed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop the original, non-ohencoded variables\n",
    "df_encoded=df_casted.drop(*col_stringwmonth)\n",
    "df_encoded=df_encoded.drop(*col_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalized using L^1 norm\n"
     ]
    }
   ],
   "source": [
    "#removed normalization step for now\n",
    "from pyspark.ml.feature import VectorAssembler\n",
    "from pyspark.mllib.linalg import Vectors\n",
    "from pyspark.ml.feature import Normalizer\n",
    "\n",
    "norm_to_columns = ['lead_time', 'stays_in_weekend_nights', 'stays_in_week_nights', 'adults', 'children', 'babies', \n",
    "                'previous_cancellations', 'previous_bookings_not_canceled', 'booking_changes', 'adr', \n",
    "                'required_car_parking_spaces', 'total_of_special_requests']\n",
    "\n",
    "# combine all to-norm columns into one vector named \"norm_features\"\n",
    "assembler = VectorAssembler(inputCols=norm_to_columns, outputCol=\"norm_features\")\n",
    "transformed = assembler.transform(df_encoded) \n",
    "transformed = transformed.drop(*norm_to_columns)\n",
    "\n",
    "# in the end, new column named normFeatures combined all features that are normalized\n",
    "normalizer = Normalizer(inputCol=\"norm_features\", outputCol=\"normFeatures\", p=1.0)\n",
    "l1NormData = normalizer.transform(transformed)\n",
    "l1NormData = l1NormData.drop(*norm_to_columns + ['norm_features'])\n",
    "print(\"Normalized using L^1 norm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# combine all feature columns (non-label columns) into one vector named \"feature\"\n",
    "assembler = VectorAssembler(inputCols=df_encoded.columns[1:], outputCol=\"features\")\n",
    "all_transformed = assembler.transform(df_encoded)\n",
    "\n",
    "# convert to rdd with 2 columns, label and features, where features is a DenseVector combination of all other features\n",
    "dataRdd = all_transformed.select(col(\"is_canceled\").alias(\"label\"), col(\"features\")).rdd.map(tuple)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[LabeledPoint(1.0, [85.0,2015.0,1.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,82.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0])]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyspark.mllib.regression import LabeledPoint\n",
    "\n",
    "# map features as floats, then input all into a DenseVector, as well as mapping labels as floats\n",
    "# then map into LabeledPoint object\n",
    "lp = dataRdd.map(lambda row: (float(row[0]), Vectors.dense([float(c) for c in row[1]])))\\\n",
    "            .map(lambda row: LabeledPoint(row[0], row[1]))\n",
    "lp.take(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#type(lp.take(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 70/30 test train split\n",
    "seed = 314\n",
    "train, test = lp.randomSplit([0.7, 0.3], seed=seed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use these variables in place of test/train.count() bc those methods take a long time, instead just call once\n",
    "test_count = test.count()\n",
    "train_count = train.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#from pyspark.mllib.tree import RandomForest\n",
    "#from pyspark.mllib.util import MLUtils\n",
    "\n",
    "#data = MLUtils.loadLibSVMFile(sc, 'hotel_bookings.csv')\n",
    "#data.take(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.mllib.tree import RandomForest\n",
    "from pyspark.mllib.util import MLUtils\n",
    "\n",
    "# Train a RandomForest model.\n",
    "#  Empty categoricalFeaturesInfo indicates all features are continuous.\n",
    "#  Setting featureSubsetStrategy=\"auto\" lets the algorithm choose.\n",
    "model = RandomForest.trainClassifier(train, numClasses=2, categoricalFeaturesInfo={},\n",
    "                                     numTrees=100, featureSubsetStrategy=\"auto\",\n",
    "                                     impurity='gini', maxDepth=5, maxBins=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "ename": "Py4JJavaError",
     "evalue": "An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.\n: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 82.0 failed 1 times, most recent failure: Lost task 2.0 in stage 82.0 (TID 588, jupyter-kliu01, executor driver): org.apache.spark.SparkException: Failed to execute user defined function(StringIndexerModel$$Lambda$3244/1026762699: (string) => double)\n\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)\n\tat org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\n\tat org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)\n\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:156)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:148)\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:148)\n\tat org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:295)\n\tat org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:607)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.$anonfun$run$1(PythonRunner.scala:383)\n\tat org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1932)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:218)\nCaused by: org.apache.spark.SparkException: Unseen label: Gr. To handle unseen labels, set Param handleInvalid to keep.\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1(StringIndexer.scala:405)\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1$adapted(StringIndexer.scala:390)\n\t... 14 more\n\nDriver stacktrace:\n\tat org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2023)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1972)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1971)\n\tat scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)\n\tat scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1971)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:950)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:950)\n\tat scala.Option.foreach(Option.scala:407)\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:950)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2203)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2152)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2141)\n\tat org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)\n\tat org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:752)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2093)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2114)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2133)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)\n\tat org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)\n\tat org.apache.spark.rdd.RDD.withScope(RDD.scala:388)\n\tat org.apache.spark.rdd.RDD.collect(RDD.scala:1003)\n\tat org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:168)\n\tat org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\n\tat java.lang.reflect.Method.invoke(Method.java:498)\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\n\tat py4j.Gateway.invoke(Gateway.java:282)\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\n\tat java.lang.Thread.run(Thread.java:748)\nCaused by: org.apache.spark.SparkException: Failed to execute user defined function(StringIndexerModel$$Lambda$3244/1026762699: (string) => double)\n\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)\n\tat org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\n\tat org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)\n\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:156)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:148)\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:148)\n\tat org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:295)\n\tat org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:607)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.$anonfun$run$1(PythonRunner.scala:383)\n\tat org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1932)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:218)\nCaused by: org.apache.spark.SparkException: Unseen label: Gr. To handle unseen labels, set Param handleInvalid to keep.\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1(StringIndexer.scala:405)\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1$adapted(StringIndexer.scala:390)\n\t... 14 more\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mPy4JJavaError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-52-84984e663a56>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mpredictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mlabelsAndPredictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mlp\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mlp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredictions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mtestErr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabelsAndPredictions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_count\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Test Error = '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtestErr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mcount\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1139\u001b[0m         \u001b[0;36m3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1140\u001b[0m         \"\"\"\n\u001b[0;32m-> 1141\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0m_\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1142\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1143\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36msum\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1130\u001b[0m         \u001b[0;36m6.0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1131\u001b[0m         \"\"\"\n\u001b[0;32m-> 1132\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moperator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1134\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mfold\u001b[0;34m(self, zeroValue, op)\u001b[0m\n\u001b[1;32m   1001\u001b[0m         \u001b[0;31m# zeroValue provided to each partition is unique from the one provided\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1002\u001b[0m         \u001b[0;31m# to the final reduce call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1003\u001b[0;31m         \u001b[0mvals\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcollect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1004\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvals\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mzeroValue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1005\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mcollect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    887\u001b[0m         \"\"\"\n\u001b[1;32m    888\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mSCCallSiteSync\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontext\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mcss\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 889\u001b[0;31m             \u001b[0msock_info\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mctx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPythonRDD\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcollectAndServe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jrdd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrdd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    890\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_load_from_socket\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msock_info\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jrdd_deserializer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    891\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/py4j/java_gateway.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m   1303\u001b[0m         \u001b[0manswer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgateway_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_command\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1304\u001b[0m         return_value = get_return_value(\n\u001b[0;32m-> 1305\u001b[0;31m             answer, self.gateway_client, self.target_id, self.name)\n\u001b[0m\u001b[1;32m   1306\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1307\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mtemp_arg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtemp_args\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/sql/utils.py\u001b[0m in \u001b[0;36mdeco\u001b[0;34m(*a, **kw)\u001b[0m\n\u001b[1;32m    129\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdeco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    130\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 131\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    132\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mpy4j\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPy4JJavaError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    133\u001b[0m             \u001b[0mconverted\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconvert_exception\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjava_exception\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/py4j/protocol.py\u001b[0m in \u001b[0;36mget_return_value\u001b[0;34m(answer, gateway_client, target_id, name)\u001b[0m\n\u001b[1;32m    326\u001b[0m                 raise Py4JJavaError(\n\u001b[1;32m    327\u001b[0m                     \u001b[0;34m\"An error occurred while calling {0}{1}{2}.\\n\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 328\u001b[0;31m                     format(target_id, \".\", name), value)\n\u001b[0m\u001b[1;32m    329\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    330\u001b[0m                 raise Py4JError(\n",
      "\u001b[0;31mPy4JJavaError\u001b[0m: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.\n: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 82.0 failed 1 times, most recent failure: Lost task 2.0 in stage 82.0 (TID 588, jupyter-kliu01, executor driver): org.apache.spark.SparkException: Failed to execute user defined function(StringIndexerModel$$Lambda$3244/1026762699: (string) => double)\n\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)\n\tat org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\n\tat org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)\n\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:156)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:148)\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:148)\n\tat org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:295)\n\tat org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:607)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.$anonfun$run$1(PythonRunner.scala:383)\n\tat org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1932)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:218)\nCaused by: org.apache.spark.SparkException: Unseen label: Gr. To handle unseen labels, set Param handleInvalid to keep.\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1(StringIndexer.scala:405)\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1$adapted(StringIndexer.scala:390)\n\t... 14 more\n\nDriver stacktrace:\n\tat org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2023)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1972)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1971)\n\tat scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)\n\tat scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1971)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:950)\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:950)\n\tat scala.Option.foreach(Option.scala:407)\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:950)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2203)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2152)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2141)\n\tat org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)\n\tat org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:752)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2093)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2114)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2133)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)\n\tat org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)\n\tat org.apache.spark.rdd.RDD.withScope(RDD.scala:388)\n\tat org.apache.spark.rdd.RDD.collect(RDD.scala:1003)\n\tat org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:168)\n\tat org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\n\tat java.lang.reflect.Method.invoke(Method.java:498)\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\n\tat py4j.Gateway.invoke(Gateway.java:282)\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\n\tat java.lang.Thread.run(Thread.java:748)\nCaused by: org.apache.spark.SparkException: Failed to execute user defined function(StringIndexerModel$$Lambda$3244/1026762699: (string) => double)\n\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)\n\tat org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\n\tat org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)\n\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:156)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.next(SerDeUtil.scala:148)\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\n\tat org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:148)\n\tat org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:295)\n\tat org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:607)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.$anonfun$run$1(PythonRunner.scala:383)\n\tat org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1932)\n\tat org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:218)\nCaused by: org.apache.spark.SparkException: Unseen label: Gr. To handle unseen labels, set Param handleInvalid to keep.\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1(StringIndexer.scala:405)\n\tat org.apache.spark.ml.feature.StringIndexerModel.$anonfun$getIndexer$1$adapted(StringIndexer.scala:390)\n\t... 14 more\n"
     ]
    }
   ],
   "source": [
    "# Evaluate model on test instances and compute test error\n",
    "predictions = model.predict(test.map(lambda x: x.features))\n",
    "labelsAndPredictions = test.map(lambda lp: lp.label).zip(predictions)\n",
    "testErr = labelsAndPredictions.filter(lambda p: p[0] != p[1]).count() / float(test_count)\n",
    "print('Test Error = ' + str(testErr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pyspark.rdd.RDD"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(labelsAndPredictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.0]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions.take(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/serializers.py\", line 468, in dumps\n",
      "    return cloudpickle.dumps(obj, pickle_protocol)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 1097, in dumps\n",
      "    cp.dump(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 357, in dump\n",
      "    return Pickler.dump(self, obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 437, in dump\n",
      "    self.save(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 786, in save_tuple\n",
      "    save(element)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 840, in _batch_appends\n",
      "    save(x)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 840, in _batch_appends\n",
      "    save(x)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 840, in _batch_appends\n",
      "    save(x)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 840, in _batch_appends\n",
      "    save(x)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 840, in _batch_appends\n",
      "    save(x)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 843, in _batch_appends\n",
      "    save(tmp[0])\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 496, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 887, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 549, in save\n",
      "    self.save_reduce(obj=obj, *rv)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 662, in save_reduce\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 524, in save\n",
      "    rv = reduce(self.proto)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/context.py\", line 343, in __getnewargs__\n",
      "    \"It appears that you are attempting to reference SparkContext from a broadcast \"\n",
      "Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.\n"
     ]
    },
    {
     "ename": "PicklingError",
     "evalue": "Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/serializers.py\u001b[0m in \u001b[0;36mdumps\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    467\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 468\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mcloudpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpickle_protocol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    469\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPickleError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36mdumps\u001b[0;34m(obj, protocol)\u001b[0m\n\u001b[1;32m   1096\u001b[0m         \u001b[0mcp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCloudPickler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprotocol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1097\u001b[0;31m         \u001b[0mcp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1098\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36mdump\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    356\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 357\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    358\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mRuntimeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36mdump\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    436\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mframer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_framing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 437\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    438\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSTOP\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_tuple\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    785\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0melement\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 786\u001b[0;31m             \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0melement\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    787\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    839\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    841\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    839\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    841\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    839\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    841\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    839\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    841\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    839\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    841\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    842\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 843\u001b[0;31m                 \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtmp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    844\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPEND\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    495\u001b[0m                 or themodule is None):\n\u001b[0;32m--> 496\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    497\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    886\u001b[0m                 \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 887\u001b[0;31m                 \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    888\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEM\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    548\u001b[0m         \u001b[0;31m# Save the reduce() output and finally memoize the object\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 549\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_reduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mrv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    550\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_reduce\u001b[0;34m(self, func, args, state, listitems, dictitems, obj)\u001b[0m\n\u001b[1;32m    661\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mstate\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 662\u001b[0;31m             \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    663\u001b[0m             \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBUILD\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    523\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mreduce\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 524\u001b[0;31m                 \u001b[0mrv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mproto\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    525\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/context.py\u001b[0m in \u001b[0;36m__getnewargs__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    342\u001b[0m         raise Exception(\n\u001b[0;32m--> 343\u001b[0;31m             \u001b[0;34m\"It appears that you are attempting to reference SparkContext from a broadcast \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    344\u001b[0m             \u001b[0;34m\"variable, action, or transformation. SparkContext can only be used on the driver, \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mException\u001b[0m: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mPicklingError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-44-865da273dae3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Evaluating the model on test data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mlabelsAndPreds_te\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0maccuracy_te\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1.0\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mlabelsAndPreds_te\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mtest_count\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;31m#print('model accuracy (test): {}'.format(accuracy_te))\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mcount\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1139\u001b[0m         \u001b[0;36m3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1140\u001b[0m         \"\"\"\n\u001b[0;32m-> 1141\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0m_\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1142\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1143\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36msum\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1130\u001b[0m         \u001b[0;36m6.0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1131\u001b[0m         \"\"\"\n\u001b[0;32m-> 1132\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moperator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1134\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mfold\u001b[0;34m(self, zeroValue, op)\u001b[0m\n\u001b[1;32m   1001\u001b[0m         \u001b[0;31m# zeroValue provided to each partition is unique from the one provided\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1002\u001b[0m         \u001b[0;31m# to the final reduce call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1003\u001b[0;31m         \u001b[0mvals\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcollect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1004\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvals\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mzeroValue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1005\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mcollect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    887\u001b[0m         \"\"\"\n\u001b[1;32m    888\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mSCCallSiteSync\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontext\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mcss\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 889\u001b[0;31m             \u001b[0msock_info\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mctx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPythonRDD\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcollectAndServe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jrdd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrdd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    890\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_load_from_socket\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msock_info\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jrdd_deserializer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    891\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36m_jrdd\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   2627\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2628\u001b[0m         wrapped_func = _wrap_function(self.ctx, self.func, self._prev_jrdd_deserializer,\n\u001b[0;32m-> 2629\u001b[0;31m                                       self._jrdd_deserializer, profiler)\n\u001b[0m\u001b[1;32m   2630\u001b[0m         python_rdd = self.ctx._jvm.PythonRDD(self._prev_jrdd.rdd(), wrapped_func,\n\u001b[1;32m   2631\u001b[0m                                              self.preservesPartitioning, self.is_barrier)\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36m_wrap_function\u001b[0;34m(sc, func, deserializer, serializer, profiler)\u001b[0m\n\u001b[1;32m   2515\u001b[0m     \u001b[0;32massert\u001b[0m \u001b[0mserializer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"serializer should not be empty\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2516\u001b[0m     \u001b[0mcommand\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprofiler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdeserializer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mserializer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2517\u001b[0;31m     \u001b[0mpickled_command\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbroadcast_vars\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mincludes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_prepare_for_python_RDD\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcommand\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2518\u001b[0m     return sc._jvm.PythonFunction(bytearray(pickled_command), env, includes, sc.pythonExec,\n\u001b[1;32m   2519\u001b[0m                                   sc.pythonVer, broadcast_vars, sc._javaAccumulator)\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36m_prepare_for_python_RDD\u001b[0;34m(sc, command)\u001b[0m\n\u001b[1;32m   2501\u001b[0m     \u001b[0;31m# the serialized command will be compressed by broadcast\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2502\u001b[0m     \u001b[0mser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCloudPickleSerializer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2503\u001b[0;31m     \u001b[0mpickled_command\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2504\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickled_command\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0msc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPythonUtils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetBroadcastThreshold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jsc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m# Default 1M\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2505\u001b[0m         \u001b[0;31m# The broadcast will have same life cycle as created PythonRDD\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/serializers.py\u001b[0m in \u001b[0;36mdumps\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    476\u001b[0m                 \u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"Could not serialize object: %s: %s\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0memsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    477\u001b[0m             \u001b[0mprint_exec\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstderr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 478\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPicklingError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    480\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mPicklingError\u001b[0m: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063."
     ]
    }
   ],
   "source": [
    "# Evaluating the model on test data\n",
    "labelsAndPreds_te = test.map(lambda p: (p.label, float(model.predict(p.features))))\n",
    "accuracy_te = 1.0 * labelsAndPreds_te.filter(lambda p: p[0] == p[1]).count() / test_count\n",
    "print('model accuracy (test): {}'.format(accuracy_te))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/serializers.py\", line 468, in dumps\n",
      "    return cloudpickle.dumps(obj, pickle_protocol)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 1097, in dumps\n",
      "    cp.dump(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 357, in dump\n",
      "    return Pickler.dump(self, obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 437, in dump\n",
      "    self.save(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 786, in save_tuple\n",
      "    save(element)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 840, in _batch_appends\n",
      "    save(x)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 840, in _batch_appends\n",
      "    save(x)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 501, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 816, in save_list\n",
      "    self._batch_appends(obj)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 843, in _batch_appends\n",
      "    save(tmp[0])\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 496, in save_function\n",
      "    self.save_function_tuple(obj)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\", line 730, in save_function_tuple\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 887, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 549, in save\n",
      "    self.save_reduce(obj=obj, *rv)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 662, in save_reduce\n",
      "    save(state)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 504, in save\n",
      "    f(self, obj) # Call unbound method with explicit self\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 856, in save_dict\n",
      "    self._batch_setitems(obj.items())\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 882, in _batch_setitems\n",
      "    save(v)\n",
      "  File \"/opt/conda/lib/python3.7/pickle.py\", line 524, in save\n",
      "    rv = reduce(self.proto)\n",
      "  File \"/opt/conda/lib/python3.7/site-packages/pyspark/context.py\", line 343, in __getnewargs__\n",
      "    \"It appears that you are attempting to reference SparkContext from a broadcast \"\n",
      "Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.\n"
     ]
    },
    {
     "ename": "PicklingError",
     "evalue": "Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/serializers.py\u001b[0m in \u001b[0;36mdumps\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    467\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 468\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mcloudpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpickle_protocol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    469\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPickleError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36mdumps\u001b[0;34m(obj, protocol)\u001b[0m\n\u001b[1;32m   1096\u001b[0m         \u001b[0mcp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCloudPickler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprotocol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1097\u001b[0;31m         \u001b[0mcp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1098\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36mdump\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    356\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 357\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    358\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mRuntimeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36mdump\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    436\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mframer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_framing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 437\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    438\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSTOP\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_tuple\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    785\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0melement\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 786\u001b[0;31m             \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0melement\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    787\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    839\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    841\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    839\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    841\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    500\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlookedup_by_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    502\u001b[0m                 \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    815\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    842\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 843\u001b[0;31m                 \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtmp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    844\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPEND\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function\u001b[0;34m(self, obj, name)\u001b[0m\n\u001b[1;32m    495\u001b[0m                 or themodule is None):\n\u001b[0;32m--> 496\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_function_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    497\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/cloudpickle.py\u001b[0m in \u001b[0;36msave_function_tuple\u001b[0;34m(self, func)\u001b[0m\n\u001b[1;32m    729\u001b[0m             \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'kwdefaults'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__kwdefaults__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTUPLE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    886\u001b[0m                 \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 887\u001b[0;31m                 \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    888\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEM\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    548\u001b[0m         \u001b[0;31m# Save the reduce() output and finally memoize the object\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 549\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_reduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mrv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    550\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_reduce\u001b[0;34m(self, func, args, state, listitems, dictitems, obj)\u001b[0m\n\u001b[1;32m    661\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mstate\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 662\u001b[0;31m             \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    663\u001b[0m             \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBUILD\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    505\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    855\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 856\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    857\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    881\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 882\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    883\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    523\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mreduce\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 524\u001b[0;31m                 \u001b[0mrv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mproto\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    525\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/context.py\u001b[0m in \u001b[0;36m__getnewargs__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    342\u001b[0m         raise Exception(\n\u001b[0;32m--> 343\u001b[0;31m             \u001b[0;34m\"It appears that you are attempting to reference SparkContext from a broadcast \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    344\u001b[0m             \u001b[0;34m\"variable, action, or transformation. SparkContext can only be used on the driver, \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mException\u001b[0m: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mPicklingError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-41-1465135b8334>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mpyspark\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mevaluation\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mMulticlassMetrics\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mmetrics\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mMulticlassMetrics\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabelsAndPreds_te\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mlabelsAndPreds_te\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Confusion Matrix:\\n{}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfusionMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtoArray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/mllib/evaluation.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, predictionAndLabels)\u001b[0m\n\u001b[1;32m    254\u001b[0m         \u001b[0msc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpredictionAndLabels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mctx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    255\u001b[0m         \u001b[0msql_ctx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSQLContext\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetOrCreate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 256\u001b[0;31m         \u001b[0mnumCol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredictionAndLabels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfirst\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    257\u001b[0m         schema = StructType([\n\u001b[1;32m    258\u001b[0m             \u001b[0mStructField\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"prediction\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mDoubleType\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnullable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mfirst\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1462\u001b[0m         \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mRDD\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mempty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1463\u001b[0m         \"\"\"\n\u001b[0;32m-> 1464\u001b[0;31m         \u001b[0mrs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1465\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mrs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1466\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mrs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mtake\u001b[0;34m(self, num)\u001b[0m\n\u001b[1;32m   1444\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1445\u001b[0m             \u001b[0mp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpartsScanned\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpartsScanned\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mnumPartsToTry\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtotalParts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1446\u001b[0;31m             \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontext\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrunJob\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtakeUpToNumLeft\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1447\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1448\u001b[0m             \u001b[0mitems\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/context.py\u001b[0m in \u001b[0;36mrunJob\u001b[0;34m(self, rdd, partitionFunc, partitions, allowLocal)\u001b[0m\n\u001b[1;32m   1135\u001b[0m         \u001b[0;31m# SparkContext#runJob.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1136\u001b[0m         \u001b[0mmappedRDD\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrdd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpartitionFunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1137\u001b[0;31m         \u001b[0msock_info\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPythonRDD\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrunJob\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jsc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmappedRDD\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jrdd\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpartitions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1138\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_load_from_socket\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msock_info\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmappedRDD\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jrdd_deserializer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1139\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36m_jrdd\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   2627\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2628\u001b[0m         wrapped_func = _wrap_function(self.ctx, self.func, self._prev_jrdd_deserializer,\n\u001b[0;32m-> 2629\u001b[0;31m                                       self._jrdd_deserializer, profiler)\n\u001b[0m\u001b[1;32m   2630\u001b[0m         python_rdd = self.ctx._jvm.PythonRDD(self._prev_jrdd.rdd(), wrapped_func,\n\u001b[1;32m   2631\u001b[0m                                              self.preservesPartitioning, self.is_barrier)\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36m_wrap_function\u001b[0;34m(sc, func, deserializer, serializer, profiler)\u001b[0m\n\u001b[1;32m   2515\u001b[0m     \u001b[0;32massert\u001b[0m \u001b[0mserializer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"serializer should not be empty\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2516\u001b[0m     \u001b[0mcommand\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprofiler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdeserializer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mserializer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2517\u001b[0;31m     \u001b[0mpickled_command\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbroadcast_vars\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mincludes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_prepare_for_python_RDD\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcommand\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2518\u001b[0m     return sc._jvm.PythonFunction(bytearray(pickled_command), env, includes, sc.pythonExec,\n\u001b[1;32m   2519\u001b[0m                                   sc.pythonVer, broadcast_vars, sc._javaAccumulator)\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36m_prepare_for_python_RDD\u001b[0;34m(sc, command)\u001b[0m\n\u001b[1;32m   2501\u001b[0m     \u001b[0;31m# the serialized command will be compressed by broadcast\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2502\u001b[0m     \u001b[0mser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCloudPickleSerializer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2503\u001b[0;31m     \u001b[0mpickled_command\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2504\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpickled_command\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0msc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPythonUtils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetBroadcastThreshold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jsc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m# Default 1M\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2505\u001b[0m         \u001b[0;31m# The broadcast will have same life cycle as created PythonRDD\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pyspark/serializers.py\u001b[0m in \u001b[0;36mdumps\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    476\u001b[0m                 \u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"Could not serialize object: %s: %s\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0memsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    477\u001b[0m             \u001b[0mprint_exec\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstderr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 478\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPicklingError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    480\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mPicklingError\u001b[0m: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063."
     ]
    }
   ],
   "source": [
    "from pyspark.mllib.evaluation import MulticlassMetrics\n",
    "\n",
    "metrics = MulticlassMetrics(labelsAndPreds_te)\n",
    "labelsAndPreds_te.take(3)\n",
    "print(\"Confusion Matrix:\\n{}\".format(metrics.confusionMatrix().toArray()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#from pyspark.mllib.classification import LogisticRegressionWithLBFGS\n",
    "\n",
    "# train logistic regression model with training data\n",
    "#model = LogisticRegressionWithLBFGS.train(train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model accuracy (train): 0.7654372955995208\n"
     ]
    }
   ],
   "source": [
    "# Evaluating the model on training data\n",
    "#labelsAndPreds_tr = train.map(lambda p: (p.label, model.predict(p.features)))\n",
    "#accuracy_tr = 1.0 * labelsAndPreds_tr.filter(lambda pl: pl[0] == pl[1]).count() / train_count\n",
    "#print('model accuracy (train): {}'.format(accuracy_tr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model accuracy (test): 0.7631966192506509\n"
     ]
    }
   ],
   "source": [
    "# Evaluating the model on test data\n",
    "#labelsAndPreds_te = test.map(lambda p: (p.label, model.predict(p.features)))\n",
    "#accuracy_te = 1.0 * labelsAndPreds_te.filter(lambda pl: pl[0] == pl[1]).count() / test_count\n",
    "#print('model accuracy (test): {}'.format(accuracy_te))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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