one_hot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime as datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image\n",
    "plt.style.use('default') # haciendo los graficos un poco mas bonitos xD\n",
    "plt.rcParams['figure.figsize'] = (15, 5)\n",
    "from pyspark import SparkContext\n",
    "from pyspark import SparkConf\n",
    "import pyspark as ps\n",
    "\n",
    "try: \n",
    "    type(sc)\n",
    "except NameError:\n",
    "    sc = ps.SparkContext('local[*]')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>idaviso</th>\n",
       "      <th>idpais</th>\n",
       "      <th>titulo</th>\n",
       "      <th>descripcion</th>\n",
       "      <th>nombre_zona</th>\n",
       "      <th>ciudad</th>\n",
       "      <th>mapacalle</th>\n",
       "      <th>tipo_de_trabajo</th>\n",
       "      <th>nivel_laboral</th>\n",
       "      <th>nombre_area</th>\n",
       "      <th>denominacion_empresa</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1111718795</td>\n",
       "      <td>1</td>\n",
       "      <td>Licenciados/as y/o Enfermeros/as Profesionales</td>\n",
       "      <td>&lt;p&gt;En Fundación Hospitalaria nos encontramos e...</td>\n",
       "      <td>Gran Buenos Aires</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Full-time</td>\n",
       "      <td>Senior / Semi-Senior</td>\n",
       "      <td>Salud</td>\n",
       "      <td>Fundación Hospitalaria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1110497155</td>\n",
       "      <td>1</td>\n",
       "      <td>Valet parking para importante evento en hipódr...</td>\n",
       "      <td>&lt;p&gt;&lt;strong&gt;&lt;span lang=\"ES\"&gt;Adecco Hoteles y Ca...</td>\n",
       "      <td>Gran Buenos Aires</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Full-time</td>\n",
       "      <td>Senior / Semi-Senior</td>\n",
       "      <td>Camareros</td>\n",
       "      <td>Adecco -Región Office</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      idaviso  idpais                                             titulo  \\\n",
       "0  1111718795       1     Licenciados/as y/o Enfermeros/as Profesionales   \n",
       "1  1110497155       1  Valet parking para importante evento en hipódr...   \n",
       "\n",
       "                                         descripcion        nombre_zona  \\\n",
       "0  <p>En Fundación Hospitalaria nos encontramos e...  Gran Buenos Aires   \n",
       "1  <p><strong><span lang=\"ES\">Adecco Hoteles y Ca...  Gran Buenos Aires   \n",
       "\n",
       "  ciudad mapacalle tipo_de_trabajo         nivel_laboral nombre_area  \\\n",
       "0    NaN       NaN       Full-time  Senior / Semi-Senior       Salud   \n",
       "1    NaN       NaN       Full-time  Senior / Semi-Senior   Camareros   \n",
       "\n",
       "     denominacion_empresa  \n",
       "0  Fundación Hospitalaria  \n",
       "1   Adecco -Región Office  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas import Series\n",
    "avisos = pd.read_csv(\"Sources/fiuba_5_avisos_online.csv\")\n",
    "descripcion = pd.read_csv(\"Sources/fiuba_6_avisos_detalle.csv\")\n",
    "completo = pd.merge(avisos,descripcion, how = 'inner')\n",
    "completo.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "completo['descripcion'] = completo.apply(lambda x: str.upper(re.sub(\"<.*?>\", \"\", x['descripcion'])),axis=1)\n",
    "completo['descripcion'] = completo.apply(lambda x: re.sub(\"\\xa0\", \"\", x['descripcion']),axis=1)\n",
    "des = completo['descripcion'].tolist()\n",
    "idaviso = completo['idaviso'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = []\n",
    "for i in range (len(des)):\n",
    "    x.append((idaviso[i],des[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "for j in x:\n",
    "    j = tuple(j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ParallelCollectionRDD[0] at parallelize at PythonRDD.scala:175"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "des = sc.parallelize(j)\n",
    "des"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def list_features(x):\n",
    "    x = x.split(' ')\n",
    "    one_hot=[0,0,0,0,0,0,0]\n",
    "    palabras=['sabados','domingos','ingles','3 anos','2 anos','4 anos', '5 anos']\n",
    "    for i in len(x)-1:\n",
    "        if palabra in palabras:\n",
    "            one_hot[palabras.index(palabra)] = 1\n",
    "        s = x[i]+\" \"+x[i+1]\n",
    "        if s in palabras:\n",
    "            one_hot[palabras.index(palabra)] = 1\n",
    "    return one_hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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 7 in stage 3.0 failed 1 times, most recent failure: Lost task 7.0 in stage 3.0 (TID 31, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 229, in main\n    process()\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 224, in process\n    serializer.dump_stream(func(split_index, iterator), outfile)\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py\", line 372, in dump_stream\n    vs = list(itertools.islice(iterator, batch))\n  File \"<ipython-input-16-c1c03702f6be>\", line 1, in <lambda>\n  File \"<ipython-input-15-0cc01e92a6cb>\", line 2, in list_features\nAttributeError: 'list' object has no attribute 'split'\n\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n\tat scala.collection.Iterator$class.foreach(Iterator.scala:893)\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\n\tat scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)\n\tat scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)\n\tat org.apache.spark.scheduler.Task.run(Task.scala:109)\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n\tat java.lang.Thread.run(Thread.java:748)\n\nDriver stacktrace:\n\tat org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1587)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1586)\n\tat scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1586)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)\n\tat scala.Option.foreach(Option.scala:257)\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1820)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1769)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1758)\n\tat org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)\n\tat org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2027)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2048)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2067)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)\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:363)\n\tat org.apache.spark.rdd.RDD.collect(RDD.scala:938)\n\tat org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:153)\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:214)\n\tat java.lang.Thread.run(Thread.java:748)\nCaused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 229, in main\n    process()\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 224, in process\n    serializer.dump_stream(func(split_index, iterator), outfile)\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py\", line 372, in dump_stream\n    vs = list(itertools.islice(iterator, batch))\n  File \"<ipython-input-16-c1c03702f6be>\", line 1, in <lambda>\n  File \"<ipython-input-15-0cc01e92a6cb>\", line 2, in list_features\nAttributeError: 'list' object has no attribute 'split'\n\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n\tat scala.collection.Iterator$class.foreach(Iterator.scala:893)\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\n\tat scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)\n\tat scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)\n\tat org.apache.spark.scheduler.Task.run(Task.scala:109)\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n\t... 1 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-16-c1c03702f6be>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdes\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[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\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[0;34m)\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[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlist_features\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\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[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[0m\n\u001b[0m",
      "\u001b[0;32m/anaconda3/lib/python3.6/site-packages/pyspark/rdd.py\u001b[0m in \u001b[0;36mcollect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    822\u001b[0m         \"\"\"\n\u001b[1;32m    823\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[0m\n\u001b[0;32m--> 824\u001b[0;31m             \u001b[0mport\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[0m\n\u001b[0m\u001b[1;32m    825\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[0mport\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[0m\n\u001b[1;32m    826\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda3/lib/python3.6/site-packages/py4j/java_gateway.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m   1158\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[0m\n\u001b[1;32m   1159\u001b[0m         return_value = get_return_value(\n\u001b[0;32m-> 1160\u001b[0;31m             answer, self.gateway_client, self.target_id, self.name)\n\u001b[0m\u001b[1;32m   1161\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1162\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[0m\n",
      "\u001b[0;32m/anaconda3/lib/python3.6/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    318\u001b[0m                 raise Py4JJavaError(\n\u001b[1;32m    319\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[0m\n\u001b[0;32m--> 320\u001b[0;31m                     format(target_id, \".\", name), value)\n\u001b[0m\u001b[1;32m    321\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    322\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 7 in stage 3.0 failed 1 times, most recent failure: Lost task 7.0 in stage 3.0 (TID 31, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 229, in main\n    process()\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 224, in process\n    serializer.dump_stream(func(split_index, iterator), outfile)\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py\", line 372, in dump_stream\n    vs = list(itertools.islice(iterator, batch))\n  File \"<ipython-input-16-c1c03702f6be>\", line 1, in <lambda>\n  File \"<ipython-input-15-0cc01e92a6cb>\", line 2, in list_features\nAttributeError: 'list' object has no attribute 'split'\n\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n\tat scala.collection.Iterator$class.foreach(Iterator.scala:893)\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\n\tat scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)\n\tat scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)\n\tat org.apache.spark.scheduler.Task.run(Task.scala:109)\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n\tat java.lang.Thread.run(Thread.java:748)\n\nDriver stacktrace:\n\tat org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1587)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1586)\n\tat scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1586)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)\n\tat scala.Option.foreach(Option.scala:257)\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1820)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1769)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1758)\n\tat org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)\n\tat org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2027)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2048)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2067)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)\n\tat org.apache.spark.rdd.RDD.withScope(RDD.scala:363)\n\tat org.apache.spark.rdd.RDD.collect(RDD.scala:938)\n\tat org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:153)\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:214)\n\tat java.lang.Thread.run(Thread.java:748)\nCaused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 229, in main\n    process()\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py\", line 224, in process\n    serializer.dump_stream(func(split_index, iterator), outfile)\n  File \"/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py\", line 372, in dump_stream\n    vs = list(itertools.islice(iterator, batch))\n  File \"<ipython-input-16-c1c03702f6be>\", line 1, in <lambda>\n  File \"<ipython-input-15-0cc01e92a6cb>\", line 2, in list_features\nAttributeError: 'list' object has no attribute 'split'\n\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)\n\tat org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n\tat scala.collection.Iterator$class.foreach(Iterator.scala:893)\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\n\tat scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)\n\tat scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\n\tat scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)\n\tat org.apache.spark.scheduler.Task.run(Task.scala:109)\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n\t... 1 more\n"
     ]
    }
   ],
   "source": [
    "one = des.map(lambda x: (x[0], list(x[1]))).map(lambda x: (x[0],list_features(x[1]))).collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "one_hot = pd.from_records(one)"
   ]
  }
 ],
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