ml_29-Big data-Spark.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "87951a1d",
   "metadata": {},
   "source": [
    "# MLlib: Logistic Regression  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9aeebbfa",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import urllib\n",
    "import os\n",
    "\n",
    "f = urllib.request.urlretrieve(\"http://kdd.ics.uci.edu/databases/kddcup99/kddcup.data_10_percent.gz\", \"kddcup.data_10_percent.gz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ba56c1e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ['JAVA_HOME'] = 'C:\\Program Files\\Java\\jre1.8.0_301'\n",
    "os.environ['SPARK_HOME'] = 'D:\\Downloads\\spark-3.1.2-bin-hadoop3.2'\n",
    "# os.environ['SPARK_HOME'] = 'D:\\Downloads\\spark-2.4.8-bin-hadoop2.7'\n",
    "os.environ['HADOOP_HOME'] = 'D:\\Downloads\\winutils\\hadoop-2.6.0\\bin'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8f05160f",
   "metadata": {},
   "outputs": [
    {
     "ename": "Py4JJavaError",
     "evalue": "An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.\n: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0) (192.168.3.7 executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"D:\\Downloads\\spark-3.1.2-bin-hadoop3.2\\python\\lib\\pyspark.zip\\pyspark\\worker.py\", line 473, in main\nException: Python in worker has different version 3.9 than that in driver 3.8, PySpark cannot run with different minor versions. Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.\n\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:652)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:635)\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470)\r\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\r\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\r\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\r\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)\r\n\tat scala.collection.TraversableOnce.to(TraversableOnce.scala:315)\r\n\tat scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)\r\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)\r\n\tat scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)\r\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)\r\n\tat scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)\r\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\r\n\tat org.apache.spark.api.python.PythonRDD$.$anonfun$runJob$1(PythonRDD.scala:166)\r\n\tat org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)\r\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\r\n\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)\r\n\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)\r\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)\r\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)\r\n\tat java.lang.Thread.run(Unknown Source)\r\n\nDriver stacktrace:\r\n\tat org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2258)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2207)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2206)\r\n\tat scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)\r\n\tat scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)\r\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)\r\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2206)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1079)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1079)\r\n\tat scala.Option.foreach(Option.scala:407)\r\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1079)\r\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2445)\r\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2387)\r\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2376)\r\n\tat org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)\r\n\tat org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)\r\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2196)\r\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2217)\r\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2236)\r\n\tat org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:166)\r\n\tat org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)\r\n\tat java.lang.reflect.Method.invoke(Unknown Source)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\r\n\tat java.lang.Thread.run(Unknown Source)\r\nCaused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"D:\\Downloads\\spark-3.1.2-bin-hadoop3.2\\python\\lib\\pyspark.zip\\pyspark\\worker.py\", line 473, in main\nException: Python in worker has different version 3.9 than that in driver 3.8, PySpark cannot run with different minor versions. Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.\n\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:652)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:635)\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470)\r\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\r\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\r\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\r\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)\r\n\tat scala.collection.TraversableOnce.to(TraversableOnce.scala:315)\r\n\tat scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)\r\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)\r\n\tat scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)\r\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)\r\n\tat scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)\r\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\r\n\tat org.apache.spark.api.python.PythonRDD$.$anonfun$runJob$1(PythonRDD.scala:166)\r\n\tat org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)\r\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\r\n\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)\r\n\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)\r\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)\r\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)\r\n\t... 1 more\r\n",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mPy4JJavaError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-ad5eb8747746>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[0mraw_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtextFile\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata_file\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 9\u001b[1;33m \u001b[0mraw_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfirst\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pyspark\\rdd.py\u001b[0m in \u001b[0;36mfirst\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1584\u001b[0m         \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mRDD\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mempty\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1585\u001b[0m         \"\"\"\n\u001b[1;32m-> 1586\u001b[1;33m         \u001b[0mrs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1587\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mrs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1588\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mrs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pyspark\\rdd.py\u001b[0m in \u001b[0;36mtake\u001b[1;34m(self, num)\u001b[0m\n\u001b[0;32m   1564\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1565\u001b[0m             \u001b[0mp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpartsScanned\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpartsScanned\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mnumPartsToTry\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtotalParts\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1566\u001b[1;33m             \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrunJob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtakeUpToNumLeft\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1567\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1568\u001b[0m             \u001b[0mitems\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mres\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pyspark\\context.py\u001b[0m in \u001b[0;36mrunJob\u001b[1;34m(self, rdd, partitionFunc, partitions, allowLocal)\u001b[0m\n\u001b[0;32m   1231\u001b[0m         \u001b[1;31m# SparkContext#runJob.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1232\u001b[0m         \u001b[0mmappedRDD\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrdd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpartitionFunc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1233\u001b[1;33m         \u001b[0msock_info\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPythonRDD\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrunJob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jsc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmappedRDD\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jrdd\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpartitions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1234\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_load_from_socket\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msock_info\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmappedRDD\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jrdd_deserializer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1235\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\py4j\\java_gateway.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m   1302\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1303\u001b[0m         \u001b[0manswer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgateway_client\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend_command\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1304\u001b[1;33m         return_value = get_return_value(\n\u001b[0m\u001b[0;32m   1305\u001b[0m             answer, self.gateway_client, self.target_id, self.name)\n\u001b[0;32m   1306\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\py4j\\protocol.py\u001b[0m in \u001b[0;36mget_return_value\u001b[1;34m(answer, gateway_client, target_id, name)\u001b[0m\n\u001b[0;32m    324\u001b[0m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mOUTPUT_CONVERTER\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0manswer\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgateway_client\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    325\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0manswer\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mREFERENCE_TYPE\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 326\u001b[1;33m                 raise Py4JJavaError(\n\u001b[0m\u001b[0;32m    327\u001b[0m                     \u001b[1;34m\"An error occurred while calling {0}{1}{2}.\\n\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    328\u001b[0m                     format(target_id, \".\", name), value)\n",
      "\u001b[1;31mPy4JJavaError\u001b[0m: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.\n: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0) (192.168.3.7 executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"D:\\Downloads\\spark-3.1.2-bin-hadoop3.2\\python\\lib\\pyspark.zip\\pyspark\\worker.py\", line 473, in main\nException: Python in worker has different version 3.9 than that in driver 3.8, PySpark cannot run with different minor versions. Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.\n\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:652)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:635)\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470)\r\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\r\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\r\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\r\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)\r\n\tat scala.collection.TraversableOnce.to(TraversableOnce.scala:315)\r\n\tat scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)\r\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)\r\n\tat scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)\r\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)\r\n\tat scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)\r\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\r\n\tat org.apache.spark.api.python.PythonRDD$.$anonfun$runJob$1(PythonRDD.scala:166)\r\n\tat org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)\r\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\r\n\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)\r\n\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)\r\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)\r\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)\r\n\tat java.lang.Thread.run(Unknown Source)\r\n\nDriver stacktrace:\r\n\tat org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2258)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2207)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2206)\r\n\tat scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)\r\n\tat scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)\r\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)\r\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2206)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1079)\r\n\tat org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1079)\r\n\tat scala.Option.foreach(Option.scala:407)\r\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1079)\r\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2445)\r\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2387)\r\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2376)\r\n\tat org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)\r\n\tat org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)\r\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2196)\r\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2217)\r\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:2236)\r\n\tat org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:166)\r\n\tat org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)\r\n\tat java.lang.reflect.Method.invoke(Unknown Source)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\r\n\tat java.lang.Thread.run(Unknown Source)\r\nCaused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n  File \"D:\\Downloads\\spark-3.1.2-bin-hadoop3.2\\python\\lib\\pyspark.zip\\pyspark\\worker.py\", line 473, in main\nException: Python in worker has different version 3.9 than that in driver 3.8, PySpark cannot run with different minor versions. Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.\n\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:652)\r\n\tat org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:635)\r\n\tat org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470)\r\n\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\r\n\tat scala.collection.Iterator.foreach(Iterator.scala:941)\r\n\tat scala.collection.Iterator.foreach$(Iterator.scala:941)\r\n\tat org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)\r\n\tat scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)\r\n\tat scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)\r\n\tat scala.collection.TraversableOnce.to(TraversableOnce.scala:315)\r\n\tat scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)\r\n\tat org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)\r\n\tat scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)\r\n\tat org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)\r\n\tat scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)\r\n\tat scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)\r\n\tat org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)\r\n\tat org.apache.spark.api.python.PythonRDD$.$anonfun$runJob$1(PythonRDD.scala:166)\r\n\tat org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2236)\r\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\r\n\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)\r\n\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\r\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)\r\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)\r\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)\r\n\t... 1 more\r\n"
     ]
    }
   ],
   "source": [
    "from pyspark import SparkConf\n",
    "from pyspark.context import SparkContext\n",
    "import pandas as pd\n",
    "sc = SparkContext.getOrCreate(SparkConf())\n",
    "\n",
    "data_file = 'datasets/kddcup.data.gz'\n",
    "\n",
    "raw_data = sc.textFile(data_file).cache()\n",
    "raw_data.first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1617b421",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql import SQLContext\n",
    "sqlContext = SQLContext(sc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ddd646a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql import Row\n",
    "\n",
    "csv_data = raw_data.map(lambda l: l.split(\",\"))\n",
    "row_data = csv_data.map(lambda p: Row(\n",
    "    duration=int(p[0]),\n",
    "    protocol_type=p[1],\n",
    "    service=p[2],\n",
    "    flag=p[3],\n",
    "    src_bytes=int(p[4]),\n",
    "    dst_bytes=int(p[5])\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e9afa08e",
   "metadata": {},
   "outputs": [],
   "source": [
    "row_data.first()\n",
    "# interactions_df = sqlContext.createDataFrame(row_data)\n",
    "# interactions_df.registerTempTable('interactions')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b0bc1bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "tcp_interactions = sqlContext.sql(\"\"\"\n",
    "    SELECT duration, dst_bytes FROM interactions WHERE protocol_type = 'tcp' AND duration > 1000 AND dts_bytes = 0\n",
    "\"\"\")\n",
    "tcp_interactions.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f9b1bc68",
   "metadata": {},
   "outputs": [],
   "source": [
    "interactions_df.printSchema()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f1149ed",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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