Spark with Amazon S3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# see http://www.supergloo.com/fieldnotes/apache-spark-amazon-s3-examples-of-text-files "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35218"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc._jsc.hadoopConfiguration().set(\"fs.s3n.awsAccessKeyId\", \"notreal-QGVOJWQ\")\n",
    "sc._jsc.hadoopConfiguration().set(\"fs.s3n.awsSecretAccessKey\", \"notreal-yi+e7i1Z6kJANKt\")\n",
    "sc.textFile(\"s3n://supergloospark/baby_names.csv\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "206"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myRDD = sc.textFile(\"s3n://supergloospark/baby_names.csv\")\n",
    "subset = myRDD.filter(lambda line: \"MICHAEL\" in line)\n",
    "sc._jsc.hadoopConfiguration().set(\"fs.s3.awsAccessKeyId\", \"notreal-PLUQGVOJWQ\")\n",
    "sc._jsc.hadoopConfiguration().set(\"fs.s3.awsSecretAccessKey\", \"notreal-GdevWcyi+e7i1Z6kJANKt\")\n",
    "subset.saveAsTextFile(\"s3://supergloospark/python_example_baby_names_s3_not_s3n.csv\")\n",
    "sc.textFile(\"s3://supergloospark/python_example_baby_names_s3_not_s3n.csv\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "Py4JJavaError",
     "evalue": "An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.\n: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: s3://supergloospark/baby_names.csv\n\tat org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:285)\n\tat org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)\n\tat org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:304)\n\tat org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:207)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:217)\n\tat org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:217)\n\tat org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:58)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:217)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:1781)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:885)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)\n\tat org.apache.spark.rdd.RDD.withScope(RDD.scala:286)\n\tat org.apache.spark.rdd.RDD.collect(RDD.scala:884)\n\tat org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:378)\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:497)\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)\n\tat py4j.Gateway.invoke(Gateway.java:259)\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:207)\n\tat java.lang.Thread.run(Thread.java:745)\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-20-109130911dea>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# interoperability between s3 and s3n?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0msc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtextFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"s3://supergloospark/baby_names.csv\"\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[0m\n\u001b[0m",
      "\u001b[0;32m/Users/toddmcgrath/Development/spark-1.4.1-bin-hadoop2.4/python/pyspark/rdd.pyc\u001b[0m in \u001b[0;36mcount\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    982\u001b[0m         \u001b[0;36m3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    983\u001b[0m         \"\"\"\n\u001b[0;32m--> 984\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[0m\n\u001b[0m\u001b[1;32m    985\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    986\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[0m\n",
      "\u001b[0;32m/Users/toddmcgrath/Development/spark-1.4.1-bin-hadoop2.4/python/pyspark/rdd.pyc\u001b[0m in \u001b[0;36msum\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    973\u001b[0m         \u001b[0;36m6.0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    974\u001b[0m         \"\"\"\n\u001b[0;32m--> 975\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[0m\n\u001b[0m\u001b[1;32m    976\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    977\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[0m\n",
      "\u001b[0;32m/Users/toddmcgrath/Development/spark-1.4.1-bin-hadoop2.4/python/pyspark/rdd.pyc\u001b[0m in \u001b[0;36mfold\u001b[0;34m(self, zeroValue, op)\u001b[0m\n\u001b[1;32m    850\u001b[0m                 \u001b[0macc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0macc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    851\u001b[0m             \u001b[0;32myield\u001b[0m \u001b[0macc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 852\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[0m\n\u001b[0m\u001b[1;32m    853\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[0m\n\u001b[1;32m    854\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/toddmcgrath/Development/spark-1.4.1-bin-hadoop2.4/python/pyspark/rdd.pyc\u001b[0m in \u001b[0;36mcollect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    755\u001b[0m         \"\"\"\n\u001b[1;32m    756\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--> 757\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    758\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    759\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/toddmcgrath/Development/spark-1.4.1-bin-hadoop2.4/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m    536\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    537\u001b[0m         return_value = get_return_value(answer, self.gateway_client,\n\u001b[0;32m--> 538\u001b[0;31m                 self.target_id, self.name)\n\u001b[0m\u001b[1;32m    539\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    540\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/Users/toddmcgrath/Development/spark-1.4.1-bin-hadoop2.4/python/lib/py4j-0.8.2.1-src.zip/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    298\u001b[0m                 raise Py4JJavaError(\n\u001b[1;32m    299\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--> 300\u001b[0;31m                     format(target_id, '.', name), value)\n\u001b[0m\u001b[1;32m    301\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    302\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.hadoop.mapred.InvalidInputException: Input path does not exist: s3://supergloospark/baby_names.csv\n\tat org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:285)\n\tat org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)\n\tat org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:304)\n\tat org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:207)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:217)\n\tat org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:217)\n\tat org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:58)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:217)\n\tat org.apache.spark.SparkContext.runJob(SparkContext.scala:1781)\n\tat org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:885)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)\n\tat org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)\n\tat org.apache.spark.rdd.RDD.withScope(RDD.scala:286)\n\tat org.apache.spark.rdd.RDD.collect(RDD.scala:884)\n\tat org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:378)\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:497)\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)\n\tat py4j.Gateway.invoke(Gateway.java:259)\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:207)\n\tat java.lang.Thread.run(Thread.java:745)\n"
     ]
    }
   ],
   "source": [
    "# interoperability between s3 and s3n?\n",
    "sc.textFile(\"s3://supergloospark/baby_names.csv\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35218"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " sc.textFile(\"s3n://supergloospark/baby_names.csv\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "206"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc.textFile(\"s3://supergloospark/python_example_baby_names_s3_not_s3n.csv\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
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