spark/ExtraQuery.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyspark\n",
    "from datetime import datetime\n",
    "from pyspark.sql.types import IntegerType, FloatType\n",
    "from pyspark.sql.functions import udf,lit\n",
    "\n",
    "from pyspark.sql import SQLContext\n",
    "\n",
    "sc = pyspark.SparkContext.getOrCreate()\n",
    "sqlContext = SQLContext(sc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extra query: Taxi time in and out per year and airport\n",
    "## SQL version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = sqlContext.read.format('com.databricks.spark.csv').options(header='true', inferschema='true')\\\n",
    "        .load(\"../BDdata/1994.csv\")\n",
    "for i in range(1995,2009):\n",
    "    d = d.union(sqlContext.read.format('com.databricks.spark.csv').options(header='true', inferschema='true')\\\n",
    "            .load('../BDdata/'+str(i)+'.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+------+-----------------+----+----+----------------+\n",
      "|Year|Origin|sum(sum(TaxiOut))|Year|Dest|sum(sum(TaxiIn))|\n",
      "+----+------+-----------------+----+----+----------------+\n",
      "|1995|   FCA|           9369.0|1995| FCA|          4209.0|\n",
      "|1998|   EWR|        3299816.0|1998| EWR|        995037.0|\n",
      "|1998|   JNU|          50459.0|1998| JNU|         13645.0|\n",
      "|1999|   FAT|           3586.0|1999| FAT|          1700.0|\n",
      "|2000|   LIT|         129359.0|2000| LIT|         54305.0|\n",
      "|2000|   MSP|        2779914.0|2000| MSP|        950838.0|\n",
      "|2001|   MLU|          16237.0|2001| MLU|          7348.0|\n",
      "|2002|   MBS|          20306.0|2002| MBS|          8328.0|\n",
      "|2004|   ADQ|           3744.0|2004| ADQ|          1878.0|\n",
      "|2004|   PHL|        2779238.0|2004| PHL|        919327.0|\n",
      "|2005|   BZN|          63313.0|2005| BZN|         23264.0|\n",
      "|2005|   CEC|           7894.0|2005| CEC|          2924.0|\n",
      "|2005|   FSM|          19010.0|2005| FSM|         10219.0|\n",
      "|2005|   PSE|           2238.0|2005| PSE|           781.0|\n",
      "|2006|   CPR|          31976.0|2006| CPR|         11771.0|\n",
      "|2006|   SIT|          15018.0|2006| SIT|          5851.0|\n",
      "|2007|   DAB|          46768.0|2007| DAB|         13841.0|\n",
      "|2008|   ACK|           8154.0|2008| ACK|          2485.0|\n",
      "|2008|   DAB|          38618.0|2008| DAB|         10956.0|\n",
      "|1996|   BFL|           2899.0|1996| BFL|          2287.0|\n",
      "+----+------+-----------------+----+----+----------------+\n",
      "only showing top 20 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from pyspark.sql.functions import col\n",
    "\n",
    "d2 = d.where(d.TaxiIn != \"NA\").where(d.TaxiOut != \"NA\").groupBy(\"Year\",\"Origin\",\"Dest\").agg({\"TaxiIn\":\"sum\",\"TaxiOut\":\"sum\"}).orderBy(\"Year\",\"Origin\",\"Dest\")\n",
    "dd2 = d2.groupBy(\"Year\",\"Origin\").agg({\"sum(TaxiOut)\":\"sum\"}).select(\"Year\",\"Origin\",\"sum(sum(TaxiOut))\")\n",
    "dd3 = d2.groupBy(\"Year\",\"Dest\").agg({\"sum(TaxiIn)\":\"sum\"}).select(\"Year\",\"Dest\",\"sum(sum(TaxiIn))\")\n",
    "#d2.coalesce(1).write.csv(\"./extraQuery/taxi\",header=True)\n",
    "dd4 = dd2.alias(\"a\").join(dd3.alias(\"b\"), on = [col(\"a.Origin\") == col(\"b.Dest\"), col(\"a.Year\") == col(\"b.Year\")])\n",
    "dd4.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dd4.select(\"a.Year\",\"Origin\",\"sum(sum(TaxiOut))\",\"sum(sum(TaxiIn))\").withColumnRenamed(\"sum(sum(TaxiIn))\",\"TaxiIn\").withColumnRenamed(\"sum(sum(TaxiOut))\",\"TaxiOut\")\\\n",
    "    .orderBy(\"Year\",\"Origin\").coalesce(1).write.csv(\"./extraQuery/taxi\",header=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extra query: Number of flights per year between any two connected airports \n",
    "## SQL version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "d3 = d.groupBy(\"Year\",\"Origin\",\"Dest\").agg({\"*\":\"count\"}).orderBy(\"Year\",\"Origin\",\"Dest\")\n",
    "d3.coalesce(1).write.csv(\"./extraQuery/from_to\",header=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spark DataSet version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = 1994\n",
    "end = 2008\n",
    "ds = sc.textFile('../BDdata/'+str(start)+'.csv')\n",
    "head = ds.take(1)[0]\n",
    "ds = ds.filter(lambda x : x != head)\n",
    "for i in range(start+1,end+1):\n",
    "    ds = ds.union(sc.textFile('../BDdata/'+str(i)+'.csv').filter(lambda x : x != head))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "h = head.split(\",\")\n",
    "index = lambda x : h.index(x)\n",
    "\n",
    "from operator import add\n",
    "res = sorted(ds.map(lambda x : x.split(\",\"))\\\n",
    "                .map(lambda x : ((x[index(\"Year\")], x[index(\"Origin\")], x[index(\"Dest\")]), 1))\\\n",
    "                .reduceByKey(lambda x, y : x+y)\\\n",
    "                .collect())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " (('1994', 'ANC', 'SCC'), 450),\n",
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       " (('1994', 'DLH', 'MSP'), 1762),\n",
       " ...]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  }
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