course2-big-data-analysis/c02w06-Demo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.types import StructType, StructField, IntegerType\n",
    "from pyspark.sql.functions import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql import SparkSession\n",
    "spark = SparkSession.builder.enableHiveSupport().master(\"local[2]\").getOrCreate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "graph_schema = StructType([\n",
    "    StructField(\"to\", IntegerType(), False),\n",
    "    StructField(\"from\", IntegerType(), False)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dist_schema = StructType([\n",
    "    StructField(\"vertex\", IntegerType(), False),\n",
    "    StructField(\"distance\", IntegerType(), False)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def shortest_path(v_from, v_to, dataset_path=None):\n",
    "    edges = spark.read.csv(dataset_path, sep=\"\\t\", schema=graph_schema)\n",
    "    path_length = None\n",
    "    \n",
    "    # Here you should implement the BFS algorithm. It should return the length\n",
    "    # of the minimal path (single integer) between v_from and v_to\n",
    "    \n",
    "    return path_length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    }
   ],
   "source": [
    "print shortest_path(12, 34, \"/data/twitter/twitter_sample2.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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