Project_1B_ Project_Template.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "# Part I. ETL Pipeline for Pre-Processing the Files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## PLEASE RUN THE FOLLOWING CODE FOR PRE-PROCESSING THE FILES"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Import Python packages "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import cassandra\n",
    "import re\n",
    "import os\n",
    "import glob\n",
    "import numpy as np\n",
    "import json\n",
    "import csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Creating list of filepaths to process original event csv data files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/workspace\n"
     ]
    }
   ],
   "source": [
    "print(os.getcwd())\n",
    "filepath = os.getcwd() + '/event_data'\n",
    "for root, dirs, files in os.walk(filepath):\n",
    "    file_path_list = glob.glob(os.path.join(root,'*'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Processing the files to create the data file csv that will be used for Apache Casssandra tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "full_data_rows_list = [] \n",
    "for f in file_path_list:\n",
    "\n",
    "    with open(f, 'r', encoding = 'utf8', newline='') as csvfile: \n",
    "        csvreader = csv.reader(csvfile) \n",
    "        next(csvreader)\n",
    "         \n",
    "        for line in csvreader:\n",
    "            full_data_rows_list.append(line) \n",
    "            \n",
    "\n",
    "csv.register_dialect('myDialect', quoting=csv.QUOTE_ALL, skipinitialspace=True)\n",
    "with open('event_datafile_new.csv', 'w', encoding = 'utf8', newline='') as f:\n",
    "    writer = csv.writer(f, dialect='myDialect')\n",
    "    writer.writerow(['artist','firstName','gender','itemInSession','lastName','length','level','location','sessionId','song','userId'])\n",
    "    for row in full_data_rows_list:\n",
    "        if (row[0] == ''):\n",
    "            continue\n",
    "        writer.writerow((row[0], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[12], row[13], row[16]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6821\n"
     ]
    }
   ],
   "source": [
    "with open('event_datafile_new.csv', 'r', encoding = 'utf8') as f:\n",
    "    print(sum(1 for line in f))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "# Part II. Complete the Apache Cassandra coding portion of your project. \n",
    "\n",
    "## Now you are ready to work with the CSV file titled <font color=red>event_datafile_new.csv</font>, located within the Workspace directory.  The event_datafile_new.csv contains the following columns: \n",
    "- artist \n",
    "- firstName of user\n",
    "- gender of user\n",
    "- item number in session\n",
    "- last name of user\n",
    "- length of the song\n",
    "- level (paid or free song)\n",
    "- location of the user\n",
    "- sessionId\n",
    "- song title\n",
    "- userId\n",
    "\n",
    "The image below is a screenshot of what the denormalized data should appear like in the <font color=red>**event_datafile_new.csv**</font> after the code above is run:<br>\n",
    "\n",
    "<img src=\"images/image_event_datafile_new.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## Begin writing your Apache Cassandra code in the cells below"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Creating a Cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "from cassandra.cluster import Cluster\n",
    "cluster = Cluster()\n",
    "\n",
    "# To establish connection and begin executing queries, need a session\n",
    "session = cluster.connect()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Create Keyspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    session.execute(\"\"\"CREATE KEYSPACE IF NOT EXISTS project2 WITH REPLICATION={ 'class' : 'SimpleStrategy', 'replication_factor' : 1 }\"\"\")\n",
    "except Exception as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Set Keyspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    session.set_keyspace('project2')\n",
    "except Exception as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "### Now we need to create tables to run the following queries. Remember, with Apache Cassandra you model the database tables on the queries you want to run."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## Create queries to ask the following three questions of the data\n",
    "\n",
    "### 1. Give me the artist, song title and song's length in the music app history that was heard during  sessionId = 338, and itemInSession  = 4\n",
    "\n",
    "\n",
    "### 2. Give me only the following: name of artist, song (sorted by itemInSession) and user (first and last name) for userid = 10, sessionid = 182\n",
    "    \n",
    "\n",
    "### 3. Give me every user name (first and last) in my music app history who listened to the song 'All Hands Against His Own'\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "query = \"CREATE TABLE IF NOT EXISTS song_history_by_session_and_iteminSession\"\n",
    "query = query + \"(SESSIONID int, ITEMINSESSION int, ARTIST text, SONG text, LENGTH float, primary key((SESSIONID),ITEMINSESSION))\"\n",
    "try:\n",
    "    session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "file = 'event_datafile_new.csv'\n",
    "with open(file, encoding = 'utf8') as f:\n",
    "    csvreader = csv.reader(f)\n",
    "    next(csvreader) \n",
    "    for line in csvreader:\n",
    "        query = \"INSERT INTO song_history_by_session_and_iteminSession (SESSIONID, ITEMINSESSION, ARTIST, SONG, LENGTH)\"\n",
    "        query = query + \" VALUES (%s, %s, %s, %s, %s)\"\n",
    "        session.execute(query, ( int(line[8]), int(line[3]), line[0], line[9], float(line[5])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Do a SELECT to verify that the data have been inserted into each table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Row(artist='Faithless', song='Music Matters (Mark Knight Dub)', length=495.30731201171875)\n"
     ]
    }
   ],
   "source": [
    "query = \"SELECT ARTIST,SONG,LENGTH from song_history_by_session_and_iteminSession where SESSIONID=338 and ITEMINSESSION=4\"\n",
    "try:\n",
    "    rows = session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "for row in rows:\n",
    "    print (row)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "### COPY AND REPEAT THE ABOVE THREE CELLS FOR EACH OF THE THREE QUESTIONS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "query = \"CREATE TABLE IF NOT EXISTS song_history_by_user_and_session\"\n",
    "query = query + \"( USERID int, SESSIONID int, ITEMINSESSION int, ARTIST text, USER text, SONG text, primary key((USERID,SESSIONID),ITEMINSESSION))\"\n",
    "try:\n",
    "    session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "file = 'event_datafile_new.csv'\n",
    "with open(file, encoding = 'utf8') as f:\n",
    "    csvreader = csv.reader(f)\n",
    "    next(csvreader) \n",
    "    for line in csvreader:\n",
    "        user = line[1]+\" \"+line[4]\n",
    "        query = \"INSERT INTO song_history_by_user_and_session (USERID, SESSIONID, ITEMINSESSION, ARTIST, USER, SONG)\"\n",
    "        query = query + \" VALUES (%s, %s, %s, %s, %s, %s)\"\n",
    "        session.execute(query, ( int(line[10]), int(line[8]), int(line[3]), line[0], user, line[9]))\n",
    "        \n",
    "                 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "Run SELECT query to verify table model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Row(artist='Down To The Bone', song=\"Keep On Keepin' On\", user='Sylvie Cruz')\n",
      "Row(artist='Three Drives', song='Greece 2000', user='Sylvie Cruz')\n",
      "Row(artist='Sebastien Tellier', song='Kilometer', user='Sylvie Cruz')\n",
      "Row(artist='Lonnie Gordon', song='Catch You Baby (Steve Pitron & Max Sanna Radio Edit)', user='Sylvie Cruz')\n"
     ]
    }
   ],
   "source": [
    "query = \"SELECT ARTIST,SONG,USER from song_history_by_user_and_session where USERID = 10 and SESSIONID = 182\"\n",
    "try:\n",
    "    rows = session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "for row in rows:\n",
    "    print (row) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "query = \"create table if not exists user_by_song_heard \"\n",
    "query = \"CREATE TABLE IF NOT EXISTS user_by_song_heard\"\n",
    "query = query + \"( SONG text, USERID int, USER text, primary key((SONG), USERID))\"\n",
    "try:\n",
    "    session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "file = 'event_datafile_new.csv'\n",
    "with open(file, encoding = 'utf8') as f:\n",
    "    csvreader = csv.reader(f)\n",
    "    next(csvreader) \n",
    "    for line in csvreader:\n",
    "        user = line[1]+\" \"+line[4]\n",
    "        query = \"INSERT INTO user_by_song_heard (SONG, USERID, USER)\"\n",
    "        query = query + \" VALUES (%s, %s, %s)\"\n",
    "        session.execute(query, (line[9], int(line[10]), user))\n",
    "                   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "Run SELECT query to verify table model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Row(song='All Hands Against His Own', user='Jacqueline Lynch')\n",
      "Row(song='All Hands Against His Own', user='Tegan Levine')\n",
      "Row(song='All Hands Against His Own', user='Sara Johnson')\n"
     ]
    }
   ],
   "source": [
    "query = \"SELECT SONG, USER from user_by_song_heard WHERE SONG ='All Hands Against His Own'\"\n",
    "try:\n",
    "    rows = session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "for row in rows:\n",
    "    print (row) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "### Drop the tables before closing out the sessions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "query = \"DROP TABLE song_history_by_session_and_iteminSession\"\n",
    "try:\n",
    "    rows = session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "\n",
    "query = \"DROP TABLE song_history_by_user_and_session\"\n",
    "try:\n",
    "    rows = session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "    \n",
    "query = \"DROP TABLE user_by_song_heard\"\n",
    "try:\n",
    "    rows = session.execute(query)\n",
    "except Exception as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "### Close the session and cluster connection¶"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "session.shutdown()\n",
    "cluster.shutdown()"
   ]
  }
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