Data_Modeling_Apache_Cassandra/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 Python packages \n",
    "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": [
      "Printing current working directory : /home/workspace\n",
      "File path of datasets : /home/workspace/event_data\n",
      " \n",
      "Walking files and collecting data ...\n",
      "Number of data files paths collected: 30\n",
      "['/home/workspace/event_data/2018-11-27-events.csv', '/home/workspace/event_data/2018-11-04-events.csv', '/home/workspace/event_data/2018-11-07-events.csv', '/home/workspace/event_data/2018-11-09-events.csv', '/home/workspace/event_data/2018-11-19-events.csv', '/home/workspace/event_data/2018-11-05-events.csv', '/home/workspace/event_data/2018-11-22-events.csv', '/home/workspace/event_data/2018-11-16-events.csv', '/home/workspace/event_data/2018-11-26-events.csv', '/home/workspace/event_data/2018-11-24-events.csv', '/home/workspace/event_data/2018-11-29-events.csv', '/home/workspace/event_data/2018-11-15-events.csv', '/home/workspace/event_data/2018-11-20-events.csv', '/home/workspace/event_data/2018-11-06-events.csv', '/home/workspace/event_data/2018-11-18-events.csv', '/home/workspace/event_data/2018-11-21-events.csv', '/home/workspace/event_data/2018-11-10-events.csv', '/home/workspace/event_data/2018-11-23-events.csv', '/home/workspace/event_data/2018-11-02-events.csv', '/home/workspace/event_data/2018-11-28-events.csv', '/home/workspace/event_data/2018-11-03-events.csv', '/home/workspace/event_data/2018-11-13-events.csv', '/home/workspace/event_data/2018-11-30-events.csv', '/home/workspace/event_data/2018-11-12-events.csv', '/home/workspace/event_data/2018-11-01-events.csv', '/home/workspace/event_data/2018-11-14-events.csv', '/home/workspace/event_data/2018-11-25-events.csv', '/home/workspace/event_data/2018-11-08-events.csv', '/home/workspace/event_data/2018-11-17-events.csv', '/home/workspace/event_data/2018-11-11-events.csv']\n"
     ]
    }
   ],
   "source": [
    "# checking your current working directory\n",
    "print(f\"Printing current working directory : {os.getcwd()}\")\n",
    "\n",
    "# Get your current folder and subfolder event data\n",
    "filepath = os.getcwd() + '/event_data'\n",
    "\n",
    "print(f\"File path of datasets : {filepath}\")\n",
    "print(\" \")\n",
    "print(\"Walking files and collecting data ...\")\n",
    "\n",
    "# Create a for loop to create a list of files and collect each filepath\n",
    "for root, dirs, files in os.walk(filepath):\n",
    "    \n",
    "# join the file path and roots with the subdirectories using glob\n",
    "    file_path_list = glob.glob(os.path.join(root,'*'))\n",
    "    #print(file_path_list)\n",
    "\n",
    "print(f\"Number of data files paths collected: {len(file_path_list)}\")\n",
    "print(file_path_list)"
   ]
  },
  {
   "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": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of rows for all data collected : 8056\n",
      "Head of dataset collect : [['Barry Tuckwell/Academy of St Martin-in-the-Fields/Sir Neville Marriner', 'Logged In', 'Mohammad', 'M', '0', 'Rodriguez', '277.15873', 'paid', 'Sacramento--Roseville--Arden-Arcade, CA', 'PUT', 'NextSong', '1.54051E+12', '961', 'Horn Concerto No. 4 in E flat K495: II. Romance (Andante cantabile)', '200', '1.54328E+12', '88'], ['Jimi Hendrix', 'Logged In', 'Mohammad', 'M', '1', 'Rodriguez', '239.82975', 'paid', 'Sacramento--Roseville--Arden-Arcade, CA', 'PUT', 'NextSong', '1.54051E+12', '961', 'Woodstock Inprovisation', '200', '1.54328E+12', '88'], ['Building 429', 'Logged In', 'Mohammad', 'M', '2', 'Rodriguez', '300.61669', 'paid', 'Sacramento--Roseville--Arden-Arcade, CA', 'PUT', 'NextSong', '1.54051E+12', '961', 'Majesty (LP Version)', '200', '1.54328E+12', '88'], [\"The B-52's\", 'Logged In', 'Gianna', 'F', '0', 'Jones', '321.54077', 'free', 'New York-Newark-Jersey City, NY-NJ-PA', 'PUT', 'NextSong', '1.54087E+12', '107', 'Love Shack', '200', '1.54328E+12', '38'], ['Die Mooskirchner', 'Logged In', 'Gianna', 'F', '1', 'Jones', '169.29914', 'free', 'New York-Newark-Jersey City, NY-NJ-PA', 'PUT', 'NextSong', '1.54087E+12', '107', \"Frisch und g'sund\", '200', '1.54328E+12', '38']]\n"
     ]
    }
   ],
   "source": [
    "# initiating an empty list of rows that will be generated from each file\n",
    "full_data_rows_list = [] \n",
    "    \n",
    "# for every filepath in the file path list \n",
    "for f in file_path_list:\n",
    "\n",
    "# reading csv file \n",
    "    with open(f, 'r', encoding = 'utf8', newline='') as csvfile: \n",
    "        # creating a csv reader object \n",
    "        csvreader = csv.reader(csvfile) \n",
    "        next(csvreader)\n",
    "        \n",
    " # extracting each data row one by one and append it        \n",
    "        for line in csvreader:\n",
    "            #print(line)\n",
    "            full_data_rows_list.append(line) \n",
    "            \n",
    "\n",
    "print(f\"Total number of rows for all data collected : {len(full_data_rows_list)}\")\n",
    "print(f\"Head of dataset collect : {full_data_rows_list[:5]}\")\n",
    "\n",
    "# creating a smaller event data csv file called event_datafile_full csv that will be used to insert data into the \\\n",
    "# Apache Cassandra tables\n",
    "csv.register_dialect('myDialect', quoting=csv.QUOTE_ALL, skipinitialspace=True)\n",
    "\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',\\\n",
    "                '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",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6821\n"
     ]
    }
   ],
   "source": [
    "# check the number of rows in your csv file\n",
    "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",
    "## 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": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cassandra cluster created and connected\n"
     ]
    }
   ],
   "source": [
    "# This should make a connection to a Cassandra instance your local machine \n",
    "# (127.0.0.1)\n",
    "from cassandra.cluster import Cluster\n",
    "cluster = Cluster()\n",
    "\n",
    "from cassandra.cluster import Cluster\n",
    "try:\n",
    "    cluster = Cluster(['127.0.0.1'])\n",
    "    session = cluster.connect()\n",
    "    print(\"Cassandra cluster created and connected\")\n",
    "except Exception as e:\n",
    "    print(f\"Error creating cluster\")\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Create Keyspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Setting keyspace ..\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    print(\"Setting keyspace ..\")\n",
    "    session.execute(\"\"\"\n",
    "    CREATE KEYSPACE IF NOT EXISTS sparkify \n",
    "    WITH REPLICATION = \n",
    "    { 'class' : 'SimpleStrategy', 'replication_factor' : 1 }\"\"\"\n",
    ")\n",
    "\n",
    "except Exception as e:\n",
    "    print(\"Error setting keyspace ..\")\n",
    "    print(e)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Set Keyspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Keyspace set\n"
     ]
    }
   ],
   "source": [
    "#Set KEYSPACE to the keyspace specified above\n",
    "session.set_keyspace('sparkify')\n",
    "print(\"Keyspace set\")"
   ]
  },
  {
   "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": 10,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Succesfully created table for query #1\n"
     ]
    }
   ],
   "source": [
    "## Query 1:  Give me the artist, song title and song's length in the music app history that was heard during \\\n",
    "## sessionId = 338, and itemInSession = 4\n",
    "create_query1 = \"\"\"CREATE TABLE IF NOT EXISTS session_item (artist text, song text, length float, sessionId int, itemInSession int, PRIMARY KEY (sessionId, itemInSession))\"\"\"\n",
    "\n",
    "try: \n",
    "    session.execute(create_query1)\n",
    "    print(\"Succesfully created table for query #1\")\n",
    "except Exception as e:\n",
    "    print(\"Error while creating table\")\n",
    "    print(e)\n",
    "                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "file = 'event_datafile_new.csv'\n",
    "\n",
    "with open(file, encoding = 'utf8') as f:\n",
    "    csvreader = csv.reader(f)\n",
    "    next(csvreader) # skip header\n",
    "    for line in csvreader:\n",
    "## Assign the INSERT statements into the `query` variable\n",
    "        query = \"INSERT INTO session_item (artist, song, length, sessionId, itemInSession) \"\n",
    "        query = query + \" VALUES (%s, %s, %s, %s, %s) \"\n",
    "        session.execute(query, (line[0], line[10], float(line[5]), int(line[8]), int(line[3])) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### SELECT to verify that the data have been inserted into each table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Row(artist='Faithless', song='50', length=495.30731201171875)\n"
     ]
    }
   ],
   "source": [
    "## SELECT statement to verify the data was entered into the table\n",
    "test_select_query1 = \"SELECT artist, song, length FROM  session_item where sessionId = 338 and itemInSession = 4\"\n",
    "try:\n",
    "    rows = session.execute(test_select_query1)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "for row in rows:\n",
    "    print(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Succesfully created table for query #2\n"
     ]
    }
   ],
   "source": [
    "##Query 2: Give me only the following: name of artist, song (sorted by itemInSession) and user (first and last name)\\\n",
    "## for userid = 10, sessionid = 182\n",
    "create_query2 = \"\"\"CREATE TABLE IF NOT EXISTS user_session (sessionId int, userId int, artist text, song text, firstName text, lastName text, itemInSession int, PRIMARY KEY ((sessionId, userId), itemInSession)) WITH CLUSTERING ORDER BY (itemInSession ASC) \"\"\"\n",
    "\n",
    "try: \n",
    "    session.execute(create_query2)\n",
    "    print(\"Succesfully created table for query #2\")\n",
    "except Exception as e:\n",
    "    print(\"Error creating table\")\n",
    "    print(e)\n",
    "\n",
    "                  \n",
    "\n",
    "\n",
    "                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Inserting table in to table for query 2 \n",
    "file = 'event_datafile_new.csv'\n",
    "\n",
    "with open(file, encoding = 'utf8') as f:\n",
    "    csvreader = csv.reader(f)\n",
    "    next(csvreader) # skip header\n",
    "    for line in csvreader:\n",
    "        query = \"INSERT INTO user_session (sessionId, userId, artist, song, firstName, lastName, itemInSession) \"\n",
    "        query = query + \" VALUES (%s, %s, %s, %s, %s, %s, %s) \"\n",
    "        session.execute(query, (int(line[8]), int(line[10]), line[0], line[9], line[1], line[4], int(line[3])  ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Row(artist='Down To The Bone', song=\"Keep On Keepin' On\", firstname='Sylvie', lastname='Cruz')\n",
      "Row(artist='Three Drives', song='Greece 2000', firstname='Sylvie', lastname='Cruz')\n",
      "Row(artist='Sebastien Tellier', song='Kilometer', firstname='Sylvie', lastname='Cruz')\n",
      "Row(artist='Lonnie Gordon', song='Catch You Baby (Steve Pitron & Max Sanna Radio Edit)', firstname='Sylvie', lastname='Cruz')\n"
     ]
    }
   ],
   "source": [
    "#select statement to verify query2\n",
    "test_select_query2 = \"SELECT artist, song, firstName, lastName FROM  user_session where sessionId = 182 and userId = 10\"\n",
    "try:\n",
    "    rows = session.execute(test_select_query2)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "\n",
    "for row in rows:\n",
    "    print(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Succesfully created table for query #3\n"
     ]
    }
   ],
   "source": [
    "## Query 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",
    "create_query3 = \"\"\"CREATE TABLE IF NOT EXISTS user_song (song text, userId int, firstName text, lastName text, PRIMARY KEY ((song), userId))\"\"\"\n",
    "\n",
    "try: \n",
    "    session.execute(create_query3)\n",
    "    print(\"Succesfully created table for query #3\")\n",
    "except Exception as e:\n",
    "    print(\"Error creating table for query #3\")\n",
    "\n",
    "\n",
    "                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Inserting data into table for query 3\n",
    "file = 'event_datafile_new.csv'\n",
    "\n",
    "with open(file, encoding = 'utf8') as f:\n",
    "    csvreader = csv.reader(f)\n",
    "    next(csvreader) # skip header\n",
    "    for line in csvreader:\n",
    "        query = \"INSERT INTO user_song (song, userId, firstName, lastName) \"\n",
    "        query = query + \" VALUES (%s, %s, %s, %s) \"\n",
    "        session.execute(query, (  line[9], int(line[10]), line[1], line[4] )  )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Row(song='All Hands Against His Own', firstname='Jacqueline', lastname='Lynch')\n",
      "Row(song='All Hands Against His Own', firstname='Tegan', lastname='Levine')\n",
      "Row(song='All Hands Against His Own', firstname='Sara', lastname='Johnson')\n"
     ]
    }
   ],
   "source": [
    "# select statement to verify query3\n",
    "test_select_query3 = \"SELECT song, firstName, lastName FROM user_song where song = 'All Hands Against His Own'\"\n",
    "try:\n",
    "    rows = session.execute(test_select_query3)\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "\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": 20,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cassandra.cluster.ResultSet at 0x7f195b03bdd8>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "session.execute(\"DROP TABLE IF EXISTS sparkify.session_item\")\n",
    "session.execute(\"DROP TABLE IF EXISTS sparkify.user_session\")\n",
    "session.execute(\"DROP TABLE IF EXISTS sparkify.user_song\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "### Close the session and cluster connection¶"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "session.shutdown()\n",
    "cluster.shutdown()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": []
  }
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