{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "2021-06-24-spark-ml-basics.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "mZdQp0NlUV0X",
        "7TH96Tefgpgd",
        "QdSNFz8Jjx6K",
        "MvLSdZjj8Et2"
      ],
      "toc_visible": true,
      "authorship_tag": "ABX9TyPKuh4JLiwjzQUwNKckW8/F"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kEn3QO6f35ZP"
      },
      "source": [
        "# SparkML Basics\n",
        "> Basics of PySpark ML Lib module\n",
        "\n",
        "- toc: true\n",
        "- badges: true\n",
        "- comments: true\n",
        "- categories: [spark, pyspark]\n",
        "- image:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rg_FleseSdTF",
        "outputId": "35f0b560-a4af-4146-a8e0-b8e9ad203672"
      },
      "source": [
        "!git clone https://github.com/PacktPublishing/Mastering-Big-Data-Analytics-with-PySpark"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'Mastering-Big-Data-Analytics-with-PySpark'...\n",
            "remote: Enumerating objects: 145, done.\u001b[K\n",
            "remote: Counting objects: 100% (145/145), done.\u001b[K\n",
            "remote: Compressing objects: 100% (96/96), done.\u001b[K\n",
            "remote: Total 145 (delta 42), reused 136 (delta 38), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (145/145), 333.95 KiB | 9.03 MiB/s, done.\n",
            "Resolving deltas: 100% (42/42), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZPeES7P-S0Be",
        "outputId": "fad9f736-6c93-4046-c988-9b33d3dc65b3"
      },
      "source": [
        "%cd Mastering-Big-Data-Analytics-with-PySpark/"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/Mastering-Big-Data-Analytics-with-PySpark\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wb1bz2N4cnEK"
      },
      "source": [
        "!python download_data.py"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V0jui5N5Trjt"
      },
      "source": [
        "# !apt-get install openjdk-8-jdk-headless -qq > /dev/null\n",
        "# !wget https://downloads.apache.org/spark/spark-3.0.2/spark-3.0.2-bin-hadoop3.2.tgz\n",
        "# !tar -xvf spark-3.0.2-bin-hadoop3.2.tgz\n",
        "# !pip install -q findspark"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1az9qwMn14l5"
      },
      "source": [
        "import os\n",
        "os.environ[\"JAVA_HOME\"] = \"/usr/lib/jvm/java-8-openjdk-amd64\"\n",
        "os.environ[\"SPARK_HOME\"] = \"/content/Mastering-Big-Data-Analytics-with-PySpark/spark-3.0.2-bin-hadoop3.2\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mZdQp0NlUV0X"
      },
      "source": [
        "### Hello world Spark!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CKBsHoTRTEDg"
      },
      "source": [
        "from pyspark.sql import SparkSession"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zZH5ExEDTdm9"
      },
      "source": [
        "spark = SparkSession.builder.appName(\"HelloWorldApp\").getOrCreate()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M1y6cG1xUFBU",
        "outputId": "ab705dfa-702b-4877-8549-95de10a583f7"
      },
      "source": [
        "# Using Spark SQL, we create a dataframe which holds our `hello world` data\n",
        "df = spark.sql('SELECT \"hello world\" as c1')\n",
        "\n",
        "# We can then use the `show()` method to see what the DataFrame we just created looks like\n",
        "df.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-----------+\n",
            "|         c1|\n",
            "+-----------+\n",
            "|hello world|\n",
            "+-----------+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ORCesjawUPKc"
      },
      "source": [
        "spark.stop()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7TH96Tefgpgd"
      },
      "source": [
        "### Preparing data using SparkSQL\n",
        "- How to use read.csv() to load CSV files, and how to control the settings of this method\n",
        "- By default, CSVs are parsed with all columns being cast to StringType\n",
        "- inferSchema allows Spark to guess what schema should be used\n",
        "- To ensure proper Type Safety, we can use Hive Schema DDL to set an explicit schema"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tMkqQ8LWczaO"
      },
      "source": [
        "from pyspark.sql import SparkSession\n",
        "spark = SparkSession.builder.appName(\"31LoadingDataFromCSV\").getOrCreate()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8IrygRwtgxFE"
      },
      "source": [
        "RATINGS_CSV_LOCATION = \"/content/Mastering-Big-Data-Analytics-with-PySpark/data-sets/ml-latest-small/ratings.csv\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-fKZMsXag7M_",
        "outputId": "cc0502e7-7b74-4b10-a68a-dcdaa63c2967"
      },
      "source": [
        "df = spark.read.csv(RATINGS_CSV_LOCATION)\n",
        "\n",
        "df.show()\n",
        "df.printSchema()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------+-------+------+---------+\n",
            "|   _c0|    _c1|   _c2|      _c3|\n",
            "+------+-------+------+---------+\n",
            "|userId|movieId|rating|timestamp|\n",
            "|     1|      1|   4.0|964982703|\n",
            "|     1|      3|   4.0|964981247|\n",
            "|     1|      6|   4.0|964982224|\n",
            "|     1|     47|   5.0|964983815|\n",
            "|     1|     50|   5.0|964982931|\n",
            "|     1|     70|   3.0|964982400|\n",
            "|     1|    101|   5.0|964980868|\n",
            "|     1|    110|   4.0|964982176|\n",
            "|     1|    151|   5.0|964984041|\n",
            "|     1|    157|   5.0|964984100|\n",
            "|     1|    163|   5.0|964983650|\n",
            "|     1|    216|   5.0|964981208|\n",
            "|     1|    223|   3.0|964980985|\n",
            "|     1|    231|   5.0|964981179|\n",
            "|     1|    235|   4.0|964980908|\n",
            "|     1|    260|   5.0|964981680|\n",
            "|     1|    296|   3.0|964982967|\n",
            "|     1|    316|   3.0|964982310|\n",
            "|     1|    333|   5.0|964981179|\n",
            "+------+-------+------+---------+\n",
            "only showing top 20 rows\n",
            "\n",
            "root\n",
            " |-- _c0: string (nullable = true)\n",
            " |-- _c1: string (nullable = true)\n",
            " |-- _c2: string (nullable = true)\n",
            " |-- _c3: string (nullable = true)\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CkEMHQ6shSZC"
      },
      "source": [
        "What you can see, is that the data is being loaded, but it does not quite appear to be right. Additionally, all the columns appear to be cast as a StringType - which is not ideal. We can fix the aformentioned issues by giving the read.csv() method the correct settings.\n",
        "\n",
        "To parse the CSV correctly, we are going to need to set the following on our read.csv() method:\n",
        "1. We leave the same path as before, referring to RATINGS_CSV_LOCATION that we set previously.\n",
        "2. Since we have comma-seperated-values, we need to set sep to ','.\n",
        "3. Since we have a single header row, we need to set header to True.\n",
        "4. Since columns that contain commas (,) are escaped using double-quotes (\"), we set quote to '\"'.\n",
        "5. Since the files are encoded as UTF-8, we set encoding to UTF-8.\n",
        "6. Additionally, since we observed that all values are cast to StringType by default, we set inferSchema to True.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4_MfppJchSno",
        "outputId": "4e9f7179-fce9-4591-e870-e93ca625f4ea"
      },
      "source": [
        "# Loading CSV file with proper parsing and inferSchema\n",
        "df = spark.read.csv(\n",
        "    path=RATINGS_CSV_LOCATION,\n",
        "    sep=\",\",\n",
        "    header=True,\n",
        "    quote='\"',\n",
        "    encoding=\"UTF-8\",\n",
        "    inferSchema=True,\n",
        ")\n",
        "\n",
        "# Displaying results of the load\n",
        "df.show()\n",
        "df.printSchema()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------+-------+------+---------+\n",
            "|userId|movieId|rating|timestamp|\n",
            "+------+-------+------+---------+\n",
            "|     1|      1|   4.0|964982703|\n",
            "|     1|      3|   4.0|964981247|\n",
            "|     1|      6|   4.0|964982224|\n",
            "|     1|     47|   5.0|964983815|\n",
            "|     1|     50|   5.0|964982931|\n",
            "|     1|     70|   3.0|964982400|\n",
            "|     1|    101|   5.0|964980868|\n",
            "|     1|    110|   4.0|964982176|\n",
            "|     1|    151|   5.0|964984041|\n",
            "|     1|    157|   5.0|964984100|\n",
            "|     1|    163|   5.0|964983650|\n",
            "|     1|    216|   5.0|964981208|\n",
            "|     1|    223|   3.0|964980985|\n",
            "|     1|    231|   5.0|964981179|\n",
            "|     1|    235|   4.0|964980908|\n",
            "|     1|    260|   5.0|964981680|\n",
            "|     1|    296|   3.0|964982967|\n",
            "|     1|    316|   3.0|964982310|\n",
            "|     1|    333|   5.0|964981179|\n",
            "|     1|    349|   4.0|964982563|\n",
            "+------+-------+------+---------+\n",
            "only showing top 20 rows\n",
            "\n",
            "root\n",
            " |-- userId: integer (nullable = true)\n",
            " |-- movieId: integer (nullable = true)\n",
            " |-- rating: double (nullable = true)\n",
            " |-- timestamp: integer (nullable = true)\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WtBGKr8dhw-B",
        "outputId": "b4099782-5fa4-4c5b-d7ba-ee655d9dd848"
      },
      "source": [
        "#  Type safe loading of ratings.csv file\n",
        "df = spark.read.csv(\n",
        "    path=RATINGS_CSV_LOCATION,\n",
        "    sep=\",\",\n",
        "    header=True,\n",
        "    quote='\"',\n",
        "    encoding=\"UTF-8\",\n",
        "    schema=\"userId INT, movieId INT, rating DOUBLE, timestamp INT\",\n",
        ")\n",
        "\n",
        "# Displaying results of the load\n",
        "df.show()\n",
        "df.printSchema()\n",
        "df.describe().show()\n",
        "df.explain()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------+-------+------+---------+\n",
            "|userId|movieId|rating|timestamp|\n",
            "+------+-------+------+---------+\n",
            "|     1|      1|   4.0|964982703|\n",
            "|     1|      3|   4.0|964981247|\n",
            "|     1|      6|   4.0|964982224|\n",
            "|     1|     47|   5.0|964983815|\n",
            "|     1|     50|   5.0|964982931|\n",
            "|     1|     70|   3.0|964982400|\n",
            "|     1|    101|   5.0|964980868|\n",
            "|     1|    110|   4.0|964982176|\n",
            "|     1|    151|   5.0|964984041|\n",
            "|     1|    157|   5.0|964984100|\n",
            "|     1|    163|   5.0|964983650|\n",
            "|     1|    216|   5.0|964981208|\n",
            "|     1|    223|   3.0|964980985|\n",
            "|     1|    231|   5.0|964981179|\n",
            "|     1|    235|   4.0|964980908|\n",
            "|     1|    260|   5.0|964981680|\n",
            "|     1|    296|   3.0|964982967|\n",
            "|     1|    316|   3.0|964982310|\n",
            "|     1|    333|   5.0|964981179|\n",
            "|     1|    349|   4.0|964982563|\n",
            "+------+-------+------+---------+\n",
            "only showing top 20 rows\n",
            "\n",
            "root\n",
            " |-- userId: integer (nullable = true)\n",
            " |-- movieId: integer (nullable = true)\n",
            " |-- rating: double (nullable = true)\n",
            " |-- timestamp: integer (nullable = true)\n",
            "\n",
            "+-------+------------------+----------------+------------------+--------------------+\n",
            "|summary|            userId|         movieId|            rating|           timestamp|\n",
            "+-------+------------------+----------------+------------------+--------------------+\n",
            "|  count|            100836|          100836|            100836|              100836|\n",
            "|   mean|326.12756356856676|19435.2957177992| 3.501556983616962|1.2059460873684695E9|\n",
            "| stddev| 182.6184914635004|35530.9871987003|1.0425292390606342|2.1626103599513078E8|\n",
            "|    min|                 1|               1|               0.5|           828124615|\n",
            "|    max|               610|          193609|               5.0|          1537799250|\n",
            "+-------+------------------+----------------+------------------+--------------------+\n",
            "\n",
            "== Physical Plan ==\n",
            "FileScan csv [userId#97,movieId#98,rating#99,timestamp#100] Batched: false, DataFilters: [], Format: CSV, Location: InMemoryFileIndex[file:/content/Mastering-Big-Data-Analytics-with-PySpark/data-sets/ml-latest-sma..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<userId:int,movieId:int,rating:double,timestamp:int>\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fI4UWcJyjav4",
        "outputId": "bc5a287b-6937-4322-cbd6-9e7c08af376b"
      },
      "source": [
        "from pyspark.sql import functions as f\n",
        "\n",
        "ratings = (\n",
        "    spark.read.csv(\n",
        "        path=RATINGS_CSV_LOCATION,\n",
        "        sep=\",\",\n",
        "        header=True,\n",
        "        quote='\"',\n",
        "        schema=\"userId INT, movieId INT, rating DOUBLE, timestamp INT\",\n",
        "    )\n",
        "    .withColumnRenamed(\"timestamp\", \"timestamp_unix\")\n",
        "    .withColumn(\"timestamp\", f.to_timestamp(f.from_unixtime(\"timestamp_unix\")))\n",
        ")\n",
        "\n",
        "ratings.show(5)\n",
        "ratings.printSchema()\n",
        "ratings.drop(\"timestamp_unix\", \"foobar\").show(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------+-------+------+--------------+-------------------+\n",
            "|userId|movieId|rating|timestamp_unix|          timestamp|\n",
            "+------+-------+------+--------------+-------------------+\n",
            "|     1|      1|   4.0|     964982703|2000-07-30 18:45:03|\n",
            "|     1|      3|   4.0|     964981247|2000-07-30 18:20:47|\n",
            "|     1|      6|   4.0|     964982224|2000-07-30 18:37:04|\n",
            "|     1|     47|   5.0|     964983815|2000-07-30 19:03:35|\n",
            "|     1|     50|   5.0|     964982931|2000-07-30 18:48:51|\n",
            "+------+-------+------+--------------+-------------------+\n",
            "only showing top 5 rows\n",
            "\n",
            "root\n",
            " |-- userId: integer (nullable = true)\n",
            " |-- movieId: integer (nullable = true)\n",
            " |-- rating: double (nullable = true)\n",
            " |-- timestamp_unix: integer (nullable = true)\n",
            " |-- timestamp: timestamp (nullable = true)\n",
            "\n",
            "+------+-------+------+-------------------+\n",
            "|userId|movieId|rating|          timestamp|\n",
            "+------+-------+------+-------------------+\n",
            "|     1|      1|   4.0|2000-07-30 18:45:03|\n",
            "|     1|      3|   4.0|2000-07-30 18:20:47|\n",
            "|     1|      6|   4.0|2000-07-30 18:37:04|\n",
            "|     1|     47|   5.0|2000-07-30 19:03:35|\n",
            "|     1|     50|   5.0|2000-07-30 18:48:51|\n",
            "+------+-------+------+-------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DMC8M6CLkoio",
        "outputId": "755e82d2-9fd5-4a91-d6d4-2b1df396cc47"
      },
      "source": [
        "MOVIES_CSV_LOCATION = \"/content/Mastering-Big-Data-Analytics-with-PySpark/data-sets/ml-latest-small/movies.csv\"\n",
        "\n",
        "movies = (\n",
        "    spark.read.csv(\n",
        "        path=MOVIES_CSV_LOCATION,\n",
        "        sep=\",\",\n",
        "        header=True,\n",
        "        quote='\"',\n",
        "        schema=\"movieId INT, title STRING, genres STRING\",\n",
        "    )\n",
        ")\n",
        "movies.show(15, truncate=False)\n",
        "movies.printSchema()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-------+----------------------------------+-------------------------------------------+\n",
            "|movieId|title                             |genres                                     |\n",
            "+-------+----------------------------------+-------------------------------------------+\n",
            "|1      |Toy Story (1995)                  |Adventure|Animation|Children|Comedy|Fantasy|\n",
            "|2      |Jumanji (1995)                    |Adventure|Children|Fantasy                 |\n",
            "|3      |Grumpier Old Men (1995)           |Comedy|Romance                             |\n",
            "|4      |Waiting to Exhale (1995)          |Comedy|Drama|Romance                       |\n",
            "|5      |Father of the Bride Part II (1995)|Comedy                                     |\n",
            "|6      |Heat (1995)                       |Action|Crime|Thriller                      |\n",
            "|7      |Sabrina (1995)                    |Comedy|Romance                             |\n",
            "|8      |Tom and Huck (1995)               |Adventure|Children                         |\n",
            "|9      |Sudden Death (1995)               |Action                                     |\n",
            "|10     |GoldenEye (1995)                  |Action|Adventure|Thriller                  |\n",
            "|11     |American President, The (1995)    |Comedy|Drama|Romance                       |\n",
            "|12     |Dracula: Dead and Loving It (1995)|Comedy|Horror                              |\n",
            "|13     |Balto (1995)                      |Adventure|Animation|Children               |\n",
            "|14     |Nixon (1995)                      |Drama                                      |\n",
            "|15     |Cutthroat Island (1995)           |Action|Adventure|Romance                   |\n",
            "+-------+----------------------------------+-------------------------------------------+\n",
            "only showing top 15 rows\n",
            "\n",
            "root\n",
            " |-- movieId: integer (nullable = true)\n",
            " |-- title: string (nullable = true)\n",
            " |-- genres: string (nullable = true)\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lHzUF7b8k7JA",
        "outputId": "c57a7c8e-534a-4632-d696-487e61e66167"
      },
      "source": [
        "movies.where(f.col(\"genres\") == \"Action\").show(5, False)\n",
        "movies.where(\"genres == 'Action'\").show(5, False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-------+-----------------------------------------------------------+------+\n",
            "|movieId|title                                                      |genres|\n",
            "+-------+-----------------------------------------------------------+------+\n",
            "|9      |Sudden Death (1995)                                        |Action|\n",
            "|71     |Fair Game (1995)                                           |Action|\n",
            "|204    |Under Siege 2: Dark Territory (1995)                       |Action|\n",
            "|251    |Hunted, The (1995)                                         |Action|\n",
            "|667    |Bloodsport 2 (a.k.a. Bloodsport II: The Next Kumite) (1996)|Action|\n",
            "+-------+-----------------------------------------------------------+------+\n",
            "only showing top 5 rows\n",
            "\n",
            "+-------+-----------------------------------------------------------+------+\n",
            "|movieId|title                                                      |genres|\n",
            "+-------+-----------------------------------------------------------+------+\n",
            "|9      |Sudden Death (1995)                                        |Action|\n",
            "|71     |Fair Game (1995)                                           |Action|\n",
            "|204    |Under Siege 2: Dark Territory (1995)                       |Action|\n",
            "|251    |Hunted, The (1995)                                         |Action|\n",
            "|667    |Bloodsport 2 (a.k.a. Bloodsport II: The Next Kumite) (1996)|Action|\n",
            "+-------+-----------------------------------------------------------+------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bdr37suXlZYv",
        "outputId": "d1581c34-f251-4ab5-84d9-8568af06f4fd"
      },
      "source": [
        "movie_genre = (\n",
        "    movies\n",
        "    .withColumn(\"genres_array\", f.split(\"genres\", \"\\|\"))\n",
        "    .withColumn(\"genre\", f.explode(\"genres_array\"))\n",
        "    .select(\"movieId\", \"title\", \"genre\")\n",
        ")\n",
        "\n",
        "movie_genre.show(10, False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-------+-----------------------+---------+\n",
            "|movieId|title                  |genre    |\n",
            "+-------+-----------------------+---------+\n",
            "|1      |Toy Story (1995)       |Adventure|\n",
            "|1      |Toy Story (1995)       |Animation|\n",
            "|1      |Toy Story (1995)       |Children |\n",
            "|1      |Toy Story (1995)       |Comedy   |\n",
            "|1      |Toy Story (1995)       |Fantasy  |\n",
            "|2      |Jumanji (1995)         |Adventure|\n",
            "|2      |Jumanji (1995)         |Children |\n",
            "|2      |Jumanji (1995)         |Fantasy  |\n",
            "|3      |Grumpier Old Men (1995)|Comedy   |\n",
            "|3      |Grumpier Old Men (1995)|Romance  |\n",
            "+-------+-----------------------+---------+\n",
            "only showing top 10 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SB0Ez1Nklg0G",
        "outputId": "719e3268-3a54-448d-f12f-20782924eaaf"
      },
      "source": [
        "available_genres = movie_genre.select(\"genre\").distinct()\n",
        "available_genres.show()\n",
        "\n",
        "movies_without_genre = movies.where(f.col(\"genres\") == \"(no genres listed)\")\n",
        "print(movies_without_genre.count())\n",
        "movies_without_genre.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------------------+\n",
            "|             genre|\n",
            "+------------------+\n",
            "|             Crime|\n",
            "|           Romance|\n",
            "|          Thriller|\n",
            "|         Adventure|\n",
            "|             Drama|\n",
            "|               War|\n",
            "|       Documentary|\n",
            "|           Fantasy|\n",
            "|           Mystery|\n",
            "|           Musical|\n",
            "|         Animation|\n",
            "|         Film-Noir|\n",
            "|(no genres listed)|\n",
            "|              IMAX|\n",
            "|            Horror|\n",
            "|           Western|\n",
            "|            Comedy|\n",
            "|          Children|\n",
            "|            Action|\n",
            "|            Sci-Fi|\n",
            "+------------------+\n",
            "\n",
            "34\n",
            "+-------+--------------------+------------------+\n",
            "|movieId|               title|            genres|\n",
            "+-------+--------------------+------------------+\n",
            "| 114335|   La cravate (1957)|(no genres listed)|\n",
            "| 122888|      Ben-hur (2016)|(no genres listed)|\n",
            "| 122896|Pirates of the Ca...|(no genres listed)|\n",
            "| 129250|   Superfast! (2015)|(no genres listed)|\n",
            "| 132084| Let It Be Me (1995)|(no genres listed)|\n",
            "| 134861|Trevor Noah: Afri...|(no genres listed)|\n",
            "| 141131|    Guardians (2016)|(no genres listed)|\n",
            "| 141866|   Green Room (2015)|(no genres listed)|\n",
            "| 142456|The Brand New Tes...|(no genres listed)|\n",
            "| 143410|          Hyena Road|(no genres listed)|\n",
            "| 147250|The Adventures of...|(no genres listed)|\n",
            "| 149330|A Cosmic Christma...|(no genres listed)|\n",
            "| 152037|  Grease Live (2016)|(no genres listed)|\n",
            "| 155589|Noin 7 veljestä (...|(no genres listed)|\n",
            "| 156605|            Paterson|(no genres listed)|\n",
            "| 159161|Ali Wong: Baby Co...|(no genres listed)|\n",
            "| 159779|A Midsummer Night...|(no genres listed)|\n",
            "| 161008|The Forbidden Dan...|(no genres listed)|\n",
            "| 165489|Ethel & Ernest (2...|(no genres listed)|\n",
            "| 166024|     Whiplash (2013)|(no genres listed)|\n",
            "+-------+--------------------+------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QdSNFz8Jjx6K"
      },
      "source": [
        "### Grouping, Joining and Aggregating"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "62iqvcMsjgBS"
      },
      "source": [
        "from pyspark.sql import SparkSession\n",
        "from pyspark.sql.types import StringType, IntegerType, StructType, StructField"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XqlO_uC8xevw",
        "outputId": "700638d9-50df-4b74-d655-0dd91600a690"
      },
      "source": [
        "spark = SparkSession.builder.appName(\"join_tests\").getOrCreate()\n",
        "schema = StructType(\n",
        "    [StructField(\"id\", IntegerType()), StructField(\"value\", StringType())]\n",
        ")\n",
        "\n",
        "\n",
        "A = spark.createDataFrame(\n",
        "    schema=schema, data=[\n",
        "        (1, \"A\"),\n",
        "        (2, \"B\"),\n",
        "        (3, \"C\"),\n",
        "        (4, \"D\"),\n",
        "        (5, \"E\"),\n",
        "        (None, \"Z\")\n",
        "    ]\n",
        ")\n",
        "\n",
        "B = spark.createDataFrame(\n",
        "    schema=schema, data=[\n",
        "        (3, \"C\"),\n",
        "        (4, \"D\"),\n",
        "        (5, \"E\"),\n",
        "        (6, \"F\"),\n",
        "        (7, \"G\")\n",
        "    ]\n",
        ")\n",
        "\n",
        "A.show()\n",
        "B.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+----+-----+\n",
            "|  id|value|\n",
            "+----+-----+\n",
            "|   1|    A|\n",
            "|   2|    B|\n",
            "|   3|    C|\n",
            "|   4|    D|\n",
            "|   5|    E|\n",
            "|null|    Z|\n",
            "+----+-----+\n",
            "\n",
            "+---+-----+\n",
            "| id|value|\n",
            "+---+-----+\n",
            "|  3|    C|\n",
            "|  4|    D|\n",
            "|  5|    E|\n",
            "|  6|    F|\n",
            "|  7|    G|\n",
            "+---+-----+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0EFstaZ1xhES"
      },
      "source": [
        "# INNER JOINS\n",
        "# A.join(B, [\"id\"], \"inner\").show()\n",
        "\n",
        "# CROSS JOINS (CARTESIAN PRODUCT)\n",
        "# A.crossJoin(B).show()\n",
        "\n",
        "# FULL JOINS\n",
        "# A.join(B, [\"id\"], \"outer\").show()\n",
        "# A.join(B, [\"id\"], \"full\").show()\n",
        "# A.join(B, [\"id\"], \"full_outer\").show()\n",
        "\n",
        "# LEFT OUTER\n",
        "# A.join(B, [\"id\"], \"left\").show()\n",
        "# A.join(B, [\"id\"], \"left_outer\").show()\n",
        "\n",
        "# RIGHT OUTER\n",
        "# A.join(B, [\"id\"], \"right\").show()\n",
        "# A.join(B, [\"id\"], \"right_outer\").show()\n",
        "\n",
        "# LEFT SPECIAL\n",
        "# A.join(B, [\"id\"], \"left_semi\").show()\n",
        "# A.join(B, [\"id\"], \"left_anti\").show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SntUyi9PzMZK",
        "outputId": "a0e22f6e-85df-44a5-86b5-ed12c61e098d"
      },
      "source": [
        "links = spark.read.csv(\n",
        "    path=\"/content/Mastering-Big-Data-Analytics-with-PySpark/data-sets/ml-latest-small/links.csv\",\n",
        "    sep=\",\",\n",
        "    header=True,\n",
        "    quote='\"',\n",
        "    schema=\"movieId INT, imdbId STRING, tmdbId INT\",\n",
        ")\n",
        "\n",
        "tags = spark.read.csv(\n",
        "    path=\"/content/Mastering-Big-Data-Analytics-with-PySpark/data-sets/ml-latest-small/tags.csv\",\n",
        "    sep=\",\",\n",
        "    header=True,\n",
        "    quote='\"',\n",
        "    inferSchema=True,\n",
        "    schema=\"userId INT, movieId INT, tag STRING, timestamp INT\",\n",
        ").withColumn(\"timestamp\", f.to_timestamp(f.from_unixtime(\"timestamp\")))\n",
        "\n",
        "links.show(5)\n",
        "tags.show(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-------+-------+------+\n",
            "|movieId| imdbId|tmdbId|\n",
            "+-------+-------+------+\n",
            "|      1|0114709|   862|\n",
            "|      2|0113497|  8844|\n",
            "|      3|0113228| 15602|\n",
            "|      4|0114885| 31357|\n",
            "|      5|0113041| 11862|\n",
            "+-------+-------+------+\n",
            "only showing top 5 rows\n",
            "\n",
            "+------+-------+---------------+-------------------+\n",
            "|userId|movieId|            tag|          timestamp|\n",
            "+------+-------+---------------+-------------------+\n",
            "|     2|  60756|          funny|2015-10-24 19:29:54|\n",
            "|     2|  60756|Highly quotable|2015-10-24 19:29:56|\n",
            "|     2|  60756|   will ferrell|2015-10-24 19:29:52|\n",
            "|     2|  89774|   Boxing story|2015-10-24 19:33:27|\n",
            "|     2|  89774|            MMA|2015-10-24 19:33:20|\n",
            "+------+-------+---------------+-------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wHCJtSnszxoa",
        "outputId": "7ea134ee-0a54-4cb0-d572-92edf56babd5"
      },
      "source": [
        "movie_per_genre = movie_genre.groupBy(\"genre\").count()\n",
        "movie_per_genre.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------------------+-----+\n",
            "|             genre|count|\n",
            "+------------------+-----+\n",
            "|             Crime| 1199|\n",
            "|           Romance| 1596|\n",
            "|          Thriller| 1894|\n",
            "|         Adventure| 1263|\n",
            "|             Drama| 4361|\n",
            "|               War|  382|\n",
            "|       Documentary|  440|\n",
            "|           Fantasy|  779|\n",
            "|           Mystery|  573|\n",
            "|           Musical|  334|\n",
            "|         Animation|  611|\n",
            "|         Film-Noir|   87|\n",
            "|(no genres listed)|   34|\n",
            "|              IMAX|  158|\n",
            "|            Horror|  978|\n",
            "|           Western|  167|\n",
            "|            Comedy| 3756|\n",
            "|          Children|  664|\n",
            "|            Action| 1828|\n",
            "|            Sci-Fi|  980|\n",
            "+------------------+-----+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yuiiUX-V1JqR",
        "outputId": "051bca2e-b254-4cbf-cc61-33f3fd0bec8c"
      },
      "source": [
        "# opinions = movies.join(tags, movies['movieId'] == tags['movieId'])\n",
        "# opinions = movies.join(tags, [\"movieId\"])\n",
        "opinions = movies.join(tags, [\"movieId\"], \"inner\")\n",
        "opinions.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-------+--------------------+--------------------+------+----------------+-------------------+\n",
            "|movieId|               title|              genres|userId|             tag|          timestamp|\n",
            "+-------+--------------------+--------------------+------+----------------+-------------------+\n",
            "|      1|    Toy Story (1995)|Adventure|Animati...|   567|             fun|2018-05-02 18:33:33|\n",
            "|      1|    Toy Story (1995)|Adventure|Animati...|   474|           pixar|2006-01-14 02:47:05|\n",
            "|      1|    Toy Story (1995)|Adventure|Animati...|   336|           pixar|2006-02-04 09:36:04|\n",
            "|      2|      Jumanji (1995)|Adventure|Childre...|   474|            game|2006-01-16 01:39:12|\n",
            "|      2|      Jumanji (1995)|Adventure|Childre...|    62|  Robin Williams|2018-06-12 22:51:47|\n",
            "|      2|      Jumanji (1995)|Adventure|Childre...|    62|magic board game|2018-06-12 22:52:12|\n",
            "|      2|      Jumanji (1995)|Adventure|Childre...|    62|         fantasy|2018-06-12 22:52:09|\n",
            "|      3|Grumpier Old Men ...|      Comedy|Romance|   289|             old|2006-03-27 02:01:00|\n",
            "|      3|Grumpier Old Men ...|      Comedy|Romance|   289|           moldy|2006-03-27 02:01:00|\n",
            "|      4|Waiting to Exhale...|Comedy|Drama|Romance|  null|            null|               null|\n",
            "|      5|Father of the Bri...|              Comedy|   474|          remake|2006-01-16 01:11:43|\n",
            "|      5|Father of the Bri...|              Comedy|   474|       pregnancy|2006-01-16 01:11:43|\n",
            "|      6|         Heat (1995)|Action|Crime|Thri...|  null|            null|               null|\n",
            "|      7|      Sabrina (1995)|      Comedy|Romance|   474|          remake|2006-01-16 01:40:42|\n",
            "|      8| Tom and Huck (1995)|  Adventure|Children|  null|            null|               null|\n",
            "|      9| Sudden Death (1995)|              Action|  null|            null|               null|\n",
            "|     10|    GoldenEye (1995)|Action|Adventure|...|  null|            null|               null|\n",
            "|     11|American Presiden...|Comedy|Drama|Romance|   474|       president|2006-01-16 01:28:24|\n",
            "|     11|American Presiden...|Comedy|Drama|Romance|   474|        politics|2006-01-16 01:28:24|\n",
            "|     12|Dracula: Dead and...|       Comedy|Horror|  null|            null|               null|\n",
            "+-------+--------------------+--------------------+------+----------------+-------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xHP2RES415rE",
        "outputId": "999d4c16-b163-4f61-8a7c-24834353a6c1"
      },
      "source": [
        "opinions = (\n",
        "    movies\n",
        "    .join(tags, [\"movieId\"], \"inner\")\n",
        "    .select(\"userId\", \"movieId\", \"title\", \"tag\", \"timestamp\")\n",
        ")\n",
        "opinions.show(5, False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------+-------+----------------+--------------+-------------------+\n",
            "|userId|movieId|title           |tag           |timestamp          |\n",
            "+------+-------+----------------+--------------+-------------------+\n",
            "|567   |1      |Toy Story (1995)|fun           |2018-05-02 18:33:33|\n",
            "|474   |1      |Toy Story (1995)|pixar         |2006-01-14 02:47:05|\n",
            "|336   |1      |Toy Story (1995)|pixar         |2006-02-04 09:36:04|\n",
            "|474   |2      |Jumanji (1995)  |game          |2006-01-16 01:39:12|\n",
            "|62    |2      |Jumanji (1995)  |Robin Williams|2018-06-12 22:51:47|\n",
            "+------+-------+----------------+--------------+-------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GMCGePR_2xM-",
        "outputId": "63dc58f6-de60-4156-9854-c8572a68ff67"
      },
      "source": [
        "opinions_ext = opinions.withColumnRenamed(\"timestamp\", \"tag_time\").join(ratings, [\"movieId\", \"userId\"])\n",
        "opinions_ext.show(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-------+------+----------------+--------------+-------------------+------+--------------+-------------------+\n",
            "|movieId|userId|           title|           tag|           tag_time|rating|timestamp_unix|          timestamp|\n",
            "+-------+------+----------------+--------------+-------------------+------+--------------+-------------------+\n",
            "|      1|   567|Toy Story (1995)|           fun|2018-05-02 18:33:33|   3.5|    1525286001|2018-05-02 18:33:21|\n",
            "|      1|   474|Toy Story (1995)|         pixar|2006-01-14 02:47:05|   4.0|     978575760|2001-01-04 02:36:00|\n",
            "|      1|   336|Toy Story (1995)|         pixar|2006-02-04 09:36:04|   4.0|    1122227329|2005-07-24 17:48:49|\n",
            "|      2|   474|  Jumanji (1995)|          game|2006-01-16 01:39:12|   3.0|    1046886814|2003-03-05 17:53:34|\n",
            "|      2|    62|  Jumanji (1995)|Robin Williams|2018-06-12 22:51:47|   4.0|    1528843890|2018-06-12 22:51:30|\n",
            "+-------+------+----------------+--------------+-------------------+------+--------------+-------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RWwUadXn3qhK",
        "outputId": "40cc381f-dce0-4b3a-ea81-52e81762c10a"
      },
      "source": [
        "ratings.groupBy(\"movieId\").agg(\n",
        "    f.count(\"*\"),\n",
        "    f.min(\"rating\"),\n",
        "    f.min(\"rating\"),\n",
        "    f.avg(\"rating\"),\n",
        "    f.min(\"timestamp\"),\n",
        "    f.max(\"timestamp\"),\n",
        ").show(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-------+--------+-----------+-----------+-----------------+-------------------+-------------------+\n",
            "|movieId|count(1)|min(rating)|min(rating)|      avg(rating)|     min(timestamp)|     max(timestamp)|\n",
            "+-------+--------+-----------+-----------+-----------------+-------------------+-------------------+\n",
            "|   1580|     165|        0.5|        0.5|3.487878787878788|1997-07-07 12:07:18|2018-07-22 13:30:52|\n",
            "|   2366|      25|        1.5|        1.5|             3.64|1999-11-04 15:23:49|2018-02-20 10:20:35|\n",
            "|   3175|      75|        1.0|        1.0|             3.58|1999-12-26 14:01:31|2018-06-25 05:07:19|\n",
            "|   1088|      42|        1.0|        1.0|3.369047619047619|1997-04-07 07:36:08|2018-01-17 01:52:47|\n",
            "|  32460|       4|        3.5|        3.5|             4.25|2011-12-18 19:21:21|2017-04-21 20:12:30|\n",
            "+-------+--------+-----------+-----------+-----------------+-------------------+-------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0M3rXQVR5eKr"
      },
      "source": [
        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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MvLSdZjj8Et2"
      },
      "source": [
        "### ALS Recommender System"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5gF2zclO3qeE"
      },
      "source": [
        "from pyspark.sql import SparkSession\n",
        "from pyspark.sql import functions as f\n",
        "\n",
        "spark = SparkSession.builder.appName(\"als-recommender\").getOrCreate()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ThehCadk3qaY"
      },
      "source": [
        "ratings = (\n",
        "    spark.read.csv(\n",
        "        path=\"/content/Mastering-Big-Data-Analytics-with-PySpark/data-sets/ml-latest-small/ratings.csv\",\n",
        "        sep=\",\",\n",
        "        header=True,\n",
        "        quote='\"',\n",
        "        schema=\"userId INT, movieId INT, rating DOUBLE, timestamp INT\",\n",
        "    )\n",
        "    # .withColumn(\"timestamp\", f.to_timestamp(f.from_unixtime(\"timestamp\")))\n",
        "    .drop(\"timestamp\")\n",
        "    .cache()\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iQ7YY90f8bn4"
      },
      "source": [
        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)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-9S-wo4t3qV_"
      },
      "source": [
        "from pyspark.ml.recommendation import ALS"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mBycntJP8dqB"
      },
      "source": [
        "model = (\n",
        "    ALS(\n",
        "        userCol=\"userId\",\n",
        "        itemCol=\"movieId\",\n",
        "        ratingCol=\"rating\",\n",
        "    ).fit(ratings)\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DP_VSR9S8fLR",
        "outputId": "139a8cdd-2612-4908-bcc0-499ca6d2d239"
      },
      "source": [
        "predictions = model.transform(ratings)\n",
        "predictions.show(10, False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------+-------+------+----------+\n",
            "|userId|movieId|rating|prediction|\n",
            "+------+-------+------+----------+\n",
            "|191   |148    |5.0   |4.921467  |\n",
            "|133   |471    |4.0   |3.1737905 |\n",
            "|597   |471    |2.0   |3.9179363 |\n",
            "|385   |471    |4.0   |2.9745612 |\n",
            "|436   |471    |3.0   |3.6886308 |\n",
            "|602   |471    |4.0   |3.6024406 |\n",
            "|91    |471    |1.0   |2.3480353 |\n",
            "|409   |471    |3.0   |3.8320298 |\n",
            "|372   |471    |3.0   |2.9738774 |\n",
            "|599   |471    |2.5   |2.7476397 |\n",
            "+------+-------+------+----------+\n",
            "only showing top 10 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZFXCGziI8g4O",
        "outputId": "439a3b8a-c009-4f31-e607-5564179a0667"
      },
      "source": [
        "model.userFactors.show(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+---+--------------------+\n",
            "| id|            features|\n",
            "+---+--------------------+\n",
            "| 10|[-0.028317755, 0....|\n",
            "| 20|[-1.2629544, 0.57...|\n",
            "| 30|[-0.64685774, -0....|\n",
            "| 40|[-1.2631711, 0.46...|\n",
            "| 50|[-0.96600693, -0....|\n",
            "+---+--------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gmj0um2E8iQL",
        "outputId": "4ba48a1f-7ba6-40fe-8f60-c57c19ce0145"
      },
      "source": [
        "model.itemFactors.show(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+---+--------------------+\n",
            "| id|            features|\n",
            "+---+--------------------+\n",
            "| 10|[-0.96596885, 0.0...|\n",
            "| 20|[-0.43237323, -0....|\n",
            "| 30|[-0.8408578, -0.2...|\n",
            "| 40|[-0.20028046, -0....|\n",
            "| 50|[-1.3041071, 0.09...|\n",
            "+---+--------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dC7NDHF18jqZ"
      },
      "source": [
        "from pyspark.ml.recommendation import ALS\n",
        "from pyspark.ml.evaluation import RegressionEvaluator"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oCnQSleL8zu2"
      },
      "source": [
        "als = ALS(\n",
        "    userCol=\"userId\",\n",
        "    itemCol=\"movieId\",\n",
        "    ratingCol=\"rating\",\n",
        ")\n",
        "\n",
        "(training_data, validation_data) = ratings.randomSplit([8.0, 2.0])\n",
        "\n",
        "evaluator = RegressionEvaluator(\n",
        "    metricName=\"rmse\", labelCol=\"rating\", predictionCol=\"prediction\"\n",
        ")\n",
        "\n",
        "model = als.fit(training_data)\n",
        "predictions = model.transform(validation_data)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jec6qWF383v0",
        "outputId": "390464d2-ce41-4af1-ea26-bf16bcc0f888"
      },
      "source": [
        "predictions.show(10, False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------+-------+------+----------+\n",
            "|userId|movieId|rating|prediction|\n",
            "+------+-------+------+----------+\n",
            "|218   |471    |4.0   |3.1557236 |\n",
            "|217   |471    |2.0   |2.904364  |\n",
            "|136   |471    |4.0   |3.0653472 |\n",
            "|273   |471    |5.0   |4.178053  |\n",
            "|287   |471    |4.5   |2.9642751 |\n",
            "|469   |471    |5.0   |3.2853742 |\n",
            "|191   |496    |5.0   |NaN       |\n",
            "|159   |1088   |4.0   |2.7479868 |\n",
            "|599   |1088   |2.5   |2.4010575 |\n",
            "|169   |1088   |4.5   |4.196451  |\n",
            "+------+-------+------+----------+\n",
            "only showing top 10 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-CCE4WTd85Pm",
        "outputId": "3f182fa8-e129-4e54-eb56-ea9988bdfcf0"
      },
      "source": [
        "rmse = evaluator.evaluate(predictions.na.drop())\n",
        "print(rmse)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.8793350703923346\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bejqt5_J9Cv0"
      },
      "source": [
        "from pyspark.ml.tuning import CrossValidator, ParamGridBuilder\n",
        "\n",
        "parameter_grid = (\n",
        "    ParamGridBuilder()\n",
        "    .addGrid(als.rank, [1, 5, 10])\n",
        "    .addGrid(als.maxIter, [20])\n",
        "    .addGrid(als.regParam, [0.05, 0.1])\n",
        "    .build()\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l-CChHqs9MFW",
        "outputId": "52b63536-75c2-4e8c-d398-118a7c6f5e79"
      },
      "source": [
        "from pprint import pprint\n",
        "\n",
        "pprint(parameter_grid)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[{Param(parent='ALS_3a101ba5e05e', name='maxIter', doc='max number of iterations (>= 0).'): 20,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='regParam', doc='regularization parameter (>= 0).'): 0.05,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='rank', doc='rank of the factorization'): 1},\n",
            " {Param(parent='ALS_3a101ba5e05e', name='maxIter', doc='max number of iterations (>= 0).'): 20,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='regParam', doc='regularization parameter (>= 0).'): 0.1,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='rank', doc='rank of the factorization'): 1},\n",
            " {Param(parent='ALS_3a101ba5e05e', name='maxIter', doc='max number of iterations (>= 0).'): 20,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='regParam', doc='regularization parameter (>= 0).'): 0.05,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='rank', doc='rank of the factorization'): 5},\n",
            " {Param(parent='ALS_3a101ba5e05e', name='maxIter', doc='max number of iterations (>= 0).'): 20,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='regParam', doc='regularization parameter (>= 0).'): 0.1,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='rank', doc='rank of the factorization'): 5},\n",
            " {Param(parent='ALS_3a101ba5e05e', name='maxIter', doc='max number of iterations (>= 0).'): 20,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='regParam', doc='regularization parameter (>= 0).'): 0.05,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='rank', doc='rank of the factorization'): 10},\n",
            " {Param(parent='ALS_3a101ba5e05e', name='maxIter', doc='max number of iterations (>= 0).'): 20,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='regParam', doc='regularization parameter (>= 0).'): 0.1,\n",
            "  Param(parent='ALS_3a101ba5e05e', name='rank', doc='rank of the factorization'): 10}]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YvFCYHdx9MgF"
      },
      "source": [
        "crossvalidator = CrossValidator(\n",
        "    estimator=als,\n",
        "    estimatorParamMaps=parameter_grid,\n",
        "    evaluator=evaluator,\n",
        "    numFolds=2,\n",
        ")\n",
        "\n",
        "crossval_model = crossvalidator.fit(training_data)\n",
        "predictions = crossval_model.transform(validation_data)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zuJ8jdGg9PNa",
        "outputId": "82f01809-8cf4-4127-a24e-77fdfd3c42db"
      },
      "source": [
        "rmse = evaluator.evaluate(predictions.na.drop())\n",
        "print(rmse)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.014127339763445\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rWIGzq5M9S7I"
      },
      "source": [
        "model = crossval_model.bestModel"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kiy1fo25wmKB"
      },
      "source": [
        "### MLlib data source APIs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CVQbCK_7ytgO"
      },
      "source": [
        "Vectors and Matrices"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_22TVFwnwn8s",
        "outputId": "56d7d80c-5bab-45b5-99ee-c63aace40c7e"
      },
      "source": [
        "import numpy as np\n",
        "import scipy.sparse as sps\n",
        "from pyspark.sql import SparkSession\n",
        "from pyspark.ml.linalg import Vectors\n",
        "from pyspark.ml.linalg import Matrix, Matrices\n",
        "\n",
        "spark = SparkSession.builder.getOrCreate()\n",
        "\n",
        "# Use a NumPy array as a dense vector.\n",
        "dv1 = np.array([1.0, 0.0, 3.0])\n",
        "# Use a Python list as a dense vector.\n",
        "dv2 = [1.0, 0.0, 3.0]\n",
        "print(\"Dense vector 1:\", dv1)\n",
        "print(\"Dense vector 2:\", dv2)\n",
        "\n",
        "# Create a SparseVector.\n",
        "sv1 = Vectors.sparse(3, [0, 2], [1.0, 3.0])\n",
        "# Use a single-column SciPy csc_matrix as a sparse vector.\n",
        "sv2 = sps.csc_matrix((np.array([1.0, 3.0]), np.array([0, 2]), np.array([0, 2])), shape=(3, 1))\n",
        "print(\"Sparse vector 1:\", sv1)\n",
        "print(\"Sparse vector 2:\", sv2)\n",
        "\n",
        "# Create a dense matrix\n",
        "dm = Matrices.dense(3, 2, [1, 3, 5, 2, 4, 6])\n",
        "# Create a sparse matrix\n",
        "sm = Matrices.sparse(3, 2, [0, 1, 3], [0, 2, 1], [9, 6, 8])\n",
        "print(\"Dense matrix:\", dm)\n",
        "print(\"Sparse matrix:\", sm)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dense vector 1: [1. 0. 3.]\n",
            "Dense vector 2: [1.0, 0.0, 3.0]\n",
            "Sparse vector 1: (3,[0,2],[1.0,3.0])\n",
            "Sparse vector 2:   (0, 0)\t1.0\n",
            "  (2, 0)\t3.0\n",
            "Dense matrix: DenseMatrix([[1., 2.],\n",
            "             [3., 4.],\n",
            "             [5., 6.]])\n",
            "Sparse matrix: 3 X 2 CSCMatrix\n",
            "(0,0) 9.0\n",
            "(2,1) 6.0\n",
            "(1,1) 8.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qXDXrp2d0_ZK"
      },
      "source": [
        "Images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "id": "YDm2socEzjxD",
        "outputId": "be2eb555-22f8-4e95-8a31-16dff6541f39"
      },
      "source": [
        "from pyspark.sql import SparkSession\n",
        "spark = SparkSession.builder.getOrCreate()\n",
        "\n",
        "PATH = \"./spark-3.0.2-bin-hadoop3.2/data/mllib/images/origin/kittens\"\n",
        "df = (\n",
        "    spark.read.format(\"image\")\n",
        "    .option(\"dropInvalid\", True)\n",
        "    .load(PATH)\n",
        "    .select(\"image.origin\", \"image.height\", \"image.width\", \"image.nChannels\", \"image.mode\", \"image.data\")\n",
        ")\n",
        "df.toPandas()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>origin</th>\n",
              "      <th>height</th>\n",
              "      <th>width</th>\n",
              "      <th>nChannels</th>\n",
              "      <th>mode</th>\n",
              "      <th>data</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>file:///content/Mastering-Big-Data-Analytics-w...</td>\n",
              "      <td>311</td>\n",
              "      <td>300</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>[193, 193, 193, 194, 194, 194, 194, 194, 194, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>file:///content/Mastering-Big-Data-Analytics-w...</td>\n",
              "      <td>313</td>\n",
              "      <td>199</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>[208, 229, 237, 202, 223, 231, 210, 231, 239, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>file:///content/Mastering-Big-Data-Analytics-w...</td>\n",
              "      <td>200</td>\n",
              "      <td>300</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>[88, 93, 96, 88, 93, 96, 88, 93, 96, 89, 94, 9...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>file:///content/Mastering-Big-Data-Analytics-w...</td>\n",
              "      <td>296</td>\n",
              "      <td>300</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>[203, 230, 244, 202, 229, 243, 201, 228, 242, ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                              origin  ...                                               data\n",
              "0  file:///content/Mastering-Big-Data-Analytics-w...  ...  [193, 193, 193, 194, 194, 194, 194, 194, 194, ...\n",
              "1  file:///content/Mastering-Big-Data-Analytics-w...  ...  [208, 229, 237, 202, 223, 231, 210, 231, 239, ...\n",
              "2  file:///content/Mastering-Big-Data-Analytics-w...  ...  [88, 93, 96, 88, 93, 96, 88, 93, 96, 89, 94, 9...\n",
              "3  file:///content/Mastering-Big-Data-Analytics-w...  ...  [203, 230, 244, 202, 229, 243, 201, 228, 242, ...\n",
              "\n",
              "[4 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6v8WGBph4Ocr"
      },
      "source": [
        "libSVM"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7VMILKvg32qg",
        "outputId": "b30b7b97-a132-4d48-9470-8fca2d19d613"
      },
      "source": [
        "from pyspark.sql import SparkSession\n",
        "spark = SparkSession.builder.getOrCreate()\n",
        "\n",
        "PATH = \"./spark-3.0.2-bin-hadoop3.2/data/mllib/sample_libsvm_data.txt\"\n",
        "\n",
        "df = spark.read.format(\"libsvm\").option(\"numFeatures\", \"780\").load(PATH)\n",
        "df.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+-----+--------------------+\n",
            "|label|            features|\n",
            "+-----+--------------------+\n",
            "|  0.0|(780,[127,128,129...|\n",
            "|  1.0|(780,[158,159,160...|\n",
            "|  1.0|(780,[124,125,126...|\n",
            "|  1.0|(780,[152,153,154...|\n",
            "|  1.0|(780,[151,152,153...|\n",
            "|  0.0|(780,[129,130,131...|\n",
            "|  1.0|(780,[158,159,160...|\n",
            "|  1.0|(780,[99,100,101,...|\n",
            "|  0.0|(780,[154,155,156...|\n",
            "|  0.0|(780,[127,128,129...|\n",
            "|  1.0|(780,[154,155,156...|\n",
            "|  0.0|(780,[153,154,155...|\n",
            "|  0.0|(780,[151,152,153...|\n",
            "|  1.0|(780,[129,130,131...|\n",
            "|  0.0|(780,[154,155,156...|\n",
            "|  1.0|(780,[150,151,152...|\n",
            "|  0.0|(780,[124,125,126...|\n",
            "|  0.0|(780,[152,153,154...|\n",
            "|  1.0|(780,[97,98,99,12...|\n",
            "|  1.0|(780,[124,125,126...|\n",
            "+-----+--------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cH3-B5q430E8"
      },
      "source": [
        "### NLP and Hyperparameter Tuning in PySpark"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FwtnjDME30rU"
      },
      "source": [
        "from pyspark.sql import SparkSession\n",
        "\n",
        "spark = SparkSession.builder.getOrCreate()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pLpIwr8EIUpZ",
        "outputId": "b7db4e2a-2261-48ae-aac4-4df8baa50aa6"
      },
      "source": [
        "from pyspark.ml import Pipeline\n",
        "from pyspark.ml.classification import LogisticRegression\n",
        "from pyspark.ml.evaluation import BinaryClassificationEvaluator\n",
        "from pyspark.ml.feature import HashingTF, Tokenizer\n",
        "from pyspark.ml.tuning import CrossValidator, ParamGridBuilder\n",
        "\n",
        "# Prepare training documents, which are labeled.\n",
        "training_data = [\n",
        "    (0, \"a b c d e spark\", 1.0),\n",
        "    (1, \"b d\", 0.0),\n",
        "    (2, \"spark f g h\", 1.0),\n",
        "    (3, \"hadoop mapreduce\", 0.0),\n",
        "    (4, \"b spark who\", 1.0),\n",
        "    (5, \"g d a y\", 0.0),\n",
        "    (6, \"spark fly\", 1.0),\n",
        "    (7, \"was mapreduce\", 0.0),\n",
        "    (8, \"e spark program\", 1.0),\n",
        "    (9, \"a e c l\", 0.0),\n",
        "    (10, \"spark compile\", 1.0),\n",
        "    (11, \"hadoop software\", 0.0),\n",
        "]\n",
        "training = spark.createDataFrame(training_data, [\"id\", \"text\", \"label\"])\n",
        "print(\"Dataset used for training (labeled):\")\n",
        "training.show()\n",
        "\n",
        "# Prepare test documents, which are unlabeled.\n",
        "test_data = [\n",
        "    (4, \"spark i j k\"),\n",
        "    (5, \"l m n\"),\n",
        "    (6, \"mapreduce spark\"),\n",
        "    (7, \"apache hadoop\"),\n",
        "]\n",
        "test = spark.createDataFrame(test_data, [\"id\", \"text\"],)\n",
        "print(\"Dataset used for testing (unlabeled):\")\n",
        "test.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dataset used for training (labeled):\n",
            "+---+----------------+-----+\n",
            "| id|            text|label|\n",
            "+---+----------------+-----+\n",
            "|  0| a b c d e spark|  1.0|\n",
            "|  1|             b d|  0.0|\n",
            "|  2|     spark f g h|  1.0|\n",
            "|  3|hadoop mapreduce|  0.0|\n",
            "|  4|     b spark who|  1.0|\n",
            "|  5|         g d a y|  0.0|\n",
            "|  6|       spark fly|  1.0|\n",
            "|  7|   was mapreduce|  0.0|\n",
            "|  8| e spark program|  1.0|\n",
            "|  9|         a e c l|  0.0|\n",
            "| 10|   spark compile|  1.0|\n",
            "| 11| hadoop software|  0.0|\n",
            "+---+----------------+-----+\n",
            "\n",
            "Dataset used for testing (unlabeled):\n",
            "+---+---------------+\n",
            "| id|           text|\n",
            "+---+---------------+\n",
            "|  4|    spark i j k|\n",
            "|  5|          l m n|\n",
            "|  6|mapreduce spark|\n",
            "|  7|  apache hadoop|\n",
            "+---+---------------+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2wEzIxLGIbNl",
        "outputId": "099ce818-e1d3-4929-ff61-6fc2035d7985"
      },
      "source": [
        "# Configure an ML pipeline, which consists of tree stages: tokenizer, hashingTF, and lr.\n",
        "tokenizer = Tokenizer(inputCol=\"text\", outputCol=\"words\")\n",
        "hashingTF = HashingTF(inputCol=tokenizer.getOutputCol(), outputCol=\"features\")\n",
        "lr = LogisticRegression(maxIter=10)\n",
        "pipeline = Pipeline(stages=[tokenizer, hashingTF, lr])\n",
        "\n",
        "# We now treat the Pipeline as an Estimator, wrapping it in a CrossValidator instance.\n",
        "# This will allow us to jointly choose parameters for all Pipeline stages.\n",
        "# A CrossValidator requires an Estimator, a set of Estimator ParamMaps, and an Evaluator.\n",
        "# We use a ParamGridBuilder to construct a grid of parameters to search over.\n",
        "# With 3 values for hashingTF.numFeatures and 2 values for lr.regParam,\n",
        "# this grid will have 3 x 2 = 6 parameter settings for CrossValidator to choose from.\n",
        "paramGrid = (\n",
        "    ParamGridBuilder()\n",
        "    .addGrid(hashingTF.numFeatures, [10, 100, 1000])\n",
        "    .addGrid(lr.regParam, [0.1, 0.01])\n",
        "    .build()\n",
        ")\n",
        "\n",
        "crossval = CrossValidator(\n",
        "    estimator=pipeline,\n",
        "    estimatorParamMaps=paramGrid,\n",
        "    evaluator=BinaryClassificationEvaluator(),\n",
        "    numFolds=2,\n",
        ")  # use 3+ folds in practice\n",
        "\n",
        "# Run cross-validation, and choose the best set of parameters.\n",
        "cvModel = crossval.fit(training)\n",
        "\n",
        "# Make predictions on test documents. cvModel uses the best model found (lrModel).\n",
        "prediction = cvModel.transform(test)\n",
        "selected = prediction.select(\"id\", \"text\", \"probability\", \"prediction\")\n",
        "selected.show(100, False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+---+---------------+----------------------------------------+----------+\n",
            "|id |text           |probability                             |prediction|\n",
            "+---+---------------+----------------------------------------+----------+\n",
            "|4  |spark i j k    |[0.2661287892091301,0.7338712107908699] |1.0       |\n",
            "|5  |l m n          |[0.9209302389399868,0.07906976106001318]|0.0       |\n",
            "|6  |mapreduce spark|[0.4429343598469927,0.5570656401530073] |1.0       |\n",
            "|7  |apache hadoop  |[0.8583692828862762,0.14163071711372377]|0.0       |\n",
            "+---+---------------+----------------------------------------+----------+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p--Z0152S29w"
      },
      "source": [
        "## Twitter Sentiment Analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UGgHlJMwS6np"
      },
      "source": [
        "### Environment Setup"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WG54aiBII2pD"
      },
      "source": [
        "import pandas as pd\n",
        "from IPython.core.display import display\n",
        "import seaborn as sns\n",
        "\n",
        "from pyspark.sql import SparkSession\n",
        "from pyspark.sql import functions as f\n",
        "\n",
        "# General settings for display purposes\n",
        "pd.options.display.max_columns = None\n",
        "pd.options.display.max_rows = None\n",
        "pd.options.display.max_colwidth = 144\n",
        "sns.set(color_codes=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YnNJoeIkTFMU"
      },
      "source": [
        "spark = SparkSession.builder.getOrCreate()\n",
        "\n",
        "# Source sentiment140: http://help.sentiment140.com/for-students/\n",
        "schema = \"polarity FLOAT, id LONG, date_time STRING, query STRING, user STRING, text STRING\"\n",
        "spark_reader = spark.read.schema(schema)\n",
        "\n",
        "# file 1: testdata.manual.2009.06.14.csv\n",
        "TESTDATA_PATH = (\"./data-sets/sentiment-140-training-data/testdata.manual.2009.06.14.csv\")\n",
        "raw_test_data = spark_reader.csv(\n",
        "    TESTDATA_PATH,\n",
        "    quote='\"',\n",
        "    header=False,\n",
        "    inferSchema=True,\n",
        "    columnNameOfCorruptRecord=\"corrupt_data\",\n",
        ").cache()\n",
        "\n",
        "# file 2: training.1600000.processed.noemoticon.csv\n",
        "TRAININGDATA_PATH = \"./data-sets/sentiment-140-training-data/training.1600000.processed.noemoticon.csv\"\n",
        "raw_training_data = spark_reader.csv(\n",
        "    TRAININGDATA_PATH,\n",
        "    quote='\"',\n",
        "    header=False,\n",
        "    inferSchema=True,\n",
        "    columnNameOfCorruptRecord=\"corrupt_data\",\n",
        ").cache()\n",
        "\n",
        "# path that we will write our raw data to\n",
        "OUTPUT_PATH = (\"./data-sets/sentiment-140-training-data/RAW\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "54DRgtHXbTkc"
      },
      "source": [
        "### Data Exploration"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Qo0rcNjlToGq",
        "outputId": "db17951d-58b9-45ae-e50e-c471c35ce84e"
      },
      "source": [
        "# Count of data\n",
        "print(f\"Overall data count: {raw_test_data.count()}\")\n",
        "\n",
        "# Data summary\n",
        "display(raw_test_data.summary().toPandas())\n",
        "print(\"Data schema\")\n",
        "raw_test_data.printSchema()\n",
        "\n",
        "# Let's look at 50 rows of data\n",
        "display(raw_test_data.limit(50).toPandas())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overall data count: 498\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>summary</th>\n",
              "      <th>polarity</th>\n",
              "      <th>id</th>\n",
              "      <th>date_time</th>\n",
              "      <th>query</th>\n",
              "      <th>user</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>count</td>\n",
              "      <td>498</td>\n",
              "      <td>498</td>\n",
              "      <td>498</td>\n",
              "      <td>498</td>\n",
              "      <td>498</td>\n",
              "      <td>498</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>mean</td>\n",
              "      <td>2.0200803212851404</td>\n",
              "      <td>1867.2269076305222</td>\n",
              "      <td>None</td>\n",
              "      <td>46.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>stddev</td>\n",
              "      <td>1.6996858490577658</td>\n",
              "      <td>2834.891681137318</td>\n",
              "      <td>None</td>\n",
              "      <td>5.163977794943222</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>min</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3</td>\n",
              "      <td>Fri May 15 06:45:54 UTC 2009</td>\n",
              "      <td>\"\"\"booz allen\"\"\"</td>\n",
              "      <td>5x1llz</td>\n",
              "      <td>\"\"\"The Republican party is a bunch of anti-abo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>25%</td>\n",
              "      <td>0.0</td>\n",
              "      <td>388</td>\n",
              "      <td>None</td>\n",
              "      <td>40.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>50%</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1013</td>\n",
              "      <td>None</td>\n",
              "      <td>50.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>75%</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2367</td>\n",
              "      <td>None</td>\n",
              "      <td>50.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>max</td>\n",
              "      <td>4.0</td>\n",
              "      <td>14076</td>\n",
              "      <td>Wed May 27 23:59:18 UTC 2009</td>\n",
              "      <td>yankees</td>\n",
              "      <td>zedomax</td>\n",
              "      <td>zomg!!! I have a G2!!!!!!!</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  summary  ...                                               text\n",
              "0   count  ...                                                498\n",
              "1    mean  ...                                               None\n",
              "2  stddev  ...                                               None\n",
              "3     min  ...  \"\"\"The Republican party is a bunch of anti-abo...\n",
              "4     25%  ...                                               None\n",
              "5     50%  ...                                               None\n",
              "6     75%  ...                                               None\n",
              "7     max  ...                         zomg!!! I have a G2!!!!!!!\n",
              "\n",
              "[8 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Data schema\n",
            "root\n",
            " |-- polarity: float (nullable = true)\n",
            " |-- id: long (nullable = true)\n",
            " |-- date_time: string (nullable = true)\n",
            " |-- query: string (nullable = true)\n",
            " |-- user: string (nullable = true)\n",
            " |-- text: string (nullable = true)\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\n",
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              "    }\n",
              "\n",
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>polarity</th>\n",
              "      <th>id</th>\n",
              "      <th>date_time</th>\n",
              "      <th>query</th>\n",
              "      <th>user</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>4.0</td>\n",
              "      <td>3</td>\n",
              "      <td>Mon May 11 03:17:40 UTC 2009</td>\n",
              "      <td>kindle2</td>\n",
              "      <td>tpryan</td>\n",
              "      <td>@stellargirl I loooooooovvvvvveee my Kindle2. ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.0</td>\n",
              "      <td>4</td>\n",
              "      <td>Mon May 11 03:18:03 UTC 2009</td>\n",
              "      <td>kindle2</td>\n",
              "      <td>vcu451</td>\n",
              "      <td>Reading my kindle2...  Love it... Lee childs i...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.0</td>\n",
              "      <td>5</td>\n",
              "      <td>Mon May 11 03:18:54 UTC 2009</td>\n",
              "      <td>kindle2</td>\n",
              "      <td>chadfu</td>\n",
              "      <td>Ok, first assesment of the #kindle2 ...it fuck...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.0</td>\n",
              "      <td>6</td>\n",
              "      <td>Mon May 11 03:19:04 UTC 2009</td>\n",
              "      <td>kindle2</td>\n",
              "      <td>SIX15</td>\n",
              "      <td>@kenburbary You'll love your Kindle2. I've had...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4.0</td>\n",
              "      <td>7</td>\n",
              "      <td>Mon May 11 03:21:41 UTC 2009</td>\n",
              "      <td>kindle2</td>\n",
              "      <td>yamarama</td>\n",
              "      <td>@mikefish  Fair enough. But i have the Kindle2...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>4.0</td>\n",
              "      <td>8</td>\n",
              "      <td>Mon May 11 03:22:00 UTC 2009</td>\n",
              "      <td>kindle2</td>\n",
              "      <td>GeorgeVHulme</td>\n",
              "      <td>@richardebaker no. it is too big. I'm quite ha...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>9</td>\n",
              "      <td>Mon May 11 03:22:30 UTC 2009</td>\n",
              "      <td>aig</td>\n",
              "      <td>Seth937</td>\n",
              "      <td>Fuck this economy. I hate aig and their non lo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>4.0</td>\n",
              "      <td>10</td>\n",
              "      <td>Mon May 11 03:26:10 UTC 2009</td>\n",
              "      <td>jquery</td>\n",
              "      <td>dcostalis</td>\n",
              "      <td>Jquery is my new best friend.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>4.0</td>\n",
              "      <td>11</td>\n",
              "      <td>Mon May 11 03:27:15 UTC 2009</td>\n",
              "      <td>twitter</td>\n",
              "      <td>PJ_King</td>\n",
              "      <td>Loves twitter</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>4.0</td>\n",
              "      <td>12</td>\n",
              "      <td>Mon May 11 03:29:20 UTC 2009</td>\n",
              "      <td>obama</td>\n",
              "      <td>mandanicole</td>\n",
              "      <td>how can you not love Obama? he makes jokes abo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2.0</td>\n",
              "      <td>13</td>\n",
              "      <td>Mon May 11 03:32:42 UTC 2009</td>\n",
              "      <td>obama</td>\n",
              "      <td>jpeb</td>\n",
              "      <td>Check this video out -- President Obama at the...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0.0</td>\n",
              "      <td>14</td>\n",
              "      <td>Mon May 11 03:32:48 UTC 2009</td>\n",
              "      <td>obama</td>\n",
              "      <td>kylesellers</td>\n",
              "      <td>@Karoli I firmly believe that Obama/Pelosi hav...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>4.0</td>\n",
              "      <td>15</td>\n",
              "      <td>Mon May 11 03:33:38 UTC 2009</td>\n",
              "      <td>obama</td>\n",
              "      <td>theviewfans</td>\n",
              "      <td>House Correspondents dinner was last night who...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>4.0</td>\n",
              "      <td>16</td>\n",
              "      <td>Mon May 11 05:05:58 UTC 2009</td>\n",
              "      <td>nike</td>\n",
              "      <td>MumsFP</td>\n",
              "      <td>Watchin Espn..Jus seen this new Nike Commerica...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.0</td>\n",
              "      <td>17</td>\n",
              "      <td>Mon May 11 05:06:22 UTC 2009</td>\n",
              "      <td>nike</td>\n",
              "      <td>vincentx24x</td>\n",
              "      <td>dear nike, stop with the flywire. that shit is...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>4.0</td>\n",
              "      <td>18</td>\n",
              "      <td>Mon May 11 05:20:15 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>cameronwylie</td>\n",
              "      <td>#lebron best athlete of our generation, if not...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>0.0</td>\n",
              "      <td>19</td>\n",
              "      <td>Mon May 11 05:20:28 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>luv8242</td>\n",
              "      <td>I was talking to this guy last night and he wa...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>4.0</td>\n",
              "      <td>20</td>\n",
              "      <td>Mon May 11 05:21:04 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>mtgillikin</td>\n",
              "      <td>i love lebron. http://bit.ly/PdHur</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>0.0</td>\n",
              "      <td>21</td>\n",
              "      <td>Mon May 11 05:21:37 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>ursecretdezire</td>\n",
              "      <td>@ludajuice Lebron is a Beast, but I'm still ch...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>4.0</td>\n",
              "      <td>22</td>\n",
              "      <td>Mon May 11 05:21:45 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>Native_01</td>\n",
              "      <td>@Pmillzz lebron IS THE BOSS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>4.0</td>\n",
              "      <td>23</td>\n",
              "      <td>Mon May 11 05:22:03 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>princezzcutz</td>\n",
              "      <td>@sketchbug Lebron is a hometown hero to me, lo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>4.0</td>\n",
              "      <td>24</td>\n",
              "      <td>Mon May 11 05:22:12 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>peterlikewhat</td>\n",
              "      <td>lebron and zydrunas are such an awesome duo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>4.0</td>\n",
              "      <td>25</td>\n",
              "      <td>Mon May 11 05:22:37 UTC 2009</td>\n",
              "      <td>lebron</td>\n",
              "      <td>emceet</td>\n",
              "      <td>@wordwhizkid Lebron is a beast... nobody in th...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>4.0</td>\n",
              "      <td>26</td>\n",
              "      <td>Mon May 11 06:02:24 UTC 2009</td>\n",
              "      <td>iphone app</td>\n",
              "      <td>CocoSavanna</td>\n",
              "      <td>downloading apps for my iphone! So much fun :-...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>4.0</td>\n",
              "      <td>33</td>\n",
              "      <td>Mon May 11 19:47:29 UTC 2009</td>\n",
              "      <td>visa</td>\n",
              "      <td>DreambigRadio</td>\n",
              "      <td>good news, just had a call from the Visa offic...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>4.0</td>\n",
              "      <td>34</td>\n",
              "      <td>Mon May 11 19:49:21 UTC 2009</td>\n",
              "      <td>fredwilson</td>\n",
              "      <td>andrewwatson</td>\n",
              "      <td>http://twurl.nl/epkr4b - awesome come back fro...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>4.0</td>\n",
              "      <td>35</td>\n",
              "      <td>Mon May 11 19:50:07 UTC 2009</td>\n",
              "      <td>fredwilson</td>\n",
              "      <td>fredwilson</td>\n",
              "      <td>In montreal for a long weekend of R&amp;amp;R. Muc...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>4.0</td>\n",
              "      <td>46</td>\n",
              "      <td>Thu May 14 02:58:07 UTC 2009</td>\n",
              "      <td>\"\"\"booz allen\"\"\"</td>\n",
              "      <td>JoeSchueller</td>\n",
              "      <td>Booz Allen Hamilton has a bad ass homegrown so...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>4.0</td>\n",
              "      <td>47</td>\n",
              "      <td>Thu May 14 02:58:23 UTC 2009</td>\n",
              "      <td>\"\"\"booz allen\"\"\"</td>\n",
              "      <td>scottabel</td>\n",
              "      <td>[#MLUC09] Customer Innovation Award Winner: Bo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>4.0</td>\n",
              "      <td>49</td>\n",
              "      <td>Thu May 14 05:24:50 UTC 2009</td>\n",
              "      <td>40d</td>\n",
              "      <td>JustMe_D</td>\n",
              "      <td>@SoChi2 I current use the Nikon D90 and love i...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2.0</td>\n",
              "      <td>50</td>\n",
              "      <td>Thu May 14 05:25:04 UTC 2009</td>\n",
              "      <td>40d</td>\n",
              "      <td>hiteshbagai</td>\n",
              "      <td>need suggestions for a good IR filter for my c...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2.0</td>\n",
              "      <td>117</td>\n",
              "      <td>Sat May 16 16:18:36 UTC 2009</td>\n",
              "      <td>google</td>\n",
              "      <td>Annimallover</td>\n",
              "      <td>@surfit: I just checked my google for my busin...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>4.0</td>\n",
              "      <td>118</td>\n",
              "      <td>Sat May 16 16:19:04 UTC 2009</td>\n",
              "      <td>google</td>\n",
              "      <td>J_Holl</td>\n",
              "      <td>@phyreman9 Google is always a good place to lo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>0.0</td>\n",
              "      <td>119</td>\n",
              "      <td>Sat May 16 16:19:24 UTC 2009</td>\n",
              "      <td>google</td>\n",
              "      <td>vamsmack</td>\n",
              "      <td>Played with an android google phone. The slide...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>0.0</td>\n",
              "      <td>120</td>\n",
              "      <td>Sat May 16 16:25:41 UTC 2009</td>\n",
              "      <td>aig</td>\n",
              "      <td>schroncd</td>\n",
              "      <td>US planning to resume the military tribunals a...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>0.0</td>\n",
              "      <td>121</td>\n",
              "      <td>Sat May 16 22:42:07 UTC 2009</td>\n",
              "      <td>itchy</td>\n",
              "      <td>MarissaLeeD</td>\n",
              "      <td>omg so bored &amp;amp; my tattoooos are so itchy!!...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>0.0</td>\n",
              "      <td>122</td>\n",
              "      <td>Sat May 16 22:42:25 UTC 2009</td>\n",
              "      <td>itchy</td>\n",
              "      <td>robloposky</td>\n",
              "      <td>I'm itchy and miserable!</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>0.0</td>\n",
              "      <td>123</td>\n",
              "      <td>Sat May 16 22:42:44 UTC 2009</td>\n",
              "      <td>itchy</td>\n",
              "      <td>EdwinLValencia</td>\n",
              "      <td>@sekseemess no. I'm not itchy for now. Maybe l...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>4.0</td>\n",
              "      <td>124</td>\n",
              "      <td>Sat May 16 23:48:15 UTC 2009</td>\n",
              "      <td>stanford</td>\n",
              "      <td>imusicmash</td>\n",
              "      <td>RT @jessverr I love the nerdy Stanford human b...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>4.0</td>\n",
              "      <td>125</td>\n",
              "      <td>Sat May 16 23:58:34 UTC 2009</td>\n",
              "      <td>lyx</td>\n",
              "      <td>drewloewe</td>\n",
              "      <td>@spinuzzi: Has been a bit crazy, with steep le...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>4.0</td>\n",
              "      <td>131</td>\n",
              "      <td>Sun May 17 15:05:03 UTC 2009</td>\n",
              "      <td>Danny Gokey</td>\n",
              "      <td>VickyTigger</td>\n",
              "      <td>\"I'm listening to \"\"P.Y.T\"\" by Danny Gokey &amp;lt...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>4.0</td>\n",
              "      <td>132</td>\n",
              "      <td>Sun May 17 17:27:45 UTC 2009</td>\n",
              "      <td>sleep</td>\n",
              "      <td>babblyabbie</td>\n",
              "      <td>is going to sleep then on a bike ride:]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>0.0</td>\n",
              "      <td>133</td>\n",
              "      <td>Sun May 17 17:27:49 UTC 2009</td>\n",
              "      <td>sleep</td>\n",
              "      <td>kisjoaquin</td>\n",
              "      <td>cant sleep... my tooth is aching.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>0.0</td>\n",
              "      <td>134</td>\n",
              "      <td>Sun May 17 17:28:02 UTC 2009</td>\n",
              "      <td>sleep</td>\n",
              "      <td>Whacktackular</td>\n",
              "      <td>Blah, blah, blah same old same old. No plans t...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>0.0</td>\n",
              "      <td>135</td>\n",
              "      <td>Sun May 17 17:29:50 UTC 2009</td>\n",
              "      <td>san francisco</td>\n",
              "      <td>Adrigonzo</td>\n",
              "      <td>glad i didnt do Bay to Breakers today, it's 10...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2.0</td>\n",
              "      <td>136</td>\n",
              "      <td>Sun May 17 17:30:19 UTC 2009</td>\n",
              "      <td>san francisco</td>\n",
              "      <td>sulu34</td>\n",
              "      <td>is in San Francisco at Bay to Breakers.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2.0</td>\n",
              "      <td>137</td>\n",
              "      <td>Sun May 17 17:30:23 UTC 2009</td>\n",
              "      <td>san francisco</td>\n",
              "      <td>schuyler</td>\n",
              "      <td>just landed at San Francisco</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2.0</td>\n",
              "      <td>138</td>\n",
              "      <td>Sun May 17 17:30:56 UTC 2009</td>\n",
              "      <td>san francisco</td>\n",
              "      <td>MattBragoni</td>\n",
              "      <td>San Francisco today.  Any suggestions?</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.0</td>\n",
              "      <td>139</td>\n",
              "      <td>Sun May 17 17:32:00 UTC 2009</td>\n",
              "      <td>aig</td>\n",
              "      <td>KennyTRoland</td>\n",
              "      <td>?Obama Administration Must Stop Bonuses to AIG...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>0.0</td>\n",
              "      <td>140</td>\n",
              "      <td>Sun May 17 17:32:30 UTC 2009</td>\n",
              "      <td>aig</td>\n",
              "      <td>aMild</td>\n",
              "      <td>started to think that Citi is in really deep s...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    polarity  ...                                               text\n",
              "0        4.0  ...  @stellargirl I loooooooovvvvvveee my Kindle2. ...\n",
              "1        4.0  ...  Reading my kindle2...  Love it... Lee childs i...\n",
              "2        4.0  ...  Ok, first assesment of the #kindle2 ...it fuck...\n",
              "3        4.0  ...  @kenburbary You'll love your Kindle2. I've had...\n",
              "4        4.0  ...  @mikefish  Fair enough. But i have the Kindle2...\n",
              "5        4.0  ...  @richardebaker no. it is too big. I'm quite ha...\n",
              "6        0.0  ...  Fuck this economy. I hate aig and their non lo...\n",
              "7        4.0  ...                      Jquery is my new best friend.\n",
              "8        4.0  ...                                      Loves twitter\n",
              "9        4.0  ...  how can you not love Obama? he makes jokes abo...\n",
              "10       2.0  ...  Check this video out -- President Obama at the...\n",
              "11       0.0  ...  @Karoli I firmly believe that Obama/Pelosi hav...\n",
              "12       4.0  ...  House Correspondents dinner was last night who...\n",
              "13       4.0  ...  Watchin Espn..Jus seen this new Nike Commerica...\n",
              "14       0.0  ...  dear nike, stop with the flywire. that shit is...\n",
              "15       4.0  ...  #lebron best athlete of our generation, if not...\n",
              "16       0.0  ...  I was talking to this guy last night and he wa...\n",
              "17       4.0  ...                 i love lebron. http://bit.ly/PdHur\n",
              "18       0.0  ...  @ludajuice Lebron is a Beast, but I'm still ch...\n",
              "19       4.0  ...                        @Pmillzz lebron IS THE BOSS\n",
              "20       4.0  ...  @sketchbug Lebron is a hometown hero to me, lo...\n",
              "21       4.0  ...        lebron and zydrunas are such an awesome duo\n",
              "22       4.0  ...  @wordwhizkid Lebron is a beast... nobody in th...\n",
              "23       4.0  ...  downloading apps for my iphone! So much fun :-...\n",
              "24       4.0  ...  good news, just had a call from the Visa offic...\n",
              "25       4.0  ...  http://twurl.nl/epkr4b - awesome come back fro...\n",
              "26       4.0  ...  In montreal for a long weekend of R&amp;R. Muc...\n",
              "27       4.0  ...  Booz Allen Hamilton has a bad ass homegrown so...\n",
              "28       4.0  ...  [#MLUC09] Customer Innovation Award Winner: Bo...\n",
              "29       4.0  ...  @SoChi2 I current use the Nikon D90 and love i...\n",
              "30       2.0  ...  need suggestions for a good IR filter for my c...\n",
              "31       2.0  ...  @surfit: I just checked my google for my busin...\n",
              "32       4.0  ...  @phyreman9 Google is always a good place to lo...\n",
              "33       0.0  ...  Played with an android google phone. The slide...\n",
              "34       0.0  ...  US planning to resume the military tribunals a...\n",
              "35       0.0  ...  omg so bored &amp; my tattoooos are so itchy!!...\n",
              "36       0.0  ...                           I'm itchy and miserable!\n",
              "37       0.0  ...  @sekseemess no. I'm not itchy for now. Maybe l...\n",
              "38       4.0  ...  RT @jessverr I love the nerdy Stanford human b...\n",
              "39       4.0  ...  @spinuzzi: Has been a bit crazy, with steep le...\n",
              "40       4.0  ...  \"I'm listening to \"\"P.Y.T\"\" by Danny Gokey &lt...\n",
              "41       4.0  ...            is going to sleep then on a bike ride:]\n",
              "42       0.0  ...                  cant sleep... my tooth is aching.\n",
              "43       0.0  ...  Blah, blah, blah same old same old. No plans t...\n",
              "44       0.0  ...  glad i didnt do Bay to Breakers today, it's 10...\n",
              "45       2.0  ...            is in San Francisco at Bay to Breakers.\n",
              "46       2.0  ...                       just landed at San Francisco\n",
              "47       2.0  ...             San Francisco today.  Any suggestions?\n",
              "48       0.0  ...  ?Obama Administration Must Stop Bonuses to AIG...\n",
              "49       0.0  ...  started to think that Citi is in really deep s...\n",
              "\n",
              "[50 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "taEwhrtrTqtG",
        "outputId": "1db18c5d-c3df-45d4-cb78-e23836310161"
      },
      "source": [
        "# Count of data\n",
        "print(f\"Overall data count: {raw_training_data.count()}\")\n",
        "\n",
        "# Data summary\n",
        "display(raw_training_data.summary().toPandas())\n",
        "print(\"Data schema\")\n",
        "raw_training_data.printSchema()\n",
        "\n",
        "# Let's look at 50 rows of data\n",
        "display(raw_training_data.limit(50).toPandas())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overall data count: 1600000\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>summary</th>\n",
              "      <th>polarity</th>\n",
              "      <th>id</th>\n",
              "      <th>date_time</th>\n",
              "      <th>query</th>\n",
              "      <th>user</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>count</td>\n",
              "      <td>1600000</td>\n",
              "      <td>1600000</td>\n",
              "      <td>1600000</td>\n",
              "      <td>1600000</td>\n",
              "      <td>1600000</td>\n",
              "      <td>1600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>mean</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.9988175522956276E9</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>4.325887521835714E9</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>stddev</td>\n",
              "      <td>2.0000006250002933</td>\n",
              "      <td>1.9357607362269536E8</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>5.1627332184548904E10</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>min</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1467810369</td>\n",
              "      <td>Fri Apr 17 20:30:31 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>000catnap000</td>\n",
              "      <td>exh...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>25%</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1956912288</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>32508.0</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>50%</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2002093413</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>130587.0</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>75%</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2177045846</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1100101.0</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>max</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2329205794</td>\n",
              "      <td>Wed May 27 07:27:38 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>zzzzeus111</td>\n",
              "      <td>�����ߧ�ǿ�����ж�؜��� &amp;lt;&amp;lt;----I DID NOT KNOW...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  summary  ...                                               text\n",
              "0   count  ...                                            1600000\n",
              "1    mean  ...                                               None\n",
              "2  stddev  ...                                               None\n",
              "3     min  ...                                             exh...\n",
              "4     25%  ...                                               None\n",
              "5     50%  ...                                               None\n",
              "6     75%  ...                                               None\n",
              "7     max  ...  �����ߧ�ǿ�����ж�؜��� &lt;&lt;----I DID NOT KNOW...\n",
              "\n",
              "[8 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Data schema\n",
            "root\n",
            " |-- polarity: float (nullable = true)\n",
            " |-- id: long (nullable = true)\n",
            " |-- date_time: string (nullable = true)\n",
            " |-- query: string (nullable = true)\n",
            " |-- user: string (nullable = true)\n",
            " |-- text: string (nullable = true)\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>polarity</th>\n",
              "      <th>id</th>\n",
              "      <th>date_time</th>\n",
              "      <th>query</th>\n",
              "      <th>user</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467810369</td>\n",
              "      <td>Mon Apr 06 22:19:45 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>_TheSpecialOne_</td>\n",
              "      <td>@switchfoot http://twitpic.com/2y1zl - Awww, t...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467810672</td>\n",
              "      <td>Mon Apr 06 22:19:49 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>scotthamilton</td>\n",
              "      <td>is upset that he can't update his Facebook by ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467810917</td>\n",
              "      <td>Mon Apr 06 22:19:53 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>mattycus</td>\n",
              "      <td>@Kenichan I dived many times for the ball. Man...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467811184</td>\n",
              "      <td>Mon Apr 06 22:19:57 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>ElleCTF</td>\n",
              "      <td>my whole body feels itchy and like its on fire</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467811193</td>\n",
              "      <td>Mon Apr 06 22:19:57 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>Karoli</td>\n",
              "      <td>@nationwideclass no, it's not behaving at all....</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467811372</td>\n",
              "      <td>Mon Apr 06 22:20:00 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>joy_wolf</td>\n",
              "      <td>@Kwesidei not the whole crew</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467811592</td>\n",
              "      <td>Mon Apr 06 22:20:03 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>mybirch</td>\n",
              "      <td>Need a hug</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467811594</td>\n",
              "      <td>Mon Apr 06 22:20:03 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>coZZ</td>\n",
              "      <td>@LOLTrish hey  long time no see! Yes.. Rains a...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467811795</td>\n",
              "      <td>Mon Apr 06 22:20:05 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>2Hood4Hollywood</td>\n",
              "      <td>@Tatiana_K nope they didn't have it</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812025</td>\n",
              "      <td>Mon Apr 06 22:20:09 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>mimismo</td>\n",
              "      <td>@twittera que me muera ?</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812416</td>\n",
              "      <td>Mon Apr 06 22:20:16 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>erinx3leannexo</td>\n",
              "      <td>spring break in plain city... it's snowing</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812579</td>\n",
              "      <td>Mon Apr 06 22:20:17 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>pardonlauren</td>\n",
              "      <td>I just re-pierced my ears</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812723</td>\n",
              "      <td>Mon Apr 06 22:20:19 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>TLeC</td>\n",
              "      <td>@caregiving I couldn't bear to watch it.  And ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812771</td>\n",
              "      <td>Mon Apr 06 22:20:19 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>robrobbierobert</td>\n",
              "      <td>@octolinz16 It it counts, idk why I did either...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812784</td>\n",
              "      <td>Mon Apr 06 22:20:20 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>bayofwolves</td>\n",
              "      <td>@smarrison i would've been the first, but i di...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812799</td>\n",
              "      <td>Mon Apr 06 22:20:20 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>HairByJess</td>\n",
              "      <td>@iamjazzyfizzle I wish I got to watch it with ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467812964</td>\n",
              "      <td>Mon Apr 06 22:20:22 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>lovesongwriter</td>\n",
              "      <td>Hollis' death scene will hurt me severely to w...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467813137</td>\n",
              "      <td>Mon Apr 06 22:20:25 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>armotley</td>\n",
              "      <td>about to file taxes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467813579</td>\n",
              "      <td>Mon Apr 06 22:20:31 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>starkissed</td>\n",
              "      <td>@LettyA ahh ive always wanted to see rent  lov...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467813782</td>\n",
              "      <td>Mon Apr 06 22:20:34 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>gi_gi_bee</td>\n",
              "      <td>@FakerPattyPattz Oh dear. Were you drinking ou...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467813985</td>\n",
              "      <td>Mon Apr 06 22:20:37 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>quanvu</td>\n",
              "      <td>@alydesigns i was out most of the day so didn'...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467813992</td>\n",
              "      <td>Mon Apr 06 22:20:38 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>swinspeedx</td>\n",
              "      <td>one of my friend called me, and asked to meet ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467814119</td>\n",
              "      <td>Mon Apr 06 22:20:40 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>cooliodoc</td>\n",
              "      <td>@angry_barista I baked you a cake but I ated it</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467814180</td>\n",
              "      <td>Mon Apr 06 22:20:40 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>viJILLante</td>\n",
              "      <td>this week is not going as i had hoped</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467814192</td>\n",
              "      <td>Mon Apr 06 22:20:41 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>Ljelli3166</td>\n",
              "      <td>blagh class at 8 tomorrow</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467814438</td>\n",
              "      <td>Mon Apr 06 22:20:44 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>ChicagoCubbie</td>\n",
              "      <td>I hate when I have to call and wake people up</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467814783</td>\n",
              "      <td>Mon Apr 06 22:20:50 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>KatieAngell</td>\n",
              "      <td>Just going to cry myself to sleep after watchi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467814883</td>\n",
              "      <td>Mon Apr 06 22:20:52 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>gagoo</td>\n",
              "      <td>im sad now  Miss.Lilly</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467815199</td>\n",
              "      <td>Mon Apr 06 22:20:56 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>abel209</td>\n",
              "      <td>ooooh.... LOL  that leslie.... and ok I won't ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467815753</td>\n",
              "      <td>Mon Apr 06 22:21:04 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>BaptisteTheFool</td>\n",
              "      <td>Meh... Almost Lover is the exception... this t...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467815923</td>\n",
              "      <td>Mon Apr 06 22:21:07 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>fatkat309</td>\n",
              "      <td>some1 hacked my account on aim  now i have to ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467815924</td>\n",
              "      <td>Mon Apr 06 22:21:07 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>EmCDL</td>\n",
              "      <td>@alielayus I want to go to promote GEAR AND GR...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467815988</td>\n",
              "      <td>Mon Apr 06 22:21:09 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>merisssa</td>\n",
              "      <td>thought sleeping in was an option tomorrow but...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467816149</td>\n",
              "      <td>Mon Apr 06 22:21:11 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>Pbearfox</td>\n",
              "      <td>@julieebaby awe i love you too!!!! 1 am here  ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467816665</td>\n",
              "      <td>Mon Apr 06 22:21:21 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>jsoo</td>\n",
              "      <td>@HumpNinja I cry my asian eyes to sleep at night</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467816749</td>\n",
              "      <td>Mon Apr 06 22:21:20 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>scarletletterm</td>\n",
              "      <td>ok I'm sick and spent an hour sitting in the s...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467817225</td>\n",
              "      <td>Mon Apr 06 22:21:27 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>crosland_12</td>\n",
              "      <td>@cocomix04 ill tell ya the story later  not a ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467817374</td>\n",
              "      <td>Mon Apr 06 22:21:30 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>ajaxpro</td>\n",
              "      <td>@MissXu sorry! bed time came here (GMT+1)   ht...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467817502</td>\n",
              "      <td>Mon Apr 06 22:21:32 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>Tmttq86</td>\n",
              "      <td>@fleurylis I don't either. Its depressing. I d...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467818007</td>\n",
              "      <td>Mon Apr 06 22:21:39 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>Anthony_Nguyen</td>\n",
              "      <td>Bed. Class 8-12. Work 12-3. Gym 3-5 or 6. Then...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467818020</td>\n",
              "      <td>Mon Apr 06 22:21:39 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>itsanimesh</td>\n",
              "      <td>really don't feel like getting up today... but...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467818481</td>\n",
              "      <td>Mon Apr 06 22:21:46 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>lionslamb</td>\n",
              "      <td>He's the reason for the teardrops on my guitar...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467818603</td>\n",
              "      <td>Mon Apr 06 22:21:49 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>kennypham</td>\n",
              "      <td>Sad, sad, sad. I don't know why but I hate thi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467818900</td>\n",
              "      <td>Mon Apr 06 22:21:53 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>DdubsShellBell</td>\n",
              "      <td>@JonathanRKnight Awww I soo wish I was there t...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467819022</td>\n",
              "      <td>Mon Apr 06 22:21:56 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>hpfangirl94</td>\n",
              "      <td>Falling asleep. Just heard about that Tracy gi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467819650</td>\n",
              "      <td>Mon Apr 06 22:22:05 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>antzpantz</td>\n",
              "      <td>@Viennah Yay! I'm happy for you with your job!...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467819712</td>\n",
              "      <td>Mon Apr 06 22:22:06 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>labrt2004</td>\n",
              "      <td>Just checked my user timeline on my blackberry...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467819812</td>\n",
              "      <td>Mon Apr 06 22:22:07 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>IrisJumbe</td>\n",
              "      <td>Oh man...was ironing @jeancjumbe's fave top to...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467820206</td>\n",
              "      <td>Mon Apr 06 22:22:13 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>peacoats</td>\n",
              "      <td>is strangely sad about LiLo and SamRo breaking...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1467820835</td>\n",
              "      <td>Mon Apr 06 22:22:25 PDT 2009</td>\n",
              "      <td>NO_QUERY</td>\n",
              "      <td>cyantist</td>\n",
              "      <td>@tea oh! i'm so sorry  i didn't think about th...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    polarity  ...                                               text\n",
              "0        0.0  ...  @switchfoot http://twitpic.com/2y1zl - Awww, t...\n",
              "1        0.0  ...  is upset that he can't update his Facebook by ...\n",
              "2        0.0  ...  @Kenichan I dived many times for the ball. Man...\n",
              "3        0.0  ...    my whole body feels itchy and like its on fire \n",
              "4        0.0  ...  @nationwideclass no, it's not behaving at all....\n",
              "5        0.0  ...                      @Kwesidei not the whole crew \n",
              "6        0.0  ...                                        Need a hug \n",
              "7        0.0  ...  @LOLTrish hey  long time no see! Yes.. Rains a...\n",
              "8        0.0  ...               @Tatiana_K nope they didn't have it \n",
              "9        0.0  ...                          @twittera que me muera ? \n",
              "10       0.0  ...        spring break in plain city... it's snowing \n",
              "11       0.0  ...                         I just re-pierced my ears \n",
              "12       0.0  ...  @caregiving I couldn't bear to watch it.  And ...\n",
              "13       0.0  ...  @octolinz16 It it counts, idk why I did either...\n",
              "14       0.0  ...  @smarrison i would've been the first, but i di...\n",
              "15       0.0  ...  @iamjazzyfizzle I wish I got to watch it with ...\n",
              "16       0.0  ...  Hollis' death scene will hurt me severely to w...\n",
              "17       0.0  ...                               about to file taxes \n",
              "18       0.0  ...  @LettyA ahh ive always wanted to see rent  lov...\n",
              "19       0.0  ...  @FakerPattyPattz Oh dear. Were you drinking ou...\n",
              "20       0.0  ...  @alydesigns i was out most of the day so didn'...\n",
              "21       0.0  ...  one of my friend called me, and asked to meet ...\n",
              "22       0.0  ...   @angry_barista I baked you a cake but I ated it \n",
              "23       0.0  ...             this week is not going as i had hoped \n",
              "24       0.0  ...                         blagh class at 8 tomorrow \n",
              "25       0.0  ...     I hate when I have to call and wake people up \n",
              "26       0.0  ...  Just going to cry myself to sleep after watchi...\n",
              "27       0.0  ...                             im sad now  Miss.Lilly\n",
              "28       0.0  ...  ooooh.... LOL  that leslie.... and ok I won't ...\n",
              "29       0.0  ...  Meh... Almost Lover is the exception... this t...\n",
              "30       0.0  ...  some1 hacked my account on aim  now i have to ...\n",
              "31       0.0  ...  @alielayus I want to go to promote GEAR AND GR...\n",
              "32       0.0  ...  thought sleeping in was an option tomorrow but...\n",
              "33       0.0  ...  @julieebaby awe i love you too!!!! 1 am here  ...\n",
              "34       0.0  ...  @HumpNinja I cry my asian eyes to sleep at night \n",
              "35       0.0  ...  ok I'm sick and spent an hour sitting in the s...\n",
              "36       0.0  ...  @cocomix04 ill tell ya the story later  not a ...\n",
              "37       0.0  ...  @MissXu sorry! bed time came here (GMT+1)   ht...\n",
              "38       0.0  ...  @fleurylis I don't either. Its depressing. I d...\n",
              "39       0.0  ...  Bed. Class 8-12. Work 12-3. Gym 3-5 or 6. Then...\n",
              "40       0.0  ...  really don't feel like getting up today... but...\n",
              "41       0.0  ...  He's the reason for the teardrops on my guitar...\n",
              "42       0.0  ...  Sad, sad, sad. I don't know why but I hate thi...\n",
              "43       0.0  ...  @JonathanRKnight Awww I soo wish I was there t...\n",
              "44       0.0  ...  Falling asleep. Just heard about that Tracy gi...\n",
              "45       0.0  ...  @Viennah Yay! I'm happy for you with your job!...\n",
              "46       0.0  ...  Just checked my user timeline on my blackberry...\n",
              "47       0.0  ...  Oh man...was ironing @jeancjumbe's fave top to...\n",
              "48       0.0  ...  is strangely sad about LiLo and SamRo breaking...\n",
              "49       0.0  ...  @tea oh! i'm so sorry  i didn't think about th...\n",
              "\n",
              "[50 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AW9d4yr9UE3O"
      },
      "source": [
        "Initial Findings\n",
        "\n",
        "- We need to apply a proper schema\n",
        "- The date column needs fixing\n",
        "- We need to extract twitter user names/handles (we'll extract it and call the output column `users_mentioned`)\n",
        "- We need to extract hashtags and replace them with the words from the hashtag (we'll extract it and call the output column `hashtags`)\n",
        "- We need to extract URLs, as our algorithm won't need that or use that (we'll simply remove it from the data)\n",
        "- The same goes for email-address\n",
        "- HTML does not appear properly unescaped, we're going to have to fix that (example: `&lt;3` and `s&amp;^t`)\n",
        "- Encoding seems to be 'broken' (example: `�����ߧ�ǿ�����ж�؜��� &lt;&lt;----I DID NOT KNOW I CUD or HOW TO DO ALL DAT ON MY PHONE TIL NOW. WOW..MY LIFE IS NOW COMPLETE. JK.`)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 480
        },
        "id": "PU9FSDkbUMia",
        "outputId": "85f11495-f621-468e-9500-100046b20a96"
      },
      "source": [
        "df = raw_training_data.select(\"polarity\").na.drop()\n",
        "print(f\"No of rows with Polarity: {df.count()} / {raw_training_data.count()}\")\n",
        "\n",
        "display(df.groupBy(\"polarity\").count().toPandas())\n",
        "sns.displot(df.toPandas());"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "No of rows with Polarity: 1600000 / 1600000\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>polarity</th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>4.0</td>\n",
              "      <td>800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>800000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   polarity   count\n",
              "0       4.0  800000\n",
              "1       0.0  800000"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 434x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kiH7klg1XND7"
      },
      "source": [
        "Store our raw data\n",
        "- keep the format CSV\n",
        "- partition the data by polarity, this will create 2 subfolders inside our output folder\n",
        "- repartition the data in 20 partitions: This will ensure that we have 20 smaller csv files per partition\n",
        "- As 498 rows is way too little for us to train a model on, we're going to disregard this dataset and focus on the Training Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ci_2d6KXWr5E"
      },
      "source": [
        "raw_training_data.repartition(20).write.partitionBy(\"polarity\").csv(OUTPUT_PATH, mode=\"overwrite\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d0MWjyELbWNR"
      },
      "source": [
        "### Data Wrangling"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lHdpTHe0csWJ"
      },
      "source": [
        "[notebook](https://nbviewer.jupyter.org/github/PacktPublishing/Mastering-Big-Data-Analytics-with-PySpark/blob/master/Section%206%20-%20Analyzing%20Big%20Data/6.3/data_wrangling.ipynb)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JygjkDBKaWNm"
      },
      "source": [
        "import html\n",
        "import pandas as pd\n",
        "from pyspark.sql import SparkSession\n",
        "from pyspark.sql import functions as f\n",
        "\n",
        "spark = SparkSession.builder.appName(\"DataCleaning\").getOrCreate()\n",
        "\n",
        "pd.options.display.max_columns = None\n",
        "pd.options.display.max_rows = 250\n",
        "pd.options.display.max_colwidth = 150\n",
        "\n",
        "schema = \"polarity FLOAT, id LONG, date_time TIMESTAMP, query STRING, user STRING, text STRING\"\n",
        "timestampformat = \"EEE MMM dd HH:mm:ss zzz yyyy\"\n",
        "\n",
        "IN_PATH = \"./data-sets/sentiment-140-training-data/RAW\"\n",
        "OUT_PATH = \"./data-sets/sentiment-140-training-data/CLEAN\"\n",
        "\n",
        "spark_reader = spark.read.schema(schema)\n",
        "\n",
        "url_regex = r\"((https?|ftp|file):\\/{2,3})+([-\\w+&@#/%=~|$?!:,.]*)|(www.)+([-\\w+&@#/%=~|$?!:,.]*)\"\n",
        "email_regex = r\"[\\w.-]+@[\\w.-]+\\.[a-zA-Z]{1,}\"\n",
        "user_regex = r\"(@\\w{1,15})\"\n",
        "hashtag_regex = \"(#\\w{1,})\"\n",
        "hashtag_replace_regex = \"#(\\w{1,})\"\n",
        "\n",
        "@f.udf\n",
        "def html_unescape(s: str):\n",
        "    if isinstance(s, str):\n",
        "        return html.unescape(s)\n",
        "    return s\n",
        "\n",
        "\n",
        "def clean_data(df):\n",
        "    df = (\n",
        "        df\n",
        "        .withColumn(\"original_text\", f.col(\"text\"))\n",
        "        .withColumn(\"text\", f.regexp_replace(f.col(\"text\"), url_regex, \"\"))\n",
        "        .withColumn(\"text\", f.regexp_replace(f.col(\"text\"), email_regex, \"\"))\n",
        "        .withColumn(\"text\", f.regexp_replace(f.col(\"text\"), user_regex, \"\"))\n",
        "        .withColumn(\"text\", f.regexp_replace(f.col(\"text\"), \"#\", \" \"))\n",
        "        .withColumn(\"text\", html_unescape(f.col(\"text\")))\n",
        "        .filter(\"text != ''\")\n",
        "    )\n",
        "    return df\n",
        "\n",
        "df_raw = spark_reader.csv(IN_PATH, timestampFormat=timestampformat) \n",
        "df_clean = clean_data(df_raw)\n",
        "\n",
        "df_clean.write.partitionBy(\"polarity\").parquet(OUT_PATH, mode=\"overwrite\")"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}