Big_Data_Analytics.ipynb

{
 "cells": [

  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "lh5NCoc8fsSO"
   },
   "outputs": [],
   "source": [
    "!apt-get install openjdk-8-jdk-headless -qq > /dev/null\n",
    "!wget -q https://downloads.apache.org/spark/spark-2.4.7/spark-2.4.7-bin-hadoop2.7.tgz\n",
    "!tar xf spark-2.4.7-bin-hadoop2.7.tgz\n",
    "!pip install -q findspark                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "Ow2mKzwMzezc"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ[\"JAVA_HOME\"] = \"/usr/lib/jvm/java-8-openjdk-amd64\"\n",
    "os.environ[\"SPARK_HOME\"] = \"/content/spark-2.4.7-bin-hadoop2.7\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "Mn7_TRf8zeDa"
   },
   "outputs": [],
   "source": [
    "## testing installation\n",
    "import findspark\n",
    "findspark.init()\n",
    "from pyspark.sql import SparkSession\n",
    "spark = SparkSession.builder.master(\"local[*]\").getOrCreate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "o1YUamHOphVn"
   },
   "source": [
    "# (1) Understanding Dataset:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VlWGxrRlphVo"
   },
   "source": [
    "### Loading the required packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 69
    },
    "id": "GLHeZDbdphVp",
    "outputId": "104b9ea6-e26d-4936-f363-8daae430228a"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "string"
      },
      "text/plain": [
       "\"import findspark\\nfindspark.init()\\nimport pyspark\\nfrom pyspark import SparkContext, SparkConf\\nfrom pyspark.sql import SparkSession\\nconf = pyspark.SparkConf().setAppName('appName').setMaster('local')\\nsc = pyspark.SparkContext(conf=conf)\\nspark = SparkSession(sc)\""
      ]
     },
     "execution_count": 61,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import findspark\n",
    "# findspark.init()\n",
    "# import pyspark\n",
    "# from pyspark import SparkContext, SparkConf\n",
    "# from pyspark.sql import SparkSession\n",
    "# conf = pyspark.SparkConf().setAppName('appName').setMaster('local')\n",
    "# sc = pyspark.SparkContext(conf=conf)\n",
    "# spark = SparkSession(sc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zQQoCplfphVq"
   },
   "source": [
    "### Loading the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "id": "itH3b0PKphVr"
   },
   "outputs": [],
   "source": [
    "df = spark.read.format(\"csv\").option('header','true').option(\"inferSchema\", \"true\").load(\"03-01-2018.csv\")\n",
    "df2 = spark.read.format(\"csv\").option('header','true').option(\"inferSchema\", \"true\").load(\"03-02-2018.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "dLzn6AzVphVs",
    "outputId": "4350b1bf-42eb-4829-80fb-067f0a5c00bc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "331112\n",
      "61534\n"
     ]
    }
   ],
   "source": [
    "print(df.count())\n",
    "print(df2.count())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "id": "nBPu77osphVu"
   },
   "outputs": [],
   "source": [
    "#Drop null values in the dataset\n",
    "df=df.na.drop()\n",
    "df2 = df2.na.drop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "gctDehTWphVv",
    "outputId": "91426c44-e871-47c8-a568-2fc9ee9a3b91"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "329266\n",
      "61485\n"
     ]
    }
   ],
   "source": [
    "print(df.count())\n",
    "print(df2.count())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "r3mhXKg0XLQb",
    "outputId": "19e876bc-5203-4103-d470-364efa706c66"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+----------+----------+----------+---------+-----------+--------+--------+------+\n",
      "|Dst Port|Protocol|       Timestamp|Flow Duration|Tot Fwd Pkts|Tot Bwd Pkts|TotLen Fwd Pkts|TotLen Bwd Pkts|Fwd Pkt Len Max|Fwd Pkt Len Min|Fwd Pkt Len Mean|Fwd Pkt Len Std|Bwd Pkt Len Max|Bwd Pkt Len Min|Bwd Pkt Len Mean|Bwd Pkt Len Std|Flow Byts/s|Flow Pkts/s|Flow IAT Mean|Flow IAT Std|Flow IAT Max|Flow IAT Min|Fwd IAT Tot|Fwd IAT Mean|Fwd IAT Std|Fwd IAT Max|Fwd IAT Min|Bwd IAT Tot|Bwd IAT Mean|Bwd IAT Std|Bwd IAT Max|Bwd IAT Min|Fwd PSH Flags|Bwd PSH Flags|Fwd URG Flags|Bwd URG Flags|Fwd Header Len|Bwd Header Len| Fwd Pkts/s|Bwd Pkts/s|Pkt Len Min|Pkt Len Max|Pkt Len Mean|Pkt Len Std|Pkt Len Var|FIN Flag Cnt|SYN Flag Cnt|RST Flag Cnt|PSH Flag Cnt|ACK Flag Cnt|URG Flag Cnt|CWE Flag Count|ECE Flag Cnt|Down/Up Ratio|Pkt Size Avg|Fwd Seg Size Avg|Bwd Seg Size Avg|Fwd Byts/b Avg|Fwd Pkts/b Avg|Fwd Blk Rate Avg|Bwd Byts/b Avg|Bwd Pkts/b Avg|Bwd Blk Rate Avg|Subflow Fwd Pkts|Subflow Fwd Byts|Subflow Bwd Pkts|Subflow Bwd Byts|Init Fwd Win Byts|Init Bwd Win Byts|Fwd Act Data Pkts|Fwd Seg Size Min|Active Mean|Active Std|Active Max|Active Min|Idle Mean|   Idle Std|Idle Max|Idle Min| Label|\n",
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+----------+----------+----------+---------+-----------+--------+--------+------+\n",
      "|       0|       0|01/03/2018 08:17|    115307855|           5|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0| 0.04336218|       2.88E7|      3.24E7|    61000000|      812396|  115000000|      2.88E7|     3.24E7|   61000000|     812396|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0| 0.04336218|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               5|               0|               0|               0|               -1|               -1|                0|               0|  1812348.0|       0.0|   1812348|   1812348|   5.67E7|6010057.622|61000000|52500000|Benign|\n",
      "|       0|       0|01/03/2018 08:20|     60997457|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788252|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788252|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|       0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|Benign|\n",
      "|      67|      17|01/03/2018 08:17|     61149019|           5|           0|           1500|              0|            300|            300|           300.0|            0.0|              0|              0|             0.0|            0.0|24.53023817|0.081767461|       1.53E7|      1.28E7|    32600000|     3530939|   61100000|      1.53E7|     1.28E7|   32600000|    3530939|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|            40|             0|0.081767461|       0.0|        300|        300|       300.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|       360.0|           300.0|             0.0|             0|             0|               0|             0|             0|               0|               5|            1500|               0|               0|               -1|               -1|                4|               8|  3530939.0|       0.0|   3530939|   3530939|   1.92E7|     1.25E7|32600000| 7999725|Benign|\n",
      "|       0|       0|01/03/2018 08:22|     60997555|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788199|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788199|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|       0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|Benign|\n",
      "|       0|       0|01/03/2018 08:24|     61997503|           3|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.048389046|        3.1E7|      4.24E7|    61000000|      999909|   62000000|       3.1E7|     4.24E7|   61000000|     999909|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.048389046|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               3|               0|               0|               0|               -1|               -1|                0|               0|   999909.0|       0.0|    999909|    999909|    6.1E7|        0.0|61000000|61000000|Benign|\n",
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+----------+----------+----------+---------+-----------+--------+--------+------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# first 5 entries\n",
    "df.show(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uOEW-jdcphVw"
   },
   "source": [
    "# (2) Big Data Query & Analysis using Spark SQL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "j2KOtGuVWCfr",
    "outputId": "2f8e5fa8-5c31-43bc-e66b-5264d1a58dee"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+------------------------+\n",
      "|count(DISTINCT Protocol)|\n",
      "+------------------------+\n",
      "|                       3|\n",
      "+------------------------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 1: Venkatesh BANDARUPALLI  ID:u2007302\n",
    "\n",
    "''' Query1: Counting the distinct classes in the Protocal column'''\n",
    "from pyspark.sql.functions import col, countDistinct\n",
    "df.select(countDistinct(\"Protocol\")).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "BGkV73r9Xbal",
    "outputId": "299c6cf5-4893-49ed-9d70-c1231c5fffaf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------+------+\n",
      "|        Label| count|\n",
      "+-------------+------+\n",
      "|Infilteration| 92634|\n",
      "|       Benign|236632|\n",
      "+-------------+------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 1: Venkatesh BANDARUPALLI  ID:u2007302\n",
    "\n",
    "''' Query2: Counting the Total appearaance of every class in the Label column'''\n",
    "df.select('Label').groupBy(\"Label\").count().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "rtA5p2fPphV0",
    "outputId": "a1fc3159-4630-4332-964e-6672c53362a6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+------+\n",
      "|Protocol| count|\n",
      "+--------+------+\n",
      "|       6|211065|\n",
      "|      17|111052|\n",
      "|       0|  7149|\n",
      "+--------+------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 2: Sairam CHINTHA          ID:u2007875\n",
    "\n",
    "''' Query1: Selecting the count of every Protocol '''\n",
    "df.select('Protocol').groupBy(\"Protocol\").count().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "PDPnq1-OphV1",
    "outputId": "456f7ed8-5916-4a96-8e19-baf848c8b193"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+------+\n",
      "|Protocol| count|\n",
      "+--------+------+\n",
      "|       6|146091|\n",
      "|      17| 84602|\n",
      "|       0|  5939|\n",
      "+--------+------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 2: Sairam CHINTHA          ID:u2007875\n",
    "\n",
    "''' Query2: Selecting the count of every Protocol with Label Benign'''\n",
    "df.filter(df[\"Label\"]==\"Benign\").groupBy(\"Protocol\").count().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "K-2DWBkEphV2",
    "outputId": "2563b1a3-9d73-40e2-a500-2a127d39ab9e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+-----+\n",
      "|Protocol|count|\n",
      "+--------+-----+\n",
      "|       6|64974|\n",
      "|      17|26450|\n",
      "|       0| 1210|\n",
      "+--------+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 3: Sreemu KOMATI  ID:u2008089\n",
    "\n",
    "''' Query1: Selecting the count of every Protocol with Label Infilteration'''\n",
    "df.filter(df[\"Label\"]==\"Infilteration\").groupBy(\"Protocol\").count().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "A0IZMCt_phV3",
    "outputId": "49fede6e-6547-4696-f46b-8cae95a2b99a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------+-----+\n",
      "|        Label|count|\n",
      "+-------------+-----+\n",
      "|Infilteration|26450|\n",
      "|       Benign|84602|\n",
      "+-------------+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 3: Sreemu KOMATI  ID:u2008089\n",
    "\n",
    "''' Query2: Filtering and count of every Label within 'Protocol 17'''\n",
    "df.filter(df[\"Protocol\"]==17).groupBy(\"Label\").count().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Hpu7bgAEphV4",
    "outputId": "b0d628ba-1d45-4944-89cc-66050d6685ee"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------+------+\n",
      "|        Label| count|\n",
      "+-------------+------+\n",
      "|Infilteration| 64974|\n",
      "|       Benign|146091|\n",
      "+-------------+------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 4: Lakshmi Rahul MUVVA     ID:u2042883\n",
    "\n",
    "''' Query1: Filtering and count of every Label within 'Protocol 6'''\n",
    "df.filter(df[\"Protocol\"]==6).groupBy(\"Label\").count().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "8_bsoM10phV5",
    "outputId": "59ffb172-a3be-49ae-80a6-02c16a625f53"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+----------+----------+----------+---------+--------+---------+---------+------+\n",
      "|Dst Port|Protocol|       Timestamp|Flow Duration|Tot Fwd Pkts|Tot Bwd Pkts|TotLen Fwd Pkts|TotLen Bwd Pkts|Fwd Pkt Len Max|Fwd Pkt Len Min|Fwd Pkt Len Mean|Fwd Pkt Len Std|Bwd Pkt Len Max|Bwd Pkt Len Min|Bwd Pkt Len Mean|Bwd Pkt Len Std|Flow Byts/s|Flow Pkts/s|Flow IAT Mean|Flow IAT Std|Flow IAT Max|Flow IAT Min|Fwd IAT Tot|Fwd IAT Mean|Fwd IAT Std|Fwd IAT Max|Fwd IAT Min|Bwd IAT Tot|Bwd IAT Mean|Bwd IAT Std|Bwd IAT Max|Bwd IAT Min|Fwd PSH Flags|Bwd PSH Flags|Fwd URG Flags|Bwd URG Flags|Fwd Header Len|Bwd Header Len| Fwd Pkts/s|Bwd Pkts/s|Pkt Len Min|Pkt Len Max|Pkt Len Mean|Pkt Len Std|Pkt Len Var|FIN Flag Cnt|SYN Flag Cnt|RST Flag Cnt|PSH Flag Cnt|ACK Flag Cnt|URG Flag Cnt|CWE Flag Count|ECE Flag Cnt|Down/Up Ratio|Pkt Size Avg|Fwd Seg Size Avg|Bwd Seg Size Avg|Fwd Byts/b Avg|Fwd Pkts/b Avg|Fwd Blk Rate Avg|Bwd Byts/b Avg|Bwd Pkts/b Avg|Bwd Blk Rate Avg|Subflow Fwd Pkts|Subflow Fwd Byts|Subflow Bwd Pkts|Subflow Bwd Byts|Init Fwd Win Byts|Init Bwd Win Byts|Fwd Act Data Pkts|Fwd Seg Size Min|Active Mean|Active Std|Active Max|Active Min|Idle Mean|Idle Std| Idle Max| Idle Min| Label|\n",
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+----------+----------+----------+---------+--------+---------+---------+------+\n",
      "|      23|       6|01/03/2018 03:16|    118785510|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0| 0.01683707|       1.19E8|         0.0|   119000000|   119000000|  119000000|      1.19E8|        0.0|  119000000|  119000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|            40|             0| 0.01683707|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           1|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|            43423|               -1|                0|              20|        0.0|       0.0|         0|         0|   1.19E8|     0.0|119000000|119000000|Benign|\n",
      "|     138|      17|01/03/2018 08:17|    119449184|           2|           0|            402|              0|            201|            201|           201.0|            0.0|              0|              0|             0.0|            0.0|3.365447854|0.016743522|       1.19E8|         0.0|   119000000|   119000000|  119000000|      1.19E8|        0.0|  119000000|  119000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|            16|             0|0.016743522|       0.0|        201|        201|       201.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|       301.5|           201.0|             0.0|             0|             0|               0|             0|             0|               0|               2|             402|               0|               0|               -1|               -1|                1|               8|        0.0|       0.0|         0|         0|   1.19E8|     0.0|119000000|119000000|Benign|\n",
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+----------+----------+----------+---------+--------+---------+---------+------+\n",
      "only showing top 2 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 4: Lakshmi Rahul MUVVA     ID:u2042883\n",
    "''' Query2: Sorting the data with 'Flow IAT Mean' and see=lecting first 2 rows'''\n",
    "df.sort('Flow IAT Mean', ascending=False).show(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Amr6gPxDphV6",
    "outputId": "4eafd342-2b01-4fc5-8e69-aa3d2434e9f9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+----------------+------+\n",
      "|Protocol|       Timestamp| Label|\n",
      "+--------+----------------+------+\n",
      "|       0|01/03/2018 08:17|Benign|\n",
      "|       0|01/03/2018 08:20|Benign|\n",
      "|      17|01/03/2018 08:17|Benign|\n",
      "|       0|01/03/2018 08:22|Benign|\n",
      "|       0|01/03/2018 08:24|Benign|\n",
      "|       0|01/03/2018 08:26|Benign|\n",
      "|      17|01/03/2018 08:23|Benign|\n",
      "|       0|01/03/2018 08:28|Benign|\n",
      "|       0|01/03/2018 08:30|Benign|\n",
      "|       0|01/03/2018 08:32|Benign|\n",
      "+--------+----------------+------+\n",
      "only showing top 10 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 5: Suhasini ALATI          ID:u1962019\n",
    "\n",
    "''' Query1: Selecting 'Protocol','Timestamp','Label' only'''\n",
    "df.select('Protocol','Timestamp','Label').show(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "i6OBgho6phV7",
    "outputId": "e0d0ec66-4f17-4fcc-85ec-f24967fb065d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------+------------+------+\n",
      "|Bwd Pkt Len Mean|Fwd IAT Mean| Label|\n",
      "+----------------+------------+------+\n",
      "|             0.0|      2.88E7|Benign|\n",
      "|             0.0|       6.1E7|Benign|\n",
      "|             0.0|      1.53E7|Benign|\n",
      "|             0.0|       6.1E7|Benign|\n",
      "|             0.0|       3.1E7|Benign|\n",
      "|             0.0|       3.1E7|Benign|\n",
      "|             0.0|      1.15E7|Benign|\n",
      "|             0.0|       6.1E7|Benign|\n",
      "|             0.0|       6.1E7|Benign|\n",
      "|             0.0|       6.1E7|Benign|\n",
      "+----------------+------------+------+\n",
      "only showing top 10 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Student 5: Suhasini ALATI          ID:u1962019\n",
    "\n",
    "''' Query2: Selecting columns 'Bwd Pkt Len Mean','Fwd IAT Mean',\"Label\"'''\n",
    "df.select('Bwd Pkt Len Mean','Fwd IAT Mean','Label').show(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JnXsRumqphV_"
   },
   "source": [
    "# (3) Advanced Analytics using PySpark"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NSWWcK5DphWA"
   },
   "source": [
    "### 3.1 Analyze and Interpret Big Data using PySpark"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AEmhe4JdYk4v"
   },
   "source": [
    "### Descriptive Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "eBrTfTWiYkAA",
    "outputId": "fd0e30eb-cc81-4f6f-a5d5-30412ba89cce"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DataFrame[summary: string, Dst Port: string, Protocol: string, Timestamp: string, Flow Duration: string, Tot Fwd Pkts: string, Tot Bwd Pkts: string, TotLen Fwd Pkts: string, TotLen Bwd Pkts: string, Fwd Pkt Len Max: string, Fwd Pkt Len Min: string, Fwd Pkt Len Mean: string, Fwd Pkt Len Std: string, Bwd Pkt Len Max: string, Bwd Pkt Len Min: string, Bwd Pkt Len Mean: string, Bwd Pkt Len Std: string, Flow Byts/s: string, Flow Pkts/s: string, Flow IAT Mean: string, Flow IAT Std: string, Flow IAT Max: string, Flow IAT Min: string, Fwd IAT Tot: string, Fwd IAT Mean: string, Fwd IAT Std: string, Fwd IAT Max: string, Fwd IAT Min: string, Bwd IAT Tot: string, Bwd IAT Mean: string, Bwd IAT Std: string, Bwd IAT Max: string, Bwd IAT Min: string, Fwd PSH Flags: string, Bwd PSH Flags: string, Fwd URG Flags: string, Bwd URG Flags: string, Fwd Header Len: string, Bwd Header Len: string, Fwd Pkts/s: string, Bwd Pkts/s: string, Pkt Len Min: string, Pkt Len Max: string, Pkt Len Mean: string, Pkt Len Std: string, Pkt Len Var: string, FIN Flag Cnt: string, SYN Flag Cnt: string, RST Flag Cnt: string, PSH Flag Cnt: string, ACK Flag Cnt: string, URG Flag Cnt: string, CWE Flag Count: string, ECE Flag Cnt: string, Down/Up Ratio: string, Pkt Size Avg: string, Fwd Seg Size Avg: string, Bwd Seg Size Avg: string, Fwd Byts/b Avg: string, Fwd Pkts/b Avg: string, Fwd Blk Rate Avg: string, Bwd Byts/b Avg: string, Bwd Pkts/b Avg: string, Bwd Blk Rate Avg: string, Subflow Fwd Pkts: string, Subflow Fwd Byts: string, Subflow Bwd Pkts: string, Subflow Bwd Byts: string, Init Fwd Win Byts: string, Init Bwd Win Byts: string, Fwd Act Data Pkts: string, Fwd Seg Size Min: string, Active Mean: string, Active Std: string, Active Max: string, Active Min: string, Idle Mean: string, Idle Std: string, Idle Max: string, Idle Min: string, Label: string]"
      ]
     },
     "execution_count": 59,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "descriptive_stats = df.describe()\n",
    "descriptive_stats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZaODDH6mYujR"
   },
   "source": [
    "### Correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "id": "jL6MrtwcphWA"
   },
   "outputs": [],
   "source": [
    "dfpd=df.toPandas()\n",
    "df2pd = df2.toPandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "uF6NRLmZphWB"
   },
   "outputs": [],
   "source": [
    "corr_feat=['Tot Fwd Pkts',\n",
    " 'Tot Bwd Pkts',\n",
    " 'TotLen Fwd Pkts',\n",
    " 'TotLen Bwd Pkts',\n",
    " 'Fwd Pkt Len Max',\n",
    " 'Fwd Pkt Len Min',\n",
    " 'Fwd Pkt Len Mean',\n",
    " 'Fwd Pkt Len Std',\n",
    " 'Bwd Pkt Len Max',\n",
    " 'Bwd Pkt Len Min',\n",
    " 'Bwd Pkt Len Mean',\n",
    " 'Bwd Pkt Len Std',]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 677
    },
    "id": "K_3RoXuyphWC",
    "outputId": "8b176856-ec23-4d58-895e-18121059acaf"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(10,10))\n",
    "corr_matrix=dfpd[corr_feat].corr()\n",
    "sns.heatmap(corr_matrix,annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 657
    },
    "id": "vIvM-4SsphWD",
    "outputId": "85ed712d-257e-474c-8502-4a36b3316915"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_feat1=['Flow Pkts/s','Flow IAT Mean', 'Flow IAT Std','Flow IAT Max','Flow IAT Min', 'Fwd IAT Tot',\n",
    "                'Fwd IAT Mean', 'Fwd IAT Std', 'Fwd IAT Max',\n",
    "                'Bwd IAT Std', 'Bwd IAT Max',]\n",
    "plt.figure(figsize=(10,10))\n",
    "corr_matrix=dfpd[corr_feat1].corr()\n",
    "sns.heatmap(corr_matrix,annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 429
    },
    "id": "KJFcVYXVphWE",
    "outputId": "c166ae0c-7207-487f-e520-f59483cddc25"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_feat2=['Active Mean',\n",
    " 'Active Std',\n",
    " 'Active Max',\n",
    " 'Active Min',\n",
    " 'Idle Mean',\n",
    " 'Idle Std',\n",
    " 'Idle Max',\n",
    " 'Idle Min',]\n",
    "plt.figure(figsize=(6,6))\n",
    "corr_matrix=dfpd[corr_feat2].corr()\n",
    "sns.heatmap(corr_matrix,annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 460
    },
    "id": "ny7NK2gcphWF",
    "outputId": "21a6b46e-b1e1-4b21-800d-9f3379f752d2"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_feat3=['Fwd Pkt Len Max',\n",
    " 'Fwd Pkt Len Min',\n",
    " 'Fwd Pkt Len Mean',\n",
    " 'Fwd Pkt Len Std',\n",
    " 'Bwd Pkt Len Max',\n",
    " 'Bwd Pkt Len Min',\n",
    " 'Bwd Pkt Len Mean',\n",
    " 'Bwd Pkt Len Std',]\n",
    "plt.figure(figsize=(6,6))\n",
    "corr_matrix=dfpd[corr_feat3].corr()\n",
    "sns.heatmap(corr_matrix,annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PeinNNC0ZWVM"
   },
   "source": [
    "### Visualizations "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "id": "LsI9bzvbUrta"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "frames = [dfpd, df2pd]\n",
    "df_pd = pd.concat(frames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 333
    },
    "id": "bUWrzrEXphWH",
    "outputId": "64e7d9d1-93a8-48c7-dea0-76f34b360202"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.countplot(df_pd.Label)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "CV7QPZAXP5nK",
    "outputId": "625c3db5-a128-4ad7-8918-cdddfb7dff92"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dst Port           int32\n",
       "Protocol           int32\n",
       "Timestamp         object\n",
       "Flow Duration      int32\n",
       "Tot Fwd Pkts       int32\n",
       "                  ...   \n",
       "Idle Mean        float64\n",
       "Idle Std         float64\n",
       "Idle Max           int32\n",
       "Idle Min           int32\n",
       "Label             object\n",
       "Length: 80, dtype: object"
      ]
     },
     "execution_count": 30,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfpd.info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AzU6TqLrphWI"
   },
   "source": [
    "#### Visualizing the protocol column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "r98w7HLiphWJ",
    "outputId": "7a7ce867-1da3-4c1b-8ada-d22264240052"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dfpd['Fwd Pkt Len Mean'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "arHw0oBLphWJ",
    "outputId": "fea2631f-c361-4a99-a465-d64fe3004640"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x254fd3d1a08>"
      ]
     },
     "execution_count": 34,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(dfpd.Protocol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "NmZst44mphWK",
    "outputId": "f2c27441-f9e3-4711-bb49-acf541f2ec96"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dfpd['Bwd Pkt Len Mean'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "yI4pHf_BphWK",
    "outputId": "e40689a7-d51c-4007-9de3-3c9f26577102"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dfpd['TotLen Fwd Pkts'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "R2qncHVgphWL",
    "outputId": "bdff0d4b-46f0-4808-f655-585e8d6f9cd2"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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h/sDvAi+XUl6q9+NmG7BXlFI+M0n7AzRXqvuXUmb7zwwmCuC3SymP79TYXMVva2nazvQ/A9fRzMx48STbv6yU8rcTtn8CcDJwTCnl+xFxJ80vCoDXWn75zNSv9EO8sta0IuJQmpnNttSme2hu+N1Fc6V9Xv1MbfvNiFgYEfsAv9ZGl2uBTwFfq9sAeInmX1jN1q3AyvG/5oiII9qoA5r9uoxmkqqJ2z+rzilNRBwYEW+jmcrzxRrUh9LMqiZ1hL/dNZmFdQgBmqvIFaWU7fXru4FTSynDEfEMzdX13QCllIci4nqameCeYUeI75JSyg01qG+O5h+/XgXcEhGbpxi3/lpEvFaX7wHOpJnCcmMN7BGaKS53tY5CM0wzsf3rEfEu4J76++Bl4PdoftH8UURspJkV7t5d7VOairPuSVICDoNIUgKGtSQlYFhLUgKGtSQlYFhLUgKGtSQlYFhLUgL/DyGmZc6B9roVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(dfpd['Bwd Pkt Len Mean'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "t85n-lryZh92"
   },
   "source": [
    "### Hypothesis Testing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hGmivxNtaOSu"
   },
   "source": [
    "H0: the sample has a Gaussian distribution. <br>\n",
    "H1: the sample does not have a Gaussian distributio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "nX0H2CjuZlYE",
    "outputId": "b931ad4b-f750-4e25-eb3e-4de0b37fb2d6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stat=0.006, p=0.000\n",
      "Probably not Gaussian\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/scipy/stats/morestats.py:1676: UserWarning: p-value may not be accurate for N > 5000.\n",
      "  warnings.warn(\"p-value may not be accurate for N > 5000.\")\n"
     ]
    }
   ],
   "source": [
    "# Example of the Shapiro-Wilk Normality Test\n",
    "from scipy.stats import shapiro\n",
    "data = df_pd['Tot Bwd Pkts']\n",
    "stat, p = shapiro(data)\n",
    "print('stat=%.3f, p=%.3f' % (stat, p))\n",
    "if p > 0.05:\n",
    "\tprint('Probably Gaussian')\n",
    "else:\n",
    "\tprint('Probably not Gaussian')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5vtEOmHophWM"
   },
   "source": [
    "#### Aggregating the mean of the 'Bwd IAT Mean' and grouping it by the Label column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "DaGD_LgnphWM",
    "outputId": "57f48f90-5cb6-4477-c1e4-12476718d790"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------+------------------+\n",
      "|        Label| avg(Bwd IAT Mean)|\n",
      "+-------------+------------------+\n",
      "|Infilteration|  888940.839159052|\n",
      "|       Benign|1019060.2277667207|\n",
      "+-------------+------------------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.groupby('Label').agg({'Bwd IAT Mean': 'mean'}).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "stFhyuPmphWN",
    "outputId": "62d9d8d4-d473-42fa-e076-8179976e84fa"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dfpd['Bwd IAT Mean'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "FbBAy_OpphWN"
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yibmopg8phWO"
   },
   "source": [
    "### 3.2 Design and Build a Machine Learning (ML) technique.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "qy17CjEUphWO"
   },
   "outputs": [],
   "source": [
    "from pyspark.ml import Pipeline\n",
    "from pyspark.ml.classification import RandomForestClassifier\n",
    "from pyspark.ml.feature import IndexToString, StringIndexer, VectorIndexer\n",
    "from pyspark.ml.evaluation import MulticlassClassificationEvaluator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "hzSJXThCphWP"
   },
   "outputs": [],
   "source": [
    "dfpd['Label'].replace('Infilteration', 0,inplace=True)\n",
    "dfpd['Label'].replace('Benign', 1,inplace=True)\n",
    "df=spark.createDataFrame(dfpd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ELNE5w8PphWP"
   },
   "outputs": [],
   "source": [
    "features=['Dst Port',\n",
    " 'Flow Duration',\n",
    " 'Tot Fwd Pkts',\n",
    " 'Tot Bwd Pkts',\n",
    " 'TotLen Fwd Pkts',\n",
    " 'TotLen Bwd Pkts',\n",
    " 'Fwd Pkt Len Max',\n",
    " 'Fwd Pkt Len Min',\n",
    " 'Fwd Pkt Len Mean',\n",
    " 'Fwd Pkt Len Std',\n",
    " 'Bwd Pkt Len Max',\n",
    " 'Bwd Pkt Len Min',\n",
    " 'Bwd Pkt Len Mean',\n",
    " 'Bwd Pkt Len Std',\n",
    " 'Flow Byts/s',\n",
    " 'Flow Pkts/s',\n",
    " 'Flow IAT Mean',\n",
    " 'Flow IAT Std',\n",
    " 'Flow IAT Max',\n",
    " 'Flow IAT Min',\n",
    " 'Fwd IAT Tot',\n",
    " 'Fwd IAT Mean',\n",
    " 'Fwd IAT Std',\n",
    " 'Fwd IAT Max',\n",
    " 'Fwd IAT Min',\n",
    " 'Bwd IAT Tot',\n",
    " 'Bwd IAT Mean',\n",
    " 'Bwd IAT Std',\n",
    " 'Bwd IAT Max',\n",
    " 'Bwd IAT Min',\n",
    " 'Fwd PSH Flags',\n",
    " 'Bwd PSH Flags',\n",
    " 'Fwd URG Flags',\n",
    " 'Bwd URG Flags',\n",
    " 'Fwd Header Len',\n",
    " 'Bwd Header Len',\n",
    " 'Fwd Pkts/s',\n",
    " 'Bwd Pkts/s',\n",
    " 'Pkt Len Min',\n",
    " 'Pkt Len Max',\n",
    " 'Pkt Len Mean',\n",
    " 'Pkt Len Std',\n",
    " 'Pkt Len Var',\n",
    " 'FIN Flag Cnt',\n",
    " 'SYN Flag Cnt',\n",
    " 'RST Flag Cnt',\n",
    " 'PSH Flag Cnt',\n",
    " 'ACK Flag Cnt',\n",
    " 'URG Flag Cnt',\n",
    " 'CWE Flag Count',\n",
    " 'ECE Flag Cnt',\n",
    " 'Down/Up Ratio',\n",
    " 'Pkt Size Avg',\n",
    " 'Fwd Seg Size Avg',\n",
    " 'Bwd Seg Size Avg',\n",
    " 'Fwd Byts/b Avg',\n",
    " 'Fwd Pkts/b Avg',\n",
    " 'Fwd Blk Rate Avg',\n",
    " 'Bwd Byts/b Avg',\n",
    " 'Bwd Pkts/b Avg',\n",
    " 'Bwd Blk Rate Avg',\n",
    " 'Subflow Fwd Pkts',\n",
    " 'Subflow Fwd Byts',\n",
    " 'Subflow Bwd Pkts',\n",
    " 'Subflow Bwd Byts',\n",
    " 'Init Fwd Win Byts',\n",
    " 'Init Bwd Win Byts',\n",
    " 'Fwd Act Data Pkts',\n",
    " 'Fwd Seg Size Min',\n",
    " 'Active Mean',\n",
    " 'Active Std',\n",
    " 'Active Max',\n",
    " 'Active Min',\n",
    " 'Idle Mean',\n",
    " 'Idle Std',\n",
    " 'Idle Max',\n",
    " 'Idle Min',]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ClqwPJEnphWQ",
    "outputId": "32d2363a-39a3-4281-9dc5-728321549aee"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+-----------+----------+----------+---------+-----------+--------+--------+-----+\n",
      "|Dst Port|Protocol|       Timestamp|Flow Duration|Tot Fwd Pkts|Tot Bwd Pkts|TotLen Fwd Pkts|TotLen Bwd Pkts|Fwd Pkt Len Max|Fwd Pkt Len Min|Fwd Pkt Len Mean|Fwd Pkt Len Std|Bwd Pkt Len Max|Bwd Pkt Len Min|Bwd Pkt Len Mean|Bwd Pkt Len Std|Flow Byts/s|Flow Pkts/s|Flow IAT Mean|Flow IAT Std|Flow IAT Max|Flow IAT Min|Fwd IAT Tot|Fwd IAT Mean|Fwd IAT Std|Fwd IAT Max|Fwd IAT Min|Bwd IAT Tot|Bwd IAT Mean|Bwd IAT Std|Bwd IAT Max|Bwd IAT Min|Fwd PSH Flags|Bwd PSH Flags|Fwd URG Flags|Bwd URG Flags|Fwd Header Len|Bwd Header Len| Fwd Pkts/s|Bwd Pkts/s|Pkt Len Min|Pkt Len Max|Pkt Len Mean|Pkt Len Std|Pkt Len Var|FIN Flag Cnt|SYN Flag Cnt|RST Flag Cnt|PSH Flag Cnt|ACK Flag Cnt|URG Flag Cnt|CWE Flag Count|ECE Flag Cnt|Down/Up Ratio|Pkt Size Avg|Fwd Seg Size Avg|Bwd Seg Size Avg|Fwd Byts/b Avg|Fwd Pkts/b Avg|Fwd Blk Rate Avg|Bwd Byts/b Avg|Bwd Pkts/b Avg|Bwd Blk Rate Avg|Subflow Fwd Pkts|Subflow Fwd Byts|Subflow Bwd Pkts|Subflow Bwd Byts|Init Fwd Win Byts|Init Bwd Win Byts|Fwd Act Data Pkts|Fwd Seg Size Min|Active Mean| Active Std|Active Max|Active Min|Idle Mean|   Idle Std|Idle Max|Idle Min|Label|\n",
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+-----------+----------+----------+---------+-----------+--------+--------+-----+\n",
      "|       0|       0|01/03/2018 08:17|    115307855|           5|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0| 0.04336218|       2.88E7|      3.24E7|    61000000|      812396|  115000000|      2.88E7|     3.24E7|   61000000|     812396|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0| 0.04336218|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               5|               0|               0|               0|               -1|               -1|                0|               0|  1812348.0|        0.0|   1812348|   1812348|   5.67E7|6010057.622|61000000|52500000|    1|\n",
      "|       0|       0|01/03/2018 08:20|     60997457|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788252|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788252|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|      67|      17|01/03/2018 08:17|     61149019|           5|           0|           1500|              0|            300|            300|           300.0|            0.0|              0|              0|             0.0|            0.0|24.53023817|0.081767461|       1.53E7|      1.28E7|    32600000|     3530939|   61100000|      1.53E7|     1.28E7|   32600000|    3530939|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|            40|             0|0.081767461|       0.0|        300|        300|       300.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|       360.0|           300.0|             0.0|             0|             0|               0|             0|             0|               0|               5|            1500|               0|               0|               -1|               -1|                4|               8|  3530939.0|        0.0|   3530939|   3530939|   1.92E7|     1.25E7|32600000| 7999725|    1|\n",
      "|       0|       0|01/03/2018 08:22|     60997555|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788199|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788199|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:24|     61997503|           3|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.048389046|        3.1E7|      4.24E7|    61000000|      999909|   62000000|       3.1E7|     4.24E7|   61000000|     999909|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.048389046|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               3|               0|               0|               0|               -1|               -1|                0|               0|   999909.0|        0.0|    999909|    999909|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:26|     61997503|           3|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.048389046|        3.1E7|      4.24E7|    61000000|     1000011|   62000000|       3.1E7|     4.24E7|   61000000|    1000011|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.048389046|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               3|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|      67|      17|01/03/2018 08:23|     92344822|           9|           0|           2700|              0|            300|            300|           300.0|            0.0|              0|              0|             0.0|            0.0|29.23823926|0.097460798|       1.15E7| 9387453.763|    31300000|     3999448|   92300000|      1.15E7|9387453.763|   31300000|    3999448|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|            72|             0|0.097460798|       0.0|        300|        300|       300.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0| 333.3333333|           300.0|             0.0|             0|             0|               0|             0|             0|               0|               9|            2700|               0|               0|               -1|               -1|                8|               8|  6678774.0| 2928068.37|   8749231|   4608317|   1.58E7|9685366.367|31300000| 7468536|    1|\n",
      "|       0|       0|01/03/2018 08:28|     60997542|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788206|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788206|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:30|     60997552|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788201|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788201|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:32|     60997614|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788168|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788168|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:34|     60997547|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788204|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788204|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|      67|      17|01/03/2018 08:29|     94865721|           9|           0|           2700|              0|            300|            300|           300.0|            0.0|              0|              0|             0.0|            0.0| 28.4612816|0.094870939|       1.19E7| 9759822.253|    32500000|     3984222|   94900000|      1.19E7|9759822.253|   32500000|    3984222|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|            72|             0|0.094870939|       0.0|        300|        300|       300.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0| 333.3333333|           300.0|             0.0|             0|             0|               0|             0|             0|               0|               9|            2700|               0|               0|               -1|               -1|                8|               8|  6504919.0|3477971.171|   8964216|   4045622|   1.64E7|9932251.778|32500000| 7984192|    1|\n",
      "|       0|       0|01/03/2018 08:36|     60997585|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788183|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788183|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:38|     61997523|           3|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0| 0.04838903|        3.1E7|      4.24E7|    61000000|      999976|   62000000|       3.1E7|     4.24E7|   61000000|     999976|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0| 0.04838903|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               3|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:40|     60997570|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788191|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788191|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|      67|      17|01/03/2018 08:36|     90870584|           9|           0|           2700|              0|            300|            300|           300.0|            0.0|              0|              0|             0.0|            0.0|29.71258554|0.099041952|       1.14E7| 9577239.497|    31500000|     3874536|   90900000|      1.14E7|9577239.497|   31500000|    3874536|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|            72|             0|0.099041952|       0.0|        300|        300|       300.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0| 333.3333333|           300.0|             0.0|             0|             0|               0|             0|             0|               0|               9|            2700|               0|               0|               -1|               -1|                8|               8|  5913068.0|2707650.458|   7827666|   3998470|   1.58E7|9721310.534|31500000| 7398661|    1|\n",
      "|       0|       0|01/03/2018 08:42|     62013106|           3|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.048376871|        3.1E7|      4.24E7|    61000000|      999954|   62000000|       3.1E7|     4.24E7|   61000000|     999954|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.048376871|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               3|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:44|     60997565|           2|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.032788194|        6.1E7|         0.0|    61000000|    61000000|   61000000|       6.1E7|        0.0|   61000000|   61000000|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.032788194|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               2|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:46|     61997502|           3|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.048389046|        3.1E7|      4.24E7|    61000000|      999949|   62000000|       3.1E7|     4.24E7|   61000000|     999949|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.048389046|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               3|               0|               0|               0|               -1|               -1|                0|               0|   999949.0|        0.0|    999949|    999949|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "|       0|       0|01/03/2018 08:48|     62013129|           3|           0|              0|              0|              0|              0|             0.0|            0.0|              0|              0|             0.0|            0.0|        0.0|0.048376853|        3.1E7|      4.24E7|    61000000|      999948|   62000000|       3.1E7|     4.24E7|   61000000|     999948|          0|         0.0|        0.0|          0|          0|            0|            0|            0|            0|             0|             0|0.048376853|       0.0|          0|          0|         0.0|        0.0|        0.0|           0|           0|           0|           0|           0|           0|             0|           0|            0|         0.0|             0.0|             0.0|             0|             0|               0|             0|             0|               0|               3|               0|               0|               0|               -1|               -1|                0|               0|        0.0|        0.0|         0|         0|    6.1E7|        0.0|61000000|61000000|    1|\n",
      "+--------+--------+----------------+-------------+------------+------------+---------------+---------------+---------------+---------------+----------------+---------------+---------------+---------------+----------------+---------------+-----------+-----------+-------------+------------+------------+------------+-----------+------------+-----------+-----------+-----------+-----------+------------+-----------+-----------+-----------+-------------+-------------+-------------+-------------+--------------+--------------+-----------+----------+-----------+-----------+------------+-----------+-----------+------------+------------+------------+------------+------------+------------+--------------+------------+-------------+------------+----------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+----------------+----------------+----------------+----------------+-----------------+-----------------+-----------------+----------------+-----------+-----------+----------+----------+---------+-----------+--------+--------+-----+\n",
      "only showing top 20 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from pyspark.sql.functions import col, isnan, when, trim\n",
    "def to_null(c):\n",
    "    return when(~(col(c).isNull() | isnan(col(c)) | (trim(col(c)) == \"\")), col(c))\n",
    "df.select([to_null(c).alias(c) for c in df.columns]).na.drop().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "fVV6u4O4phWS"
   },
   "outputs": [],
   "source": [
    "from pyspark.ml.classification import RandomForestClassifier\n",
    "from pyspark.ml.feature import VectorAssembler\n",
    "\n",
    "feature_list = []\n",
    "for col in df.columns:\n",
    "    if col == 'Label' or col=='Timestamp':\n",
    "        continue\n",
    "    else:\n",
    "        feature_list.append(col)\n",
    "assembler = VectorAssembler(inputCols=feature_list, outputCol=\"features\")\n",
    "transformed_data = assembler.transform(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "XkSV-p1JphWT"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "FA5uISYephWU",
    "outputId": "765d2c01-ef5b-4c4e-b0b8-9976e7bee9c1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-----+\n",
      "|Label|\n",
      "+-----+\n",
      "|    0|\n",
      "|    1|\n",
      "+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.select('Label').distinct().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "XpdZPXqcphWV"
   },
   "outputs": [],
   "source": [
    "(training_data, test_data) = transformed_data.randomSplit([0.8,0.2], seed =2020)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "l5nHmJUZphWW"
   },
   "source": [
    "### 1. Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "PcQzxbt0phWW"
   },
   "outputs": [],
   "source": [
    "from pyspark.ml.classification import LogisticRegression\n",
    "\n",
    "lr = LogisticRegression(featuresCol = 'features', labelCol = 'Label', maxIter=5)\n",
    "lrModel = lr.fit(training_data)\n",
    "lr_predictions = lrModel.transform(test_data)\n",
    "\n",
    "multi_evaluator = MulticlassClassificationEvaluator(labelCol = 'Label', metricName = 'accuracy')\n",
    "print('Logistic Regression Accuracy:', multi_evaluator.evaluate(lr_predictions))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pp-YP6hNphWY"
   },
   "source": [
    "### 2. Building a Random Forest Classifier to classfy the Label column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "jjcN7Oe5phWY"
   },
   "outputs": [],
   "source": [
    "rf = RandomForestClassifier(labelCol='Label',featuresCol='features',maxDepth=5)\n",
    "model = rf.fit(training_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "JhpHjlH9phWZ"
   },
   "outputs": [],
   "source": [
    "rf_predictions = model.transform(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "-2HPziJHphWa",
    "outputId": "4c6be253-c273-4228-ab24-1a1dc1e42eff"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forest classifier Accuracy: 0.7747038559168379\n"
     ]
    }
   ],
   "source": [
    "from pyspark.ml.evaluation import MulticlassClassificationEvaluator\n",
    "multi_evaluator = MulticlassClassificationEvaluator(labelCol = 'Label', metricName = 'accuracy')\n",
    "print('Random Forest classifier Accuracy:', multi_evaluator.evaluate(rf_predictions))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kTCHR7R7phWa"
   },
   "source": [
    "### 3. Building a Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "BJdaLr5EphWb",
    "outputId": "86da6013-849a-45f0-c2b6-a6682726520f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Accuracy: 0.767390910189774\n"
     ]
    }
   ],
   "source": [
    "from pyspark.ml.classification import DecisionTreeClassifier\n",
    "\n",
    "dt = DecisionTreeClassifier(featuresCol = 'features', labelCol = 'Label', maxDepth = 3)\n",
    "dtModel = dt.fit(training_data)\n",
    "dt_predictions = dtModel.transform(test_data)\n",
    "multi_evaluator = MulticlassClassificationEvaluator(labelCol = 'Label', metricName = 'accuracy')\n",
    "print('Decision Tree Accuracy:', multi_evaluator.evaluate(dt_predictions))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bOM8eArSphWb"
   },
   "source": [
    "### 4.Gradient-Boosted Tree Classifier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "hh_j6x4GphWc",
    "outputId": "4b36f7e6-d4cf-4cc0-fb54-872621f1a56b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gradient-boosted Trees Accuracy: 0.7816692856279464\n"
     ]
    }
   ],
   "source": [
    "from pyspark.ml.classification import GBTClassifier\n",
    "gb = GBTClassifier(labelCol = 'Label', featuresCol = 'features')\n",
    "gbModel = gb.fit(training_data)\n",
    "gb_predictions = gbModel.transform(test_data)\n",
    "from pyspark.ml.evaluation import MulticlassClassificationEvaluator\n",
    "multi_evaluator = MulticlassClassificationEvaluator(labelCol = 'Label', metricName = 'accuracy')\n",
    "print('Gradient-boosted Trees Accuracy:', multi_evaluator.evaluate(gb_predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "YMXN2QjsphWc"
   },
   "outputs": [],
   "source": []
  }
 ],
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