RandomParallelComparison.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6653307d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql import SparkSession, Window\n",
    "from pyspark.sql.functions import col, udf, array, min as smin, lit, count, isnan, when, sum as spark_sum, rand\n",
    "from pyspark.sql.types import IntegerType, FloatType\n",
    "from pyspark.ml.feature import MinMaxScaler, VectorAssembler\n",
    "from pyspark.ml.clustering import KMeans\n",
    "from pyspark.ml.evaluation import ClusteringEvaluator\n",
    "from pyspark.sql.functions import col, expr\n",
    "from pyspark.sql.functions import explode\n",
    "from sklearn.datasets import fetch_kddcup99\n",
    "from sklearn.metrics.pairwise import euclidean_distances\n",
    "\n",
    "\n",
    "import time\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from sklearn.datasets import make_blobs\n",
    "from pyspark.sql import DataFrame\n",
    "from pyspark.sql.types import StructType, StructField, DoubleType\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "09458350",
   "metadata": {},
   "outputs": [],
   "source": [
    "def initiate_session(ncores, spark=spark):\n",
    "    \n",
    "    spark.stop()\n",
    "\n",
    "    spark = SparkSession.builder \\\n",
    "        .config(\"spark.executor.cores\", str(ncores))\\\n",
    "        .master(\"spark://10.67.22.21:7077\")\\\n",
    "        .appName(\"k-meaner\")\\\n",
    "        .config('spark.jars.packages', 'org.apache.hadoop:hadoop-common:3.2.0')\\\n",
    "        .config('spark.jars.packages', 'org.apache.hadoop:hadoop-aws:3.2.0')\\\n",
    "        .config('spark.jars.packages', 'com.amazonaws:aws-java-sdk:1.11.375')\\\n",
    "        .config(\"spark.executor.memory\", \"4096m\")\\\n",
    "        .config(\"spark.sql.execution.arrow.pyspark.enabled\", \"true\")\\\n",
    "        .config(\"spark.sql.execution.arrow.pyspark.fallback.enabled\", \"false\")\\\n",
    "        .config('spark.hadoop.fs.s3a.aws.credentials.provider', 'org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider')\\\n",
    "        .config('spark.hadoop.fs.s3a.access.key', '79f100fb66c34d338833171110cb12fe')\\\n",
    "        .config('spark.hadoop.fs.s3a.secret.key', '--------------------------------')\\\n",
    "        .config('spark.hadoop.fs.s3a.endpoint', 'https://cloud-areapd.pd.infn.it:5210')\\\n",
    "        .config(\"spark.hadoop.fs.s3a.impl\", \"org.apache.hadoop.fs.s3a.S3AFileSystem\") \\\n",
    "        .config(\"spark.hadoop.fs.s3a.metadatastore.impl\", \"org.apache.hadoop.fs.s3a.s3guard.NullMetadataStore\") \\\n",
    "        .config(\"spark.hadoop.fs.s3a.path.style.access\", \"true\") \\\n",
    "        .config(\"spark.hadoop.fs.s3a.connection.ssl.enabled\",\"false\") \\\n",
    "        .config(\"com.amazonaws.sdk.disableCertChecking\",\"true\") \\\n",
    "        .getOrCreate()\n",
    "\n",
    "    sc = spark.sparkContext\n",
    "    sc.setLogLevel(\"ERROR\")\n",
    "    \n",
    "    return spark, sc\n",
    "\n",
    "ncores = 4\n",
    "# 4 cores\n",
    "spark, sc = initiate_session(ncores=ncores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e17d0aba",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "            <div>\n",
       "                <p><b>SparkSession - in-memory</b></p>\n",
       "                \n",
       "        <div>\n",
       "            <p><b>SparkContext</b></p>\n",
       "\n",
       "            <p><a href=\"http://master:4040\">Spark UI</a></p>\n",
       "\n",
       "            <dl>\n",
       "              <dt>Version</dt>\n",
       "                <dd><code>v3.4.1</code></dd>\n",
       "              <dt>Master</dt>\n",
       "                <dd><code>spark://10.67.22.21:7077</code></dd>\n",
       "              <dt>AppName</dt>\n",
       "                <dd><code>k-meaner</code></dd>\n",
       "            </dl>\n",
       "        </div>\n",
       "        \n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "<pyspark.sql.session.SparkSession at 0x7f7553a599f0>"
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     "execution_count": 3,
     "metadata": {},
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   "source": [
    "spark"
   ]
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  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "06982c79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <div>\n",
       "            <p><b>SparkContext</b></p>\n",
       "\n",
       "            <p><a href=\"http://master:4040\">Spark UI</a></p>\n",
       "\n",
       "            <dl>\n",
       "              <dt>Version</dt>\n",
       "                <dd><code>v3.4.1</code></dd>\n",
       "              <dt>Master</dt>\n",
       "                <dd><code>spark://10.67.22.21:7077</code></dd>\n",
       "              <dt>AppName</dt>\n",
       "                <dd><code>k-meaner</code></dd>\n",
       "            </dl>\n",
       "        </div>\n",
       "        "
      ],
      "text/plain": [
       "<SparkContext master=spark://10.67.22.21:7077 appName=k-meaner>"
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     "execution_count": 4,
     "metadata": {},
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   "source": [
    "sc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6756273d",
   "metadata": {},
   "source": [
    "# BEST RANDOM KMEANS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bad94dd5",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# load data\n",
    "kdd = spark.createDataFrame(pd.read_csv(\"./data.csv\"))\n",
    "\n",
    "# List of columns to be ignored\n",
    "\n",
    "ignored_cols = [\"labels\", \"centr\", \"cost\", \"w\"]\n",
    "\n",
    "ncols = len([c for c in kdd.columns if c not in ignored_cols]) #n° of columns ccontaining the actual data\n",
    "\n",
    "#kdd.printSchema()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "500e690c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%writefile kmeans_random.py\n",
    "\n",
    "# Function to calculate Euclidean distance between two points x and y\n",
    "def euclidean_distance(x, y):\n",
    "    return np.linalg.norm(np.array(x) - np.array(y))\n",
    "\n",
    "# Function to find the index of the minimum value in a list x\n",
    "def argmin(x):\n",
    "    return x.index(min(x))\n",
    "\n",
    "# Function to initialize K-Means with random centers\n",
    "def random_choice_init(data, k):\n",
    "    # Select relevant columns and take k random samples\n",
    "    three_dim_array = np.array(data.select(array([c for c in data.columns if c not in ignored_cols])).rdd.takeSample(False, k))\n",
    "    final = three_dim_array.reshape(three_dim_array.shape[0], -1)\n",
    "    return final\n",
    "\n",
    "# Main K-Means function\n",
    "def kmeans(data, centers, max_iter=100, perc=0.999999, return_cost=False):\n",
    "    count = 0\n",
    "\n",
    "    # Get column names\n",
    "    cols = data.columns\n",
    "\n",
    "    # Initialize cost history \n",
    "    cost = [float(\"inf\")]\n",
    "\n",
    "    # Main K-Means loop\n",
    "    while count <= max_iter:\n",
    "        print(\"Iteration\", count)\n",
    "\n",
    "        # Define a UDF to find the index of the nearest center for each row\n",
    "        argmin_distance_udf = udf(lambda row: (argmin([euclidean_distance(row, c) for c in centers])), IntegerType())\n",
    "\n",
    "        # Calculate the \"centr\" column based on the nearest center\n",
    "        data = data.withColumn(\"centr\", argmin_distance_udf(array([c for c in cols if c not in ignored_cols])))\n",
    "\n",
    "        # Update the centers based on the assigned clusters\n",
    "        \n",
    "        centers = np.array(data.groupBy(\"centr\").mean().select(*[col(\"avg(\"+c+\")\") for c in data.columns if c not in ignored_cols+['avg(centr)']]).collect())\n",
    "\n",
    "        # Calculate the cost value per element, then sum\n",
    "        get_cost = udf(lambda row: str(min([euclidean_distance(row, cen)**2 for cen in centers])))\n",
    "\n",
    "        data = data.withColumn(\"cost\", get_cost(array([c for c in cols if c not in ignored_cols])).cast(\"double\"))\n",
    "\n",
    "        # Calculate the new cost and add it to the cost history\n",
    "        finalcost = data.select(\"cost\").groupBy().sum().collect()[0][0]\n",
    "        cost.append(finalcost)\n",
    "        \n",
    "        print(\"Cost function values\", cost[count])\n",
    "\n",
    "        # Increment the iteration count\n",
    "        count += 1\n",
    "\n",
    "        # Break if the cost change ratio is below the specified threshold\n",
    "        if cost[-1] / cost[-2] > perc:\n",
    "            break\n",
    "\n",
    "    # Return the result based on whether cost history is requested\n",
    "    if return_cost:\n",
    "        return data, centers, cost[1:]\n",
    "    else:\n",
    "        return data, centers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "70ff55e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def avg_cost_time_results(k, data, partitions, iterations, func, L=None):\n",
    "    \n",
    "    total_cost_history = np.zeros(len(partitions))\n",
    "    total_time = np.zeros(len(partitions))\n",
    "    \n",
    "    for part in partitions:\n",
    "        part_cost = list()\n",
    "        part_time = list()\n",
    "        for i in range(iterations):\n",
    "            start_time = time.time()\n",
    "            data = data.repartition(int(part))\n",
    "            data = data.persist()\n",
    "            r_centr = func(data, k)\n",
    "            result, final_centroids, cost_history = kmeans(data, r_centr, max_iter=15, return_cost=True)\n",
    "            part_cost.append(np.array(cost_history))\n",
    "            elapsed_time = time.time() - start_time\n",
    "            part_time.append(elapsed_time)\n",
    "            \n",
    "\n",
    "    return part_cost, part_time\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1abe0d18",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8956989.601979231\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8904482.37037084\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8741533.989231333\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8369312.1582704615\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7863975.837079446\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7773424.987593739\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7717491.58630231\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7701608.582284784\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7688567.047513449\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7678105.640332552\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7676828.976348989\n",
      "Iteration 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7675950.080892273\n",
      "Iteration 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7674136.820340304\n",
      "Iteration 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7661905.6902870545\n",
      "Iteration 15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7573860.35516868\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9563243.519742493\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8996214.250479668\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8617311.054963231\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8568004.93780889\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8553443.065381907\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8525965.24185946\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8444168.006371953\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8345357.289155557\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8273515.78803671\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8205782.97167193\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8195205.125978409\n",
      "Iteration 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8193326.7222835515\n",
      "Iteration 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8191924.440072211\n",
      "Iteration 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8177063.380050134\n",
      "Iteration 15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8045592.307430963\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9111202.411372723\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8204921.154740699\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7775696.281781221\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7767470.175999577\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7765241.621751914\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7699411.5570903905\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7644711.069304806\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7641041.469664875\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7640407.148759229\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7640310.23842993\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7640294.516146548\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9475870.508118251\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9204758.924747562\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8987566.382945638\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8904379.978657655\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8897151.654044995\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8896819.255504409\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8895000.923754018\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8893157.284565883\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8887329.0494671\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8881286.474310867\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8819154.325296499\n",
      "Iteration 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8418507.323541183\n",
      "Iteration 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8355174.990636323\n",
      "Iteration 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8351539.250434652\n",
      "Iteration 15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8350955.663757862\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9514193.003628926\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9201954.581230685\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9118455.606488515\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9061629.3041859\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8962997.120824702\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8694333.959504895\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8426999.118036455\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8120365.694959196\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8023970.34040447\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7915238.359605302\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7436085.0626894\n",
      "Iteration 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7361181.485223055\n",
      "Iteration 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7298307.17761414\n",
      "Iteration 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7289855.846724051\n",
      "Iteration 15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 1400:===========================================>          (13 + 3) / 16]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7289009.739898003\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "ncores = 3\n",
    "spark, sc = initiate_session(ncores=ncores, spark=spark)\n",
    "\n",
    "data = spark.createDataFrame(pd.read_csv(\"./data.csv\"))\n",
    "k = 23 # length of unique labels\n",
    "partitions = np.array([16])\n",
    "iterations = 5\n",
    "\n",
    "\n",
    "part_cost, part_time = avg_cost_time_results(k=k, data=data, partitions=partitions, iterations=iterations,\n",
    "                                                   func=random_choice_init)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "df8257c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def pad_arrays(arrays):\n",
    "    max_length = max(len(arr) for arr in arrays)\n",
    "    padded_arrays = []\n",
    "    for arr in arrays:\n",
    "        pad_length = max_length - len(arr)\n",
    "        padded_arr = np.pad(arr, (0, pad_length), mode='constant')\n",
    "        padded_arrays.append(padded_arr)\n",
    "    return padded_arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "69139c79",
   "metadata": {},
   "outputs": [],
   "source": [
    "part_cost = pad_arrays(part_cost)\n",
    "\n",
    "part_time = np.array(part_time)\n",
    "part_cost = np.array(part_cost)\n",
    "\n",
    "# Mask padded values\n",
    "mask = (part_cost != 0)\n",
    "\n",
    "# Calculate average and standard deviation over columns considering non-padded elements only\n",
    "avg_cost = np.sum(part_cost * mask, axis=0) / np.sum(mask, axis=0)\n",
    "std_cost = np.sqrt(np.sum(((part_cost - avg_cost) ** 2) * mask, axis=0) / np.sum(mask, axis=0))\n",
    "\n",
    "avg_time = np.mean(part_time)\n",
    "std_time = np.std(part_time)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95b38b2c",
   "metadata": {},
   "source": [
    "# BEST PARALLEL KMEANS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "db8e9703",
   "metadata": {},
   "outputs": [],
   "source": [
    "    \n",
    "def kmeans_Lloyd(X, centroids, k, max_iters=100, tol=1e-7):\n",
    "    \n",
    "    \"\"\" Run the sequential LLoyd algorithm given data X, centroids and k number of clusters.\"\"\"\n",
    "\n",
    "    costs = []\n",
    "\n",
    "    for _ in range(max_iters):\n",
    "        # Step 1: Assign each data point to the nearest centroid\n",
    "        distances = euclidean_distances(X, centroids)\n",
    "        labels = np.argmin(distances, axis=1)\n",
    "        \n",
    "        # Step 2: Update centroids based on the assigned points\n",
    "        new_centroids = np.array([X[labels == i].mean(axis=0) for i in range(k)])\n",
    "        \n",
    "        # Calculate the cost function (sum of squared distances to centroids)\n",
    "        cost = np.sum(np.min(distances, axis=1))\n",
    "        costs.append(cost)\n",
    "\n",
    "        \n",
    "        # Check for convergence\n",
    "        if np.linalg.norm(new_centroids - centroids) <= tol:\n",
    "            break\n",
    "        \n",
    "        centroids = new_centroids\n",
    "    \n",
    "    return centroids, labels, costs\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "db5117b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def kmeans_Lloyd(X, centroids, k, max_iters=100, tol=1e-7):\n",
    "    \n",
    "    \"\"\" Run the sequential LLoyd algorithm given data X, centroids and k number of clusters.\"\"\"\n",
    "\n",
    "    costs = []\n",
    "\n",
    "    for _ in range(max_iters):\n",
    "        # Step 1: Assign each data point to the nearest centroid\n",
    "        distances = euclidean_distances(X, centroids)\n",
    "        labels = np.argmin(distances, axis=1)\n",
    "        \n",
    "        # Step 2: Update centroids based on the assigned points\n",
    "        new_centroids = np.array([X[labels == i].mean(axis=0) for i in range(k)])\n",
    "        \n",
    "        # Calculate the cost function (sum of squared distances to centroids)\n",
    "        cost = np.sum(np.min(distances, axis=1))\n",
    "        costs.append(cost)\n",
    "\n",
    "        \n",
    "        # Check for convergence\n",
    "        if np.linalg.norm(new_centroids - centroids) <= tol:\n",
    "            break\n",
    "        \n",
    "        centroids = new_centroids\n",
    "    \n",
    "    return centroids, labels, costs\n",
    "\n",
    "\n",
    "\n",
    "def kmeans_ll(data, k, L=1): \n",
    "    \n",
    "    \"\"\" || kmeans initialization of k centroids elements. X is the data, L the oversampling factor.\"\"\"\n",
    "    \n",
    "    \n",
    "    cols = data.columns\n",
    "    n_samples, n_features = data.count(), len(data.columns)\n",
    "    centroids = np.zeros((1, n_features))\n",
    "    \n",
    "    # Step 1: Choose one random point as the first centroid\n",
    "    three_dim_array = np.array(data.select(array([c for c in data.columns if c not in ignored_cols])).rdd.takeSample(False, 1))\n",
    "    centroids[0] = three_dim_array.reshape(three_dim_array.shape[0], -1)\n",
    "    \n",
    "    # Define a UDF to find psi\n",
    "    # Calculate the distance using the UDF and collect the result\n",
    "    distance_udf = udf(lambda row: ((float(euclidean_distance(row, centroids[0])))), DoubleType())\n",
    "\n",
    "    distance = data.withColumn(\"distance\", distance_udf(array([c for c in cols if c not in ignored_cols])))\n",
    "\n",
    "    # Sum the distances\n",
    "    psi = distance.select(spark_sum(col(\"distance\"))).collect()[0][0]\n",
    "    #print(psi)\n",
    "\n",
    "    \n",
    "\n",
    "    # Calculate psi\n",
    "    #psi = spark_sum(distance_udf(array([c for c in cols if c not in ignored_cols])).collect())\n",
    "\n",
    "    \n",
    "    for j in range(1, int(np.log(psi))):\n",
    "\n",
    "        # Step 2: Compute distances from each point to the nearest centroid and define probabilities\n",
    "        min_distance_udf = udf(lambda row: (float(min([euclidean_distance(row, c) for c in centroids]))), DoubleType())\n",
    "        data = data.withColumn(\"probs\", min_distance_udf(array([c for c in cols if c not in ignored_cols])))\n",
    "        # Calculate the sum of the \"probs\" column\n",
    "        total_sum = data.select(spark_sum(col(\"probs\"))).collect()[0][0]\n",
    "        # Normalize the \"probs\" column by dividing each row's value by the total sum\n",
    "        data = data.withColumn(\"probs\", col(\"probs\")*L / total_sum)\n",
    "        \n",
    "        # Sample and add centroids\n",
    "        # Generate a random column for filtering\n",
    "        data = data.withColumn(\"rand_col\", rand())\n",
    "\n",
    "        # Filter and select the rows where 'rand_col' is less than 'probs' to get n_samples\n",
    "        selected_data = data.filter(col(\"rand_col\") < col(\"probs\")).select([col(c) for c in data.columns if c not in ['rand_col','centr','cost','probs']]).collect()\n",
    "\n",
    "        #print(\"centroids\", centroids)\n",
    "        #print(\"selected_data\", selected_data)\n",
    "        if selected_data != []:\n",
    "            centroids = np.concatenate((centroids, selected_data), axis=0)\n",
    "                \n",
    "    if len(centroids) > k:\n",
    "                \n",
    "        #A SORT OF K MEANS ++ INITIALIAZATION FOR Lloyd ITERATIONS ON CENTROIDS       \n",
    "        cc = np.copy(centroids)\n",
    "        p_centroids = np.zeros((k, n_features))\n",
    "\n",
    "        for j in range(0, k):\n",
    "            \n",
    "            # Define weights\n",
    "            w = np.zeros(len(cc))\n",
    "\n",
    "            # Create new column with the index of the nearest center for each row\n",
    "            argmin_distance_udf = udf(lambda row: (argmin([euclidean_distance(row, c) for c in cc])), IntegerType())\n",
    "            data = data.withColumn(\"index\", argmin_distance_udf(array([c for c in cols if c not in ignored_cols])))\n",
    "\n",
    "            #w = np.array(data.groupBy(\"index\").count().collect())\n",
    "            # Group by 'centroid_inddex' and count the occurrences, renaming the count column\n",
    "            centroid_counts = data.groupBy(\"index\").count()\n",
    "            # Order by ascending index value\n",
    "            centroid_counts = centroid_counts.sort(\"index\")\n",
    "            # Calculate the sum of counts\n",
    "            total_count = centroid_counts.select(spark_sum(col(\"count\"))).collect()[0][0]\n",
    "            # Normalize the \"probs\" column by dividing each row's value by the total sum\n",
    "            renormalized_counts = centroid_counts.withColumn(\"count\", col(\"count\")/ total_count).select(col(\"count\")).collect()\n",
    "            probs = np.array(renormalized_counts).flatten()\n",
    "\n",
    "            next_centroid_idx = np.random.choice(len(probs), p=probs)\n",
    "            p_centroids[j] = cc[next_centroid_idx]\n",
    "            cc = np.delete(cc, next_centroid_idx, axis=0)\n",
    "\n",
    "        #print(len(centroids), len(p_centroids))\n",
    "        # K MEANS Lloyd ITERATIONS ON CENTROIDS\n",
    "\n",
    "        final_centroids, __, _ = kmeans_Lloyd(centroids, p_centroids, k)\n",
    "    else:\n",
    "        final_centroids = centroids\n",
    "        \n",
    "    return final_centroids\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "31df6a40",
   "metadata": {},
   "outputs": [],
   "source": [
    "ncores = 3\n",
    "# 4 cores\n",
    "spark, sc = initiate_session(ncores=ncores, spark=spark)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "60dcccb8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6691059.31377656\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6446053.655031749\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6196412.060850556\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6145320.231456628\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6129917.182387537\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6104366.078180213\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6053710.209627607\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6051487.193159205\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6051355.549449811\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6050553.598292772\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6045812.076494363\n",
      "Iteration 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 6012890.602163393\n",
      "Iteration 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 5668722.367608393\n",
      "Iteration 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 5602030.653939595\n",
      "Iteration 15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 5599548.300071866\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8280102.6156306\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7846784.87922548\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7638784.229894099\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7596767.967821854\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7595641.916635383\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7595560.884856804\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7595547.215405993\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 9008150.830829425\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8819104.076554883\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8763800.537609184\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8727773.490051398\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8716123.403448084\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8707196.544812078\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8703779.7110516\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8702159.72768776\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8701107.623932654\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8695147.249352677\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8692869.973045\n",
      "Iteration 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8692038.927889377\n",
      "Iteration 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8690002.758973341\n",
      "Iteration 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8666259.8081417\n",
      "Iteration 15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8524902.392168734\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8373762.116951124\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7509842.330537876\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7146342.238411474\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7126499.734027796\n",
      "Iteration 5\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7121094.783562107\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7119004.581470822\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7117237.581816428\n",
      "Iteration 8\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7115395.618716272\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7114769.977197345\n",
      "Iteration 10\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7114367.357594196\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7114075.820098166\n",
      "Iteration 12\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7113781.041682037\n",
      "Iteration 13\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7113502.258198252\n",
      "Iteration 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7113311.373592409\n",
      "Iteration 15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 7113210.850990934\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values inf\n",
      "Iteration 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Cost function values 8972828.92405828\n",
      "Iteration 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8789834.29285686\n",
      "Iteration 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8773938.04682192\n",
      "Iteration 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8765096.777863715\n",
      "Iteration 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8739652.224155951\n",
      "Iteration 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8704871.371414676\n",
      "Iteration 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8696004.190604532\n",
      "Iteration 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8694091.158258382\n",
      "Iteration 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8693719.536082473\n",
      "Iteration 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8693521.4612246\n",
      "Iteration 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8693219.271669399\n",
      "Iteration 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 2217:================================================>     (29 + 3) / 32]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function values 8693183.72605247\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "[Stage 2217:==================================================>   (30 + 2) / 32]\r",
      "\r",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "data = spark.createDataFrame(pd.read_csv(\"./data.csv\"))\n",
    "k = 23 # length of unique labels\n",
    "partitions = np.array([32])\n",
    "iterations = 5\n",
    "\n",
    "part_cost_ll, part_time_ll =  avg_cost_time_results(k=k, data=data, partitions=partitions, iterations=iterations,\n",
    "                                                   func=kmeans_ll, L=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "2c4fcde5",
   "metadata": {},
   "outputs": [],
   "source": [
    "part_cost_ll = pad_arrays(part_cost_ll)\n",
    "\n",
    "part_time_ll = np.array(part_time_ll)\n",
    "part_cost_ll = np.array(part_cost_ll)\n",
    "\n",
    "# Mask padded values\n",
    "mask_ll = (part_cost_ll != 0)\n",
    "\n",
    "# Calculate average and standard deviation over columns considering non-padded elements only\n",
    "avg_cost_ll = np.sum(part_cost_ll * mask_ll, axis=0) / np.sum(mask_ll, axis=0)\n",
    "std_cost_ll = np.sqrt(np.sum(((part_cost_ll - avg_cost_ll) ** 2) * mask_ll, axis=0) / np.sum(mask_ll, axis=0))\n",
    "\n",
    "avg_time_ll = np.mean(part_time_ll)\n",
    "std_time_ll = np.std(part_time_ll)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "bb3ddcb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the average cost over iterations with error bars representing standard deviation\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.errorbar(range(1, len(avg_cost) + 1), avg_cost, yerr=std_cost, fmt='o-', color='green', ecolor='lightgreen', elinewidth=3, capsize=0, label='Random KMeans')\n",
    "plt.errorbar(range(1, len(avg_cost_ll) + 1), avg_cost_ll, yerr=std_cost_ll, fmt='o-', color='orange', ecolor='lightgray', elinewidth=3, capsize=0, label='KMeans ll')\n",
    "plt.xlabel('Iterations')\n",
    "plt.ylabel('Average Cost')\n",
    "plt.title('Average Cost Over Iterations with Standard Deviation Error Bars')\n",
    "plt.ylim(6.5*1e6, 10.5*1e6)\n",
    "plt.grid(True)\n",
    "plt.legend(loc='upper left')\n",
    "\n",
    "# Creating a bar plot in the top right corner for avg_time and avg_time * 2\n",
    "ax = plt.axes([0.65, 0.6, 0.25, 0.2])  # [left, bottom, width, height]\n",
    "ax.bar(1, avg_time, width=0.4, align='center', alpha=0.7, color='green', label='Random KMeans', yerr=std_time, capsize=5)\n",
    "ax.bar(2, avg_time_ll, width=0.4, align='center', alpha=0.7, color='orange', label='KMeans ll', yerr=std_time_ll, capsize=5)\n",
    "ax.set_xticks([1, 2])\n",
    "ax.set_xticklabels(['Random KMeans', 'KMeans ll'])\n",
    "ax.set_ylabel('Avg Time')\n",
    "ax.set_title('Execution Time')\n",
    "\n",
    "\n",
    "# Set legend for both the plots\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "66826af8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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