analytix-hostmetrics-example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://swan.web.cern.ch/sites/swan.web.cern.ch/files/pictures/logo_swan_letters.png\" alt=\"SWAN\" style=\"float: left; width: 20%; margin-right: 15%; margin-left: 15%; margin-bottom: 2.0em;\">\n",
    "<img src=\"https://spark.apache.org/images/spark-logo-trademark.png\" alt=\"EP-SFT\" style=\"float: left; width: 25%; margin-right: 15%; margin-bottom: 2.0em;\">\n",
    "<p style=\"clear: both;\">\n",
    "<div style=\"text-align:center\"><h1>Integration of SWAN with Spark clusters</h1></div>\n",
    "<hr style=\"border-top-width: 4px; border-top-color: #34609b;\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The current setup allows to execute PySpark operations on CERN Hadoop and Spark clusters. \n",
    "\n",
    "This notebook illustrates the use of __Spark in SWAN to analyze the monitoring data available on HDFS (analytix)__ and plots a heatmap of loadAvg across machines in a particular service."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Connect to the cluster (analytix)\n",
    "*Env - LCG_97a & analytix*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To connect to a cluster, click on the star button on the top and follow the instructions\n",
    "* The star button only appears if you have selected a SPARK cluster in the configuration\n",
    "* The star button is active after the notebook kernel is ready"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import necessary spark and python stuff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.functions import from_unixtime, when, col\n",
    "from pyspark.sql.types import *\n",
    "from pyspark.sql.functions import from_json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### select the data\n",
    "*path_on_hdfs_to_your_data*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = spark.read.parquet(\"/project/monitoring/collectd/load/2020/10/14/\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### check the structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- dstype: string (nullable = true)\n",
      " |-- host: string (nullable = true)\n",
      " |-- interval: double (nullable = true)\n",
      " |-- plugin: string (nullable = true)\n",
      " |-- plugin_instance: string (nullable = true)\n",
      " |-- time: long (nullable = true)\n",
      " |-- type: string (nullable = true)\n",
      " |-- type_instance: string (nullable = true)\n",
      " |-- env: string (nullable = true)\n",
      " |-- region: string (nullable = true)\n",
      " |-- dc: string (nullable = true)\n",
      " |-- value: double (nullable = true)\n",
      " |-- value_instance: string (nullable = true)\n",
      " |-- _id: string (nullable = true)\n",
      " |-- availability_zone: string (nullable = true)\n",
      " |-- event_timestamp: long (nullable = true)\n",
      " |-- submitter_environment: string (nullable = true)\n",
      " |-- submitter_hostgroup: string (nullable = true)\n",
      " |-- timestamp: long (nullable = true)\n",
      " |-- toplevel_hostgroup: string (nullable = true)\n",
      " |-- version: string (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.printSchema()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create temporary table view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.createOrReplaceTempView(\"loadAvg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Do the heavylifting in spark and collect aggregated view to panda DF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_loadAvg_pandas = spark.sql(\"SELECT host, \\\n",
    "                                      avg(value) as avg, \\\n",
    "                                      hour(from_unixtime(timestamp / 1000, 'yyyy-MM-dd HH:mm:ss')) as hr \\\n",
    "                               FROM loadAvg \\\n",
    "                               WHERE submitter_hostgroup like 'hadoop_ng/nxcals_prod%' \\\n",
    "                               AND dayofmonth(from_unixtime(timestamp / 1000, 'yyyy-MM-dd HH:mm:ss')) = 14 \\\n",
    "                               GROUP BY hour(from_unixtime(timestamp / 1000, 'yyyy-MM-dd HH:mm:ss')), host\")\\\n",
    "                    .toPandas()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize with seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1, 'Heatmap of loadAvg for NXCals cluster on 14th October 2020')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# heatmap of loadAvg\n",
    "plt.figure(figsize=(12, 8))\n",
    "ax = sns.heatmap(df_loadAvg_pandas.pivot(index='host', columns='hr', values='avg'), cmap=\"Blues\")\n",
    "ax.set_title(\"Heatmap of loadAvg for NXCals cluster on 14th October 2020\", fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create histogram of uptime for the servers in datacenter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create the dataframe\n",
    "df = spark.read.parquet(\"/project/monitoring/collectd/uptime/2020/10/14/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create temporary view\n",
    "df.createOrReplaceTempView(\"uptime\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# processing in spark\n",
    "df_uptime_pandas = spark.sql(\"SELECT  host, round(max(value)/60/60/24) as days \\\n",
    "                              FROM uptime \\\n",
    "                               WHERE dayofmonth(from_unixtime(timestamp / 1000, 'yyyy-MM-dd HH:mm:ss')) = 14 \\\n",
    "                               AND hour(from_unixtime(timestamp / 1000, 'yyyy-MM-dd HH:mm:ss')) = 12 \\\n",
    "                               GROUP BY host\")\\\n",
    "                    .toPandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize with seaborn\n",
    "# histogram of uptime (last reboot)\n",
    "plt.figure(figsize=(12, 8))\n",
    "ax = sns.distplot(df_uptime_pandas['days'], kde=False, color='red', bins=range(0, 1800, 20))\n",
    "ax.set_title(\"Histogram of uptime (last reboot) for servers in datacenter\", fontsize=20)\n",
    "ax.set_yscale('log')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  },
  "sparkconnect": {
   "bundled_options": [],
   "list_of_options": []
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}