Architecture breakdown

Architecture breakdown.ipynb

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   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import ujson as json\n",
      "import matplotlib.pyplot as plt\n",
      "import pandas as pd\n",
      "import numpy as np\n",
      "import plotly.plotly as py\n",
      "\n",
      "from moztelemetry import get_pings, get_pings_properties, get_one_ping_per_client\n",
      "\n",
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pings = get_pings(sc, app=\"Firefox\", channel=\"nightly\", version=\"40.0a1\", submission_date=\"20150414\", fraction=1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "subset = get_pings_properties(pings, [\"clientID\", \"info/OS\", \"info/version\", \"info/arch\", \"simpleMeasurements/firstPaint\"])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 52
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def win_filter(ping):\n",
      "    return ping[\"OS\"] == \"WINNT\" and ping[\"version\"] == \"6.1\" and \"firstPaint\" in ping\n",
      "\n",
      "subset = subset.filter(win_filter)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 53
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Per session data:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "frame = pd.DataFrame(subset.collect())\n",
      "frame.groupby(\"arch\")[\"firstPaint\"].apply(len)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 54,
       "text": [
        "arch\n",
        "x86       20162\n",
        "x86-64    50215\n",
        "Name: firstPaint, dtype: int64"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Per client data:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "subset = get_one_ping_per_client(subset)\n",
      "frame = pd.DataFrame(subset.collect())\n",
      "frame.groupby(\"arch\")[\"firstPaint\"].apply(len)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 55,
       "text": [
        "arch\n",
        "x86        5199\n",
        "x86-64    12698\n",
        "Name: firstPaint, dtype: int64"
       ]
      }
     ],
     "prompt_number": 55
    }
   ],
   "metadata": {}
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