chutten/beta_spinners_frequencies.ipynb Secret

## beta_spinners_frequencies.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Egregious Spinners on Beta 50 and their Frequencies of Occurence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/hadoop/anaconda2/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unable to parse whitelist (/home/hadoop/anaconda2/lib/python2.7/site-packages/moztelemetry/histogram-whitelists.json). Assuming all histograms are acceptable.\n",
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: pylab import has clobbered these variables: ['Annotation', 'Figure']\n",
      "`%matplotlib` prevents importing * from pylab and numpy\n"
     ]
    }
   ],
   "source": [
    "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",
    "from plotly.graph_objs import *\n",
    "import IPython\n",
    "\n",
    "from moztelemetry import get_pings, get_pings_properties, get_one_ping_per_client, get_clients_history, get_records\n",
    "\n",
    "%pylab inline\n",
    "IPython.core.pylabtools.figsize(16, 7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "224"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc.defaultParallelism"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pings = get_pings(sc, app=\"Firefox\", channel=\"beta\", version=\"50.0\", submission_date=\"20160923\", fraction=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "969450"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pings.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "subset = get_pings_properties(pings, [\"clientId\",\n",
    "                                      \"environment/system/os/name\",\n",
    "                                      \"environment/system/memoryMB\",\n",
    "                                      \"environment/system/cpu/speedMHz\",\n",
    "                                      \"environment/addons/activeAddons\",\n",
    "                                      \"payload/histograms/GC_MAX_PAUSE_MS\",\n",
    "                                      \"payload/histograms/CYCLE_COLLECTOR_MAX_PAUSE\",\n",
    "                                      \"payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS\"], with_processes=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "acceptable_addons = set([\n",
    "        \"e10srollout@mozilla.org\",\n",
    "        \"firefox@getpocket.com\",\n",
    "        \"webcompat@mozilla.org\",\n",
    "    ])\n",
    "\n",
    "def no_addons(p):\n",
    "    return p[\"environment/addons/activeAddons\"] is None or \\\n",
    "        len(p[\"environment/addons/activeAddons\"]) == 0 or \\\n",
    "        len(set(p[\"environment/addons/activeAddons\"].keys()) | acceptable_addons) == len(acceptable_addons)\n",
    "\n",
    "acceptable = subset.filter(no_addons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "subset = acceptable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "468574"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ping_count = subset.count()\n",
    "ping_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28018"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spinning_pings = subset.filter(lambda p: p[\"payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS\"] is not None)\n",
    "spinning_pings.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "140593"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client_count = get_one_ping_per_client(subset).count()\n",
    "client_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18876"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spinning_clients_count = get_one_ping_per_client(spinning_pings).count()\n",
    "spinning_clients_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6933"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hgram = \"payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS\"\n",
    "def has_longish_spinner(p):\n",
    "    if p[hgram] is None:\n",
    "        return False\n",
    "    for bucket, count in p[hgram].iteritems():\n",
    "        if bucket > 1000 and count > 0:\n",
    "            return True\n",
    "    return False\n",
    "\n",
    "longish_spinning_pings = spinning_pings.filter(has_longish_spinner)\n",
    "longish_spinning_pings.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5477"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "longish_spinning_clients = get_one_ping_per_client(longish_spinning_pings)\n",
    "longish_spinning_clients.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check frequencies of spinners per client, per bucket"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "client_spinner_freq = spinning_pings \\\n",
    "    .flatMap(lambda p: [((p[\"clientId\"], bucket), p[hgram][bucket]) for bucket in p[hgram].keys()]) \\\n",
    "    .reduceByKey(lambda a,b: a+b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAHBCAYAAACygEz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nev8/6BumRz+DRE4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4157ca2f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAHBCAYAAACygEz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAACAwdPcAgAAMHiaWwAAAAbv/wezOKR0sIdZbgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4157d27e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAHBCAYAAACygEz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4157d27dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAHBCAYAAACygEz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f41551d4e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAHBCAYAAACygEz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4155278310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAHBCAYAAACygEz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nADbeXhVUcwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f41552b4e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAHBCAYAAACygEz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCwAAQO8pbgEAAOi9/wOrlylqXYd73AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f41555efd50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "limit = 50\n",
    "\n",
    "for bucket in spinning_pings.take(1)[0][hgram].keys():\n",
    "    bucket_client_spinner_freq = client_spinner_freq \\\n",
    "        .filter(lambda x: x[0][1] == bucket) \\\n",
    "        .map(lambda x: x[1] if x[1] < limit else limit) # cap to a max of `limit` spinners\n",
    "    bucket_spinner_series = pd.Series(bucket_client_spinner_freq.collect())\n",
    "    bucket_spinner_series.hist(bins=limit, log=True, width=1)\n",
    "    plt.xlim(0, limit)\n",
    "    plt.title(\"Spinners of length %d\" % bucket)\n",
    "    plt.xlabel(\"Number of spinners ( %d total )\" % bucket_spinner_series.sum())\n",
    "    plt.ylabel(\"Number of clients\")\n",
    "    plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}

## beta_spinners_frequencies.py

# coding: utf-8

# ### Egregious Spinners on Beta 50 and their Frequencies of Occurence

# In[1]:

import ujson as json
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import plotly.plotly as py
from plotly.graph_objs import *
import IPython

from moztelemetry import get_pings, get_pings_properties, get_one_ping_per_client, get_clients_history, get_records

get_ipython().magic(u'pylab inline')
IPython.core.pylabtools.figsize(16, 7)


# In[2]:

sc.defaultParallelism


# In[3]:

pings = get_pings(sc, app="Firefox", channel="beta", version="50.0", submission_date="20160923", fraction=1)


# In[4]:

pings.count()


# In[5]:

subset = get_pings_properties(pings, ["clientId",
                                      "environment/system/os/name",
                                      "environment/system/memoryMB",
                                      "environment/system/cpu/speedMHz",
                                      "environment/addons/activeAddons",
                                      "payload/histograms/GC_MAX_PAUSE_MS",
                                      "payload/histograms/CYCLE_COLLECTOR_MAX_PAUSE",
                                      "payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS"], with_processes=True)


# In[6]:

acceptable_addons = set([
        "e10srollout@mozilla.org",
        "firefox@getpocket.com",
        "webcompat@mozilla.org",
    ])

def no_addons(p):
    return p["environment/addons/activeAddons"] is None or         len(p["environment/addons/activeAddons"]) == 0 or         len(set(p["environment/addons/activeAddons"].keys()) | acceptable_addons) == len(acceptable_addons)

acceptable = subset.filter(no_addons)


# In[7]:

subset = acceptable


# In[8]:

ping_count = subset.count()
ping_count


# In[9]:

spinning_pings = subset.filter(lambda p: p["payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS"] is not None)
spinning_pings.count()


# In[10]:

client_count = get_one_ping_per_client(subset).count()
client_count


# In[11]:

spinning_clients_count = get_one_ping_per_client(spinning_pings).count()
spinning_clients_count


# In[12]:

hgram = "payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS"
def has_longish_spinner(p):
    if p[hgram] is None:
        return False
    for bucket, count in p[hgram].iteritems():
        if bucket > 1000 and count > 0:
            return True
    return False

longish_spinning_pings = spinning_pings.filter(has_longish_spinner)
longish_spinning_pings.count()


# In[13]:

longish_spinning_clients = get_one_ping_per_client(longish_spinning_pings)
longish_spinning_clients.count()


# #### Check frequencies of spinners per client, per bucket

# In[14]:

client_spinner_freq = spinning_pings     .flatMap(lambda p: [((p["clientId"], bucket), p[hgram][bucket]) for bucket in p[hgram].keys()])     .reduceByKey(lambda a,b: a+b)


# In[15]:

limit = 50

for bucket in spinning_pings.take(1)[0][hgram].keys():
    bucket_client_spinner_freq = client_spinner_freq         .filter(lambda x: x[0][1] == bucket)         .map(lambda x: x[1] if x[1] < limit else limit) # cap to a max of `limit` spinners
    bucket_spinner_series = pd.Series(bucket_client_spinner_freq.collect())
    bucket_spinner_series.hist(bins=limit, log=True, width=1)
    plt.xlim(0, limit)
    plt.title("Spinners of length %d" % bucket)
    plt.xlabel("Number of spinners ( %d total )" % bucket_spinner_series.sum())
    plt.ylabel("Number of clients")
    plt.show()

	# coding: utf-8

	# ### Egregious Spinners on Beta 50 and their Frequencies of Occurence

	# In[1]:

	import ujson as json
	import matplotlib.pyplot as plt
	import pandas as pd
	import numpy as np
	import plotly.plotly as py
	from plotly.graph_objs import *
	import IPython

	from moztelemetry import get_pings, get_pings_properties, get_one_ping_per_client, get_clients_history, get_records

	get_ipython().magic(u'pylab inline')
	IPython.core.pylabtools.figsize(16, 7)


	# In[2]:

	sc.defaultParallelism


	# In[3]:

	pings = get_pings(sc, app="Firefox", channel="beta", version="50.0", submission_date="20160923", fraction=1)


	# In[4]:

	pings.count()


	# In[5]:

	subset = get_pings_properties(pings, ["clientId",
	"environment/system/os/name",
	"environment/system/memoryMB",
	"environment/system/cpu/speedMHz",
	"environment/addons/activeAddons",
	"payload/histograms/GC_MAX_PAUSE_MS",
	"payload/histograms/CYCLE_COLLECTOR_MAX_PAUSE",
	"payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS"], with_processes=True)


	# In[6]:

	acceptable_addons = set([
	"e10srollout@mozilla.org",
	"firefox@getpocket.com",
	"webcompat@mozilla.org",
	])

	def no_addons(p):
	return p["environment/addons/activeAddons"] is None or len(p["environment/addons/activeAddons"]) == 0 or len(set(p["environment/addons/activeAddons"].keys()) \| acceptable_addons) == len(acceptable_addons)

	acceptable = subset.filter(no_addons)


	# In[7]:

	subset = acceptable


	# In[8]:

	ping_count = subset.count()
	ping_count


	# In[9]:

	spinning_pings = subset.filter(lambda p: p["payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS"] is not None)
	spinning_pings.count()


	# In[10]:

	client_count = get_one_ping_per_client(subset).count()
	client_count


	# In[11]:

	spinning_clients_count = get_one_ping_per_client(spinning_pings).count()
	spinning_clients_count


	# In[12]:

	hgram = "payload/histograms/FX_TAB_SWITCH_SPINNER_VISIBLE_LONG_MS"
	def has_longish_spinner(p):
	if p[hgram] is None:
	return False
	for bucket, count in p[hgram].iteritems():
	if bucket > 1000 and count > 0:
	return True
	return False

	longish_spinning_pings = spinning_pings.filter(has_longish_spinner)
	longish_spinning_pings.count()


	# In[13]:

	longish_spinning_clients = get_one_ping_per_client(longish_spinning_pings)
	longish_spinning_clients.count()


	# #### Check frequencies of spinners per client, per bucket

	# In[14]:

	client_spinner_freq = spinning_pings .flatMap(lambda p: [((p["clientId"], bucket), p[hgram][bucket]) for bucket in p[hgram].keys()]) .reduceByKey(lambda a,b: a+b)


	# In[15]:

	limit = 50

	for bucket in spinning_pings.take(1)[0][hgram].keys():
	bucket_client_spinner_freq = client_spinner_freq .filter(lambda x: x[0][1] == bucket) .map(lambda x: x[1] if x[1] < limit else limit) # cap to a max of `limit` spinners
	bucket_spinner_series = pd.Series(bucket_client_spinner_freq.collect())
	bucket_spinner_series.hist(bins=limit, log=True, width=1)
	plt.xlim(0, limit)
	plt.title("Spinners of length %d" % bucket)
	plt.xlabel("Number of spinners ( %d total )" % bucket_spinner_series.sum())
	plt.ylabel("Number of clients")
	plt.show()