Ping latency

Untitled.ipynb

Untitled.py

# coding: utf-8

# In[39]:

import ujson as json
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import IPython

from __future__ import division
from montecarlino import grouped_permutation_test

from moztelemetry.spark import get_pings, get_pings_properties

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

from operator import add
import datetime
import itertools
import collections
import dateutil
import dateutil.parser


# In[2]:

sc.defaultParallelism


# In[ ]:

def get_property(value, path):
    for key in path:
        if not isinstance(value, dict) or key not in value:
            return None
        value = value[key]
    return value


# In[4]:

criteria = {
    'app': 'Firefox',
    'channel': 'beta',
    'version': '47.0',
    'submission_date': "20160522",
}

main_pings = get_pings(sc, doc_type="main", **criteria)


# In[5]:

crash_pings = get_pings(sc, doc_type="crash", **criteria)


# In[18]:




# In[122]:

both_properties = [
    "meta/Timestamp",
    "creationDate",
]
main_properties = both_properties + [
    "payload/info/subsessionStartDate",
    "payload/info/subsessionLength",
]
crash_properties = both_properties + [
    "payload/crashDate",
    "payload/metadata/CrashTime",
]

main_data = get_pings_properties(main_pings, main_properties)
crash_data = get_pings_properties(crash_pings, crash_properties)


# In[123]:

main_data = main_data.cache()
crash_data = crash_data.cache()


# In[124]:

fm = main_data.first()
fm


# In[29]:

fc = crash_data.first()
fc


# In[70]:

errcount = sc.accumulator(0)
def cd_to_timestamp(crash_ping):
    try:
        cd = dateutil.parser.parse(crash_ping['payload/crashDate']).date()
        rd = datetime.date(2016, 5, 22)
        days = (rd - cd).days
        if days < 0:
            days = -1
        elif days > 20:
            days = 21
        yield days
    except ValueError:
        errcount.add(1)
        pass
    
crash_ping_latency = crash_data.flatMap(cd_to_timestamp).countByValue()
print "errcount", errcount.value


# In[130]:

crash_df = pd.DataFrame(data=crash_ping_latency.items(), columns=("Latency", "Count")).sort_values(("Latency"))
crash_total = crash_df['Count'].sum()
by_pct = crash_df.assign(pct=crash_df["Count"].div(crash_total / 100))
by_pct.plot.bar(x="Latency", y="pct",
                title="Latency of activity date (local time) against receipt date (UTC) for crash pings")


# In[127]:

main_errcount = sc.accumulator(0)
def cd_to_timestamp(main_ping):
    if main_ping['payload/info/subsessionStartDate'] is None:
        return
    try:
        hours = (main_ping["payload/info/subsessionLength"] or 0) / 3600.0
        if hours > 25:
            hours = 25
        elif hours < 0:
            return
        cd = dateutil.parser.parse(main_ping['payload/info/subsessionStartDate']).date()
        rd = datetime.date(2016, 5, 22)
        days = (rd - cd).days
        if days < 0:
            days = -1
        elif days > 20:
            days = 21
        yield (days, hours)
    except ValueError:
        errcount.add(1)
        pass
    
main_ping_latency = main_data.flatMap(cd_to_timestamp).foldByKey(0, add).collect()
print "errcount", main_errcount.value
main_df = pd.DataFrame(data=main_ping_latency, columns=("Latency", "Count")).sort_values(("Latency"))
main_df


# In[132]:

main_total = df['Count'].sum()
main_by_pct = main_df.assign(pct=main_df["Count"].div(main_total / 100))
main_by_pct.plot.bar(x="Latency", y="pct",
                title="Latency of activity date (local time) against receipt date (UTC) for main pings, by usage-hour")