downgrade-analysis

downgrade-analysis.ipynb

downgrade-analysis.py

# coding: utf-8

# Downgrade and Channel Switching Analysis
# ========================================
# 
# authors:
# - bsmedberg
# 
# last run: 2017-03-08
# 

# ### Longitudinal Dataset Tutorial

# In[1]:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import plotly.plotly as py

get_ipython().magic(u'pylab inline')


# In[2]:

sc.defaultParallelism


# The longitudinal dataset can be accessed as a Spark [DataFrame](https://spark.apache.org/docs/1.5.2/api/python/pyspark.sql.html#pyspark.sql.DataFrame), which is a distributed collection of data organized into named columns. It is conceptually equivalent to a table in a relational database or a data frame in R/Python.

# In[3]:

frame = sqlContext.sql("SELECT client_id, profile_subsession_counter, build, settings FROM longitudinal")


# In[4]:

sc


# In[10]:

def get_version(v):
    if v is None:
        return None
    try:
        return int(v.split(".")[0])
    except ValueError:
        return None


# In[6]:

print get_version("")
print get_version("12.3")
print get_version("12")
print get_version("abcd")


# In[11]:

count_total = sc.accumulator(0)
count_backwardsversion = sc.accumulator(0)
count_channelswitch = sc.accumulator(0)
count_backwardsversion_releaseonly = sc.accumulator(0)

def mapper(row):
    channel_switch = False
    release_only = True
    backwardsversion = False

    # sessions are sorted by subsessionStartDate and then profileSubsessionCounter, newest-first.
    last_version = 99
    last_channel = None

    if row.settings is None:
        return
            
    for settings in row.settings:
        channel = settings.update.channel
        if channel != "release":
            release_only = False
        if last_channel is None:
            last_channel = channel
        elif last_channel != channel:
            channel_switch = True

    for build in row.build:
        version = get_version(build.version)
        if version is not None:
            if version > last_version:
                backwardsversion = True
            last_version = version

    count_total.add(1)
    if backwardsversion:
        count_backwardsversion.add(1)
        if release_only:
            count_backwardsversion_releaseonly.add(1)
    if channel_switch:
        count_channelswitch.add(1)
frame.rdd.foreach(mapper)

total = float(count_total.value)
print "users that switched channels at all: {:.2f}%".format(count_channelswitch.value / total * 100)
print "users that reverted to an older version: {:.2f}%".format(count_backwardsversion.value / total * 100)
print "users that reverted to an older version, staying on the release channel: {:.2f}".format(count_backwardsversion_releaseonly.value / total * 100)