Processing tweets with Spark

Processing tweets with Spark =

Continuing the examples from [Getting started with Apache Spark]:

• load the tweets in ‘tweet-id-text-345/’ as JSON objects
• collect only the texts from the tweets
• split the texts into words and select all the hashtags
• the step where you go from a column of lists-of-words to a columns of words is a little harder

 * you can write this step in Python (using collect() and then creating a new DataFrame)
 * you can also go via a Pandas frame, but like the Python solution, this breaks the parallel processing
 * you can also use the file all-tweet-words.txt in mitt.uib.no to skip this step
 * two other solutions, which we will present later, are: 
   * going via an RDD and using a flatMap()
   * writing a user-defined Spark function (UDF)

• split the tweets into two sets of 80% and 20% size
• find URLs in the texts and download a few image files