I\'m working with Spark RDDs and created two idential length arrays, one is the hour of tweet, and the other is the text of a tweet. I\'m looking to combine these into one data
You should go with .zip to combine both rdds into RDD[(String, String)]
for example I created two rdds
val split_time = sparkContext.parallelize(Array("17", "17", "17", "17", "17", "17", "17", "17", "17", "17"))
val split_text = sparkContext.parallelize(Array("17", "17", "17", "17", "colts", "17", "17", "colts", "17", "17"))
zip combines both rdds as I have mentioned above into RDD[Tuple2[String, String]]
val tweet_tuple = split_time.zip(split_text)
After combining all you need is to apply .filter
tweet_tuple.filter(line => line._1 == "17" && line._2.toString.matches("colts"))
The output should be
(17,colts)
(17,colts)
Updated
Since your split_text rdd are collection of sentences, contains should be used instead of matches. So the following logic should work after you've zipped.
tweet_tuple.filter(line => line._1 == "17" && line._2.toString.contains("colts"))