What are paired RDDs in Spark?

Spark Paired RDDs are defined as the RDD containing a key-value pair. There is two linked data item in a key-value pair (KVP). We can say the key is the identifier, while the value is the data corresponding to the key value. In addition, most of the Spark operations work on RDDs containing any type of objects.

What is the difference between RDDs and paired RDDs?

pairRDD operations are applied on each key/element in parallel. Operations on RDD (like flatMap) are applied to the whole collection. Spark provides special operations on RDDs containing key/value pairs. These RDDs are called pair RDDs.

How do I combine two RDDs in Spark?

Which function in spark is used to combine two RDDs by keys

1. rdd1 = [ (key1, [value1, value2]), (key2, [value3, value4]) ] and.
2. rdd2 = [ (key1, [value5, value6]), (key2, [value7]) ]
3. ret = [ (key1, [value1, value2, value5, value6]), (key2, [value3, value4, value7]) ]

Which method is used to perform a right outer join between 2 pair RDDS?

rightOuterJoin(): Perform a right outer join of this and other.

What is the difference between groupByKey and reduceByKey in spark?

Both reduceByKey and groupByKey result in wide transformations which means both triggers a shuffle operation. The key difference between reduceByKey and groupByKey is that reduceByKey does a map side combine and groupByKey does not do a map side combine.

Which method is used to perform a right outer join between 2 pair RDDs?

What is the difference between MAP and flatMap in spark?

As per the definition, difference between map and flatMap is: map : It returns a new RDD by applying given function to each element of the RDD. Function in map returns only one item. flatMap : Similar to map , it returns a new RDD by applying a function to each element of the RDD, but output is flattened.

How do I join RDD?

RDD join can only be done in the form of key value pair. Once it is joined, the value of both RDD are nested. Becasue we need courseID to further join with course RDD, we need name for final result. We need to remap the postion of join result.

How do I join multiple RDDs?

Joining 3 pair-RDDs

1. populate 2 RDD (A and B)
2. identify a common key and create 2 pair-RDD (A and B)
3. perform a join on this key and get a 3rd RDD (C)
4. populate a new RDD (D)
5. identify a common key and create 2 pair-RDD again (C and D)
6. perform a join on this key and get a 5th RDD (E)

What is narrow and wide transformation in Spark?

Narrow transformations are the result of map(), filter(). Wide transformation — In wide transformation, all the elements that are required to compute the records in the single partition may live in many partitions of parent RDD. Wide transformations are the result of groupbyKey and reducebyKey.