spark-instrumented-optimizer/core/src/test
sujithjay 0bf1a74a77 [SPARK-22465][CORE] Add a safety-check to RDD defaultPartitioner
## What changes were proposed in this pull request?
In choosing a Partitioner to use for a cogroup-like operation between a number of RDDs, the default behaviour was if some of the RDDs already have a partitioner, we choose the one amongst them with the maximum number of partitions.

This behaviour, in some cases, could hit the 2G limit (SPARK-6235). To illustrate one such scenario, consider two RDDs:
rDD1: with smaller data and smaller number of partitions, alongwith a Partitioner.
rDD2: with much larger data and a larger number of partitions, without a Partitioner.

The cogroup of these two RDDs could hit the 2G limit, as a larger amount of data is shuffled into a smaller number of partitions.

This PR introduces a safety-check wherein the Partitioner is chosen only if either of the following conditions are met:
1. if the number of partitions of the RDD associated with the Partitioner is greater than or equal to the max number of upstream partitions; or
2. if the number of partitions of the RDD associated with the Partitioner is less than and within a single order of magnitude of the max number of upstream partitions.

## How was this patch tested?
Unit tests in PartitioningSuite and PairRDDFunctionsSuite

Author: sujithjay <sujith@logistimo.com>

Closes #20002 from sujithjay/SPARK-22465.
2017-12-24 11:14:30 -08:00
..
java [SPARK-17788][SPARK-21033][SQL] fix the potential OOM in UnsafeExternalSorter and ShuffleExternalSorter 2017-10-30 17:53:06 +01:00
resources [SPARK-20648][CORE] Port JobsTab and StageTab to the new UI backend. 2017-11-14 10:34:32 -06:00
scala/org/apache [SPARK-22465][CORE] Add a safety-check to RDD defaultPartitioner 2017-12-24 11:14:30 -08:00