[SPARK-19601] Fix CollapseRepartition rule to preserve shuffle-enabled Repartition

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 2.0.2, 2.1.0
• Fix Version/s: 2.2.0
• Component/s: SQL
• Assignee: Xiao Li
• Reporter: Xiao Li
• Created: 14/Feb/17 21:20
• Updated: 08/Mar/17 17:37
• Resolved: 08/Mar/17 17:37

Description

When users use the shuffle-enabled `repartition` API, they expect the partition they got should be the exact number they provided, even if they call shuffle-disabled `coalesce` later. Currently, `CollapseRepartition` rule does not consider whether shuffle is enabled or not. Thus, we got the following unexpected result.

    val df = spark.range(0, 10000, 1, 5)
    val df2 = df.repartition(10)
    assert(df2.coalesce(13).rdd.getNumPartitions == 5)
    assert(df2.coalesce(7).rdd.getNumPartitions == 5)
    assert(df2.coalesce(3).rdd.getNumPartitions == 3)

Issue Links

• links to: [Github] Pull Request #16933 (gatorsmile)