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From "Tejas Patil (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-19122) Unnecessary shuffle+sort added if join predicates ordering differ from bucketing and sorting order
Date Sun, 08 Jan 2017 01:06:58 GMT
Tejas Patil created SPARK-19122:
-----------------------------------

             Summary: Unnecessary shuffle+sort added if join predicates ordering differ from
bucketing and sorting order
                 Key: SPARK-19122
                 URL: https://issues.apache.org/jira/browse/SPARK-19122
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 2.1.0, 2.0.2
            Reporter: Tejas Patil


`table1` and `table2` are sorted and bucketed on columns `j` and `k` (in respective order)

This is how they are generated:
{code}
val df = (0 until 16).map(i => (i % 8, i * 2, i.toString)).toDF("i", "j", "k").coalesce(1)
df.write.format("org.apache.spark.sql.hive.orc.OrcFileFormat").bucketBy(8, "j", "k").sortBy("j",
"k").saveAsTable("table1")
df.write.format("org.apache.spark.sql.hive.orc.OrcFileFormat").bucketBy(8, "j", "k").sortBy("j",
"k").saveAsTable("table2")
{code}

Now, if join predicates are specified in query in *same* order as bucketing and sort order,
there is no shuffle and sort.

{code}
scala> hc.sql("SELECT * FROM table1 a JOIN table2 b ON a.j=b.j AND a.k=b.k").explain(true)

== Physical Plan ==
*SortMergeJoin [j#61, k#62], [j#100, k#101], Inner
:- *Project [i#60, j#61, k#62]
:  +- *Filter (isnotnull(k#62) && isnotnull(j#61))
:     +- *FileScan orc default.table1[i#60,j#61,k#62] Batched: false, Format: ORC, Location:
InMemoryFileIndex[file:/Users/tejasp/Desktop/dev/tp-spark/spark-warehouse/table1], PartitionFilters:
[], PushedFilters: [IsNotNull(k), IsNotNull(j)], ReadSchema: struct<i:int,j:int,k:string>
+- *Project [i#99, j#100, k#101]
   +- *Filter (isnotnull(j#100) && isnotnull(k#101))
      +- *FileScan orc default.table2[i#99,j#100,k#101] Batched: false, Format: ORC, Location:
InMemoryFileIndex[file:/Users/tejasp/Desktop/dev/tp-spark/spark-warehouse/table2], PartitionFilters:
[], PushedFilters: [IsNotNull(j), IsNotNull(k)], ReadSchema: struct<i:int,j:int,k:string>
{code}


The same query with join predicates in *different* order from bucketing and sort order leads
to extra shuffle and sort being introduced

{code}
scala> hc.sql("SELECT * FROM table1 a JOIN table2 b ON a.k=b.k AND a.j=b.j ").explain(true)

== Physical Plan ==
*SortMergeJoin [k#62, j#61], [k#101, j#100], Inner
:- *Sort [k#62 ASC NULLS FIRST, j#61 ASC NULLS FIRST], false, 0
:  +- Exchange hashpartitioning(k#62, j#61, 200)
:     +- *Project [i#60, j#61, k#62]
:        +- *Filter (isnotnull(k#62) && isnotnull(j#61))
:           +- *FileScan orc default.table1[i#60,j#61,k#62] Batched: false, Format: ORC, Location:
InMemoryFileIndex[file:/spark-warehouse/table1], PartitionFilters: [], PushedFilters: [IsNotNull(k),
IsNotNull(j)], ReadSchema: struct<i:int,j:int,k:string>
+- *Sort [k#101 ASC NULLS FIRST, j#100 ASC NULLS FIRST], false, 0
   +- Exchange hashpartitioning(k#101, j#100, 200)
      +- *Project [i#99, j#100, k#101]
         +- *Filter (isnotnull(j#100) && isnotnull(k#101))
            +- *FileScan orc default.table2[i#99,j#100,k#101] Batched: false, Format: ORC,
Location: InMemoryFileIndex[file:/spark-warehouse/table2], PartitionFilters: [], PushedFilters:
[IsNotNull(j), IsNotNull(k)], ReadSchema: struct<i:int,j:int,k:string>
{code}



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