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https://issues.apache.org/jira/browse/SPARK-13900?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15198099#comment-15198099
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Xiao Li commented on SPARK-13900:
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BroadcastNestedLoopJoin is much slower than BroadcastHashJoin. This is the
major reason why your first plan is faster than the second one.
> Spark SQL queries with OR condition is not optimized properly
> -------------------------------------------------------------
>
> Key: SPARK-13900
> URL: https://issues.apache.org/jira/browse/SPARK-13900
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.0
> Reporter: Ashok kumar Rajendran
>
> I have a large table with few billions of rows and have a very small table
> with 4 dimensional values. All the data is stored in parquet format. I would
> like to get rows that match any of these dimensions. For example,
> Select field1, field2 from A, B where A.dimension1 = B.dimension1 OR
> A.dimension2 = B.dimension2 OR A.dimension3 = B.dimension3 OR A.dimension4 =
> B.dimension4.
> The query plan takes this as BroadcastNestedLoopJoin and executes for very
> long time.
> If I execute this as Union queries, it takes around 1.5mins for each
> dimension. Each query internally does BroadcastHashJoin.
> Select field1, field2 from A, B where A.dimension1 = B.dimension1
> UNION ALL
> Select field1, field2 from A, B where A.dimension2 = B.dimension2
> UNION ALL
> Select field1, field2 from A, B where A.dimension3 = B.dimension3
> UNION ALL
> Select field1, field2 from A, B where A.dimension4 = B.dimension4.
> This is obviously not an optimal solution as it makes multiple scanning at
> same table but it gives result much better than OR condition.
> Seems the SQL optimizer is not working properly which causes huge performance
> impact on this type of OR query.
> Please correct me if I miss anything here.
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