[SPARK-15916][SQL] JDBC filter push down should respect operator precedence #13743
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Test build #60729 has finished for PR 13743 at commit
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LGTM |
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Merging to master and branch-2.0. |
asfgit
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Jun 18, 2016
…edence
## What changes were proposed in this pull request?
This PR fixes the problem that the precedence order is messed when pushing where-clause expression to JDBC layer.
**Case 1:**
For sql `select * from table where (a or b) and c`, the where-clause is wrongly converted to JDBC where-clause `a or (b and c)` after filter push down. The consequence is that JDBC may returns less or more rows than expected.
**Case 2:**
For sql `select * from table where always_false_condition`, the result table may not be empty if the JDBC RDD is partitioned using where-clause:
```
spark.read.jdbc(url, table, predicates = Array("partition 1 where clause", "partition 2 where clause"...)
```
## How was this patch tested?
Unit test.
This PR also close #13640
Author: hyukjinkwon <[email protected]>
Author: Sean Zhong <[email protected]>
Closes #13743 from clockfly/SPARK-15916.
(cherry picked from commit ebb9a3b)
Signed-off-by: Cheng Lian <[email protected]>
zzcclp
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Jul 27, 2016
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What changes were proposed in this pull request?
This PR fixes the problem that the precedence order is messed when pushing where-clause expression to JDBC layer.
Case 1:
For sql
select * from table where (a or b) and c, the where-clause is wrongly converted to JDBC where-clausea or (b and c)after filter push down. The consequence is that JDBC may returns less or more rows than expected.Case 2:
For sql
select * from table where always_false_condition, the result table may not be empty if the JDBC RDD is partitioned using where-clause:How was this patch tested?
Unit test.
This PR also close #13640