GitHub user gatorsmile opened a pull request:
https://github.com/apache/spark/pull/13773
[SPARK-16056] [SPARK-16057] [SPARK-16058] [SQL] Fix Multiple Bugs in Column
Partitioning in JDBC Source
#### What changes were proposed in this pull request?
This PR is to fix the following bugs:
**Issue 1: Wrong Results when lowerBound is larger than upperBound in
Column Partitioning**
```scala
spark.read.jdbc(
url = urlWithUserAndPass,
table = "TEST.seq",
columnName = "id",
lowerBound = 4,
upperBound = 0,
numPartitions = 3,
connectionProperties = new Properties)
```
**Before code changes:**
The generated partitions are wrong:
```
Part 0 id < 3 or id is null
Part 1 id >= 3 AND id < 2
Part 2 id >= 2
```
**After code changes:**
Issue an `IllegalArgumentException` exception:
```
Operation not allowed: the lower bound of partitioning column is larger
than the upper bound. lowerBound: 5; higherBound: 1
```
**Issue 2: numPartitions is More than the number of rows between upper and
lower bounds**
```scala
spark.read.jdbc(
url = urlWithUserAndPass,
table = "TEST.seq",
columnName = "id",
lowerBound = 1,
upperBound = 5,
numPartitions = 10,
connectionProperties = new Properties)
```
**Before code changes:**
Generated partitions are like:
```
Partition 0: id < 1 or id is null
Partition 1: id >= 1 AND id < 1
Partition 2: id >= 1 AND id < 1
Partition 3: id >= 1 AND id < 1
Partition 4: id >= 1 AND id < 1
Partition 5: id >= 1 AND id < 1
Partition 6: id >= 1 AND id < 1
Partition 7: id >= 1 AND id < 1
Partition 8: id >= 1 AND id < 1
Partition 9: id >= 1
```
**After code changes:**
Adjust `numPartitions` and can return correct answers:
```
Partition 0: id < 2 or id is null
Partition 1: id >= 2 AND id < 3
Partition 2: id >= 3 AND id < 4
Partition 3: id >= 4
```
**Issue 3: java.lang.ArithmeticException when numPartitions is zero**
```Scala
spark.read.jdbc(
url = urlWithUserAndPass,
table = "TEST.seq",
columnName = "id",
lowerBound = 0,
upperBound = 4,
numPartitions = 0,
connectionProperties = new Properties)
```
**Before code changes:**
Got the following exception:
```
java.lang.ArithmeticException: / by zero
```
**After code changes:**
Return a right answer by disabling column partitioning
#### How was this patch tested?
Added test cases to verify the results
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/gatorsmile/spark jdbcPartitioning
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/13773.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #13773
----
commit 2198f5975a452daa8946ddb0bb084d826a448d54
Author: gatorsmile <[email protected]>
Date: 2016-06-19T17:00:45Z
fix
----
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