GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/14919
[SPARK-17354][SQL] Partitioning by dates/timestamps should work with
Parquet vectorized reader
## What changes were proposed in this pull request?
This PR fixes `ColumnVectorUtils.populate` so that Parquet vectorized
reader can read partitioned table with dates/timestamps.
This is being only called within
[VectorizedParquetRecordReader.java#L185](https://github.com/apache/spark/blob/master/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedParquetRecordReader.java#L185).
When partition column types are explicitly given, this fails with the
exception below:
```
16/09/01 10:30:07 ERROR Executor: Exception in task 0.0 in stage 5.0 (TID 6)
java.lang.ClassCastException: java.lang.Integer cannot be cast to
java.sql.Date
at
org.apache.spark.sql.execution.vectorized.ColumnVectorUtils.populate(ColumnVectorUtils.java:89)
at
org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:185)
at
org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:204)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReader$1.apply(ParquetFileFormat.scala:362)
at
```
## How was this patch tested?
Unit tests in `SQLQuerySuite`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/HyukjinKwon/spark SPARK-17354
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14919.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 #14919
----
commit bef83fca16b7cda1021cbb2f992109a4c1624c0d
Author: hyukjinkwon <[email protected]>
Date: 2016-09-01T13:10:09Z
Partitioning by dates/timestamps works with Parquet vectorized reader
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