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author | hyukjinkwon <gurwls223@gmail.com> | 2016-09-09 14:23:05 -0700 |
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committer | Davies Liu <davies.liu@gmail.com> | 2016-09-09 14:23:05 -0700 |
commit | f7d2143705c8c1baeed0bc62940f9dba636e705b (patch) | |
tree | 8067836599fbfb1a71595fb01551e0f775c6b644 /sql/hive/src | |
parent | a3981c28c956a82ccf5b1c61d45b6bd252d4abed (diff) | |
download | spark-f7d2143705c8c1baeed0bc62940f9dba636e705b.tar.gz spark-f7d2143705c8c1baeed0bc62940f9dba636e705b.tar.bz2 spark-f7d2143705c8c1baeed0bc62940f9dba636e705b.zip |
[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 works fine with Parquet normal reader.
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 to `DateType` or `TimestampType` (rather than inferring the type of partition column), 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)
...
```
## How was this patch tested?
Unit tests in `SQLQuerySuite`.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #14919 from HyukjinKwon/SPARK-17354.
Diffstat (limited to 'sql/hive/src')
-rw-r--r-- | sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala | 21 |
1 files changed, 21 insertions, 0 deletions
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala index 05d0687fb7..dc4d099f0f 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala @@ -1787,6 +1787,27 @@ class SQLQuerySuite extends QueryTest with SQLTestUtils with TestHiveSingleton { } } + test("SPARK-17354: Partitioning by dates/timestamps works with Parquet vectorized reader") { + withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "true") { + sql( + """CREATE TABLE order(id INT) + |PARTITIONED BY (pd DATE, pt TIMESTAMP) + |STORED AS PARQUET + """.stripMargin) + + sql("set hive.exec.dynamic.partition.mode=nonstrict") + sql( + """INSERT INTO TABLE order PARTITION(pd, pt) + |SELECT 1 AS id, CAST('1990-02-24' AS DATE) AS pd, CAST('1990-02-24' AS TIMESTAMP) AS pt + """.stripMargin) + val actual = sql("SELECT * FROM order") + val expected = sql( + "SELECT 1 AS id, CAST('1990-02-24' AS DATE) AS pd, CAST('1990-02-24' AS TIMESTAMP) AS pt") + checkAnswer(actual, expected) + sql("DROP TABLE order") + } + } + def testCommandAvailable(command: String): Boolean = { val attempt = Try(Process(command).run(ProcessLogger(_ => ())).exitValue()) attempt.isSuccess && attempt.get == 0 |