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https://issues.apache.org/jira/browse/SPARK-10177?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Cheng Lian updated SPARK-10177:
-------------------------------
Description:
Running the following SQL under Hive 0.14.0+ (tested against 0.14.0 and 1.2.1):
{code:sql}
CREATE TABLE ts_test STORED AS PARQUET
AS SELECT CAST("2015-01-01 00:00:00" AS TIMESTAMP);
{code}
Then read the Parquet file generated by Hive with Spark SQL:
{noformat}
scala>
sqlContext.read.parquet("hdfs://localhost:9000/user/hive/warehouse_hive14/ts_test").collect()
res1: Array[org.apache.spark.sql.Row] = Array([2015-01-01 12:00:00.0])
{noformat}
This issue can be easily reproduced with this test case in PR
Spark 1.4.1 works as expected in this case.
was:
Running the following SQL under Hive 0.14.0+ (tested against 0.14.0 and 1.2.1):
{code:sql}
CREATE TABLE ts_test STORED AS PARQUET
AS SELECT CAST("2015-01-01 00:00:00" AS TIMESTAMP);
{code}
Then read the Parquet file generated by Hive with Spark SQL:
{noformat}
scala>
sqlContext.read.parquet("hdfs://localhost:9000/user/hive/warehouse_hive14/ts_test").collect()
res1: Array[org.apache.spark.sql.Row] = Array([2015-01-01 12:00:00.0])
{noformat}
Spark 1.4.1 works as expected in this case.
> Parquet support interprets timestamp values differently from Hive 0.14.0+
> -------------------------------------------------------------------------
>
> Key: SPARK-10177
> URL: https://issues.apache.org/jira/browse/SPARK-10177
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.0
> Reporter: Cheng Lian
> Assignee: Cheng Lian
> Priority: Blocker
> Attachments: 000000_0
>
>
> Running the following SQL under Hive 0.14.0+ (tested against 0.14.0 and
> 1.2.1):
> {code:sql}
> CREATE TABLE ts_test STORED AS PARQUET
> AS SELECT CAST("2015-01-01 00:00:00" AS TIMESTAMP);
> {code}
> Then read the Parquet file generated by Hive with Spark SQL:
> {noformat}
> scala>
> sqlContext.read.parquet("hdfs://localhost:9000/user/hive/warehouse_hive14/ts_test").collect()
> res1: Array[org.apache.spark.sql.Row] = Array([2015-01-01 12:00:00.0])
> {noformat}
> This issue can be easily reproduced with this test case in PR
> Spark 1.4.1 works as expected in this case.
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