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https://issues.apache.org/jira/browse/SPARK-25873?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16668853#comment-16668853
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Pawan commented on SPARK-25873:
-------------------------------
[~hyukjin.kwon]
Please find below the data in t_src and t_tgt table:
{code:java}
hive> select * from t_src;
OK
p1 0001-01-01 00:00:00
p2 0002-01-01 00:00:00
p3 0003-01-01 00:00:00
p4 0004-01-01 00:00:00{code}
{code:java}
hive> select * from t_tgt;
OK
p1 0001-12-31 15:00:00
p2 0001-12-31 15:00:00
p3 0002-12-31 15:00:00
p4 0003-12-31 15:00:00{code}
Data in table t_tgt is a result of execution of scala code given in
description.
Thanks & regards,
Pawan Lawale
> Date corruption when Spark and Hive both are on different timezones
> -------------------------------------------------------------------
>
> Key: SPARK-25873
> URL: https://issues.apache.org/jira/browse/SPARK-25873
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, Spark Shell, Spark Submit
> Affects Versions: 2.2.1
> Reporter: Pawan
> Priority: Major
>
> There is date alteration when loading date from one table to another in hive
> through spark. This happens when Hive is on a remote machine with timezone
> different than the one on which Spark is running. This happens only when the
> Source table format is
> 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
> Below are the steps to produce the issue:
> 1. Create two tables as below in hive which has a timezone, say in, EST
> {code}
> CREATE TABLE t_src(
> name varchar(10),
> dob timestamp
> )
> ROW FORMAT SERDE
> 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
> STORED AS INPUTFORMAT
> 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat'
> OUTPUTFORMAT
> 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
> {code}
> {code}
> INSERT INTO t_src VALUES ('p1', '0001-01-01 00:00:00.0'),('p2', '0002-01-01
> 00:00:00.0'), ('p3', '0003-01-01 00:00:00.0'),('p4', '0004-01-01 00:00:00.0');
> {code}
>
> {code}
> CREATE TABLE t_tgt(
> name varchar(10),
> dob timestamp
> );
> {code}
> 2. Copy {{hive-site.xml}} to {{spark-2.2.1-bin-hadoop2.7/conf}} folder, so
> that when you create {{sqlContext}} for hive it connects to your remote hive
> server.
> 3. Start your spark-shell on some other machine whose timezone is different
> than that of Hive, say, PDT
> 4. Execute below code:
> {code}
> import org.apache.spark.sql.hive.HiveContext
> val sqlContext = new org.apache.spark.sql.hive.HiveContext(sc)
> val q0 = "TRUNCATE table t_tgt"
> val q1 = "SELECT CAST(alias.name AS String) as a0, alias.dob as a1 FROM t_src
> alias"
> val q2 = "INSERT OVERWRITE TABLE t_tgt SELECT tbl0.a0 as c0, tbl0.a1 as c1
> FROM tbl0"
> sqlContext.sql(q0)
> sqlContext.sql(q1).select("a0","a1").createOrReplaceTempView("tbl0")
> sqlContext.sql(q2)
> {code}
> 5. Now navigate to hive and check the contents of the {{TARGET table
> (t_tgt)}}. The dob field will have incorrect values.
>
> Is this a known issue? Is there any work around on this? Can it be fixed?
>
> Thanks & regards,
> Pawan Lawale
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