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Date: Tue, 9 May 2017 08:32:04 +0000 (UTC)
From: "Teng Yutong (JIRA)" <jira@apache.org>
To: issues@spark.apache.org
Message-ID: <JIRA.13013426.1476862988000.161766.1494318724209@Atlassian.JIRA>
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References: <JIRA.13013426.1476862988000@Atlassian.JIRA> <JIRA.13013426.1476862988206@jira-lw-us.apache.org>
Subject: [jira] [Commented] (SPARK-18004) DataFrame filter Predicate
 push-down fails for Oracle Timestamp type columns
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archived-at: Tue, 09 May 2017 08:32:19 -0000


    [ https://issues.apache.org/jira/browse/SPARK-18004?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16002282#comment-16002282 ] 

Teng Yutong commented on SPARK-18004:
-------------------------------------

a silly but doable workaround: cast TimestampType row to LongType and compare the inner representation...

```
src.filter(col("timestamp_col").cast(LongType).*(1000l) > condition.asInstanceOf[Timestamp].getTime)
```

> DataFrame filter Predicate push-down fails for Oracle Timestamp type columns
> ----------------------------------------------------------------------------
>
>                 Key: SPARK-18004
>                 URL: https://issues.apache.org/jira/browse/SPARK-18004
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.6.0
>            Reporter: Suhas Nalapure
>            Priority: Critical
>
> DataFrame filter Predicate push-down fails for Oracle Timestamp type columns with Exception java.sql.SQLDataException: ORA-01861: literal does not match format string:
> Java source code (this code works fine for mysql & mssql databases) :
> {noformat}
> //DataFrame df = create a DataFrame over an Oracle table
> df = df.filter(df.col("TS").lt(new java.sql.Timestamp(System.currentTimeMillis())));
> 		df.explain();
> 		df.show();
> {noformat}
> Log statements with the Exception:
> {noformat}
> Schema: root
>  |-- ID: string (nullable = false)
>  |-- TS: timestamp (nullable = true)
>  |-- DEVICE_ID: string (nullable = true)
>  |-- REPLACEMENT: string (nullable = true)
> {noformat}
> {noformat}
> == Physical Plan ==
> Filter (TS#1 < 1476861841934000)
> +- Scan JDBCRelation(jdbc:oracle:thin:@10.0.0.111:1521:orcl,ORATABLE,[Lorg.apache.spark.Partition;@78c74647,{user=user, password=pwd, url=jdbc:oracle:thin:@10.0.0.111:1521:orcl, dbtable=ORATABLE, driver=oracle.jdbc.driver.OracleDriver})[ID#0,TS#1,DEVICE_ID#2,REPLACEMENT#3] PushedFilters: [LessThan(TS,2016-10-19 12:54:01.934)]
> 2016-10-19 12:54:04,268 ERROR [Executor task launch worker-0] org.apache.spark.executor.Executor
> Exception in task 0.0 in stage 0.0 (TID 0)
> java.sql.SQLDataException: ORA-01861: literal does not match format string
> 	at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:461)
> 	at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:402)
> 	at oracle.jdbc.driver.T4C8Oall.processError(T4C8Oall.java:1065)
> 	at oracle.jdbc.driver.T4CTTIfun.receive(T4CTTIfun.java:681)
> 	at oracle.jdbc.driver.T4CTTIfun.doRPC(T4CTTIfun.java:256)
> 	at oracle.jdbc.driver.T4C8Oall.doOALL(T4C8Oall.java:577)
> 	at oracle.jdbc.driver.T4CPreparedStatement.doOall8(T4CPreparedStatement.java:239)
> 	at oracle.jdbc.driver.T4CPreparedStatement.doOall8(T4CPreparedStatement.java:75)
> 	at oracle.jdbc.driver.T4CPreparedStatement.executeForDescribe(T4CPreparedStatement.java:1043)
> 	at oracle.jdbc.driver.OracleStatement.executeMaybeDescribe(OracleStatement.java:1111)
> 	at oracle.jdbc.driver.OracleStatement.doExecuteWithTimeout(OracleStatement.java:1353)
> 	at oracle.jdbc.driver.OraclePreparedStatement.executeInternal(OraclePreparedStatement.java:4485)
> 	at oracle.jdbc.driver.OraclePreparedStatement.executeQuery(OraclePreparedStatement.java:4566)
> 	at oracle.jdbc.driver.OraclePreparedStatementWrapper.executeQuery(OraclePreparedStatementWrapper.java:5251)
> 	at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:383)
> 	at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:359)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> 	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:89)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	at java.lang.Thread.run(Thread.java:745)
> {noformat}


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