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Posted to issues@spark.apache.org by "Suhas Nalapure (JIRA)" <ji...@apache.org> on 2016/10/19 07:43:58 UTC
[jira] [Created] (SPARK-18004) DataFrame filter Predicate push-down
fails for Oracle Timestamp type columns
Suhas Nalapure created SPARK-18004:
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Summary: 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) :
---------------------------------------------------------------------------------------
//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();
Log statements with the Exception:
--------------------------------------------
Schema: root
|-- ID: string (nullable = false)
|-- TS: timestamp (nullable = true)
|-- DEVICE_ID: string (nullable = true)
|-- REPLACEMENT: string (nullable = true)
== 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)
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