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Kostas papageorgopoulos commented on SPARK-10909: ------------------------------------------------- I will test it in the first chance and let you know if this patch worked ok > Spark sql jdbc fails for Oracle NUMBER type columns > --------------------------------------------------- > > Key: SPARK-10909 > URL: https://issues.apache.org/jira/browse/SPARK-10909 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 1.5.1 > Environment: Dev > Reporter: Kostas papageorgopoulos > Priority: Minor > Labels: jdbc, newbie, sql > > When using spark sql to connect to Oracle and run a spark sql query i get the > following exception "requirement failed: Overflowed precision" This is > triggered when in the dbTable definition it is included an Oracle NUMBER > column > {code} > SQLContext sqlContext = new SQLContext(sc); > Map<String, String> options = new HashMap<>(); > options.put("driver", "oracle.jdbc.OracleDriver"); > options.put("user", "USER"); > options.put("password", "PASS"); > options.put("url", "ORACLE CONNECTINO URL"); > options.put("dbtable", "(select VARCHAR_COLUMN > ,TIMESTAMP_COLUMN,NUMBER_COLUMN from lsc_subscription_profiles)"); > DataFrame jdbcDF = > sqlContext.read().format("jdbc").options(options).load(); > jdbcDF.toJavaRDD().saveAsTextFile("hdfs://hdfshost:8020" + > "/path/to/write.bz2", BZip2Codec.class); > {code} > using driver > {code} > <groupId>com.oracle</groupId> > <artifactId>ojdbc6</artifactId> > <version>11.2.0.3.0</version> > <!--<scope>runtime</scope>--> > </dependency> > {code} > Using java sun java jdk 1.8.51 along with spring4 > The classpath of the junit run is > {code} > /home/kostas/dev2/tools/jdk1.8.0_51/bin/java > -agentlib:jdwp=transport=dt_socket,address=127.0.0.1:42901,suspend=y,server=n > -ea -Duser.timezone=Africa/Cairo -Dfile.encoding=UTF-8 -classpath > 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/sun/jersey/contribs/jersey-guice/1.9/jersey-guice-1.9.jar:/home/kostas/.m2/repository/org/apache/hadoop/hadoop-distcp/2.6.0/hadoop-distcp-2.6.0.jar:/home/kostas/.m2/repository/org/springframework/spring-messaging/4.1.6.RELEASE/spring-messaging-4.1.6.RELEASE.jar:/home/kostas/.m2/repository/org/kitesdk/kite-data-core/1.0.0/kite-data-core-1.0.0.jar:/home/kostas/.m2/repository/org/kitesdk/kite-hadoop-compatibility/1.0.0/kite-hadoop-compatibility-1.0.0.jar:/home/kostas/.m2/repository/com/twitter/parquet-avro/1.4.1/parquet-avro-1.4.1.jar:/home/kostas/.m2/repository/com/twitter/parquet-column/1.4.1/parquet-column-1.4.1.jar:/home/kostas/.m2/repository/com/twitter/parquet-common/1.4.1/parquet-common-1.4.1.jar:/home/kostas/.m2/repository/com/twitter/parquet-encoding/1.4.1/parquet-encoding-1.4.1.jar:/home/kostas/.m2/repository/com/twitter/parquet-generator/1.4.1/parquet-generator-1.4.1.jar:/home/kostas/.m2/repository/com/twitter/parquet-hadoop/1.4.1/parquet-hadoop-1.4.1.jar:/home/kostas/.m2/repository/com/twitter/parquet-jackson/1.4.1/parquet-jackson-1.4.1.jar:/home/kostas/.m2/repository/com/twitter/parquet-format/2.0.0/parquet-format-2.0.0.jar:/home/kostas/.m2/repository/net/sf/opencsv/opencsv/2.3/opencsv-2.3.jar:/home/kostas/.m2/repository/org/apache/commons/commons-jexl/2.1.1/commons-jexl-2.1.1.jar:/home/kostas/.m2/repository/org/apache/hadoop/hadoop-streaming/2.6.0/hadoop-streaming-2.6.0.jar:/home/kostas/.m2/repository/org/mybatis/mybatis-spring/1.2.3/mybatis-spring-1.2.3.jar:/home/kostas/.m2/repository/org/mybatis/mybatis/3.3.0/mybatis-3.3.0.jar:/home/kostas/.m2/repository/org/mvel/mvel2/2.2.6.Final/mvel2-2.2.6.Final.jar:/home/kostas/.m2/repository/org/aspectj/aspectjrt/1.8.7/aspectjrt-1.8.7.jar:/home/kostas/.m2/repository/org/aspectj/aspectjweaver/1.8.7/aspectjweaver-1.8.7.jar:/home/kostas/.m2/repository/com/zaxxer/HikariCP/2.4.1/HikariCP-2.4.1.jar:/home/kostas/.m2/repository/com/oracle/ojdbc6/11.2.0.3.0/ojdbc6-11.2.0.3.0.jar:/home/kostas/.m2/repository/net/sf/ehcache/ehcache/2.10.0/ehcache-2.10.0.jar:/home/kostas/.m2/repository/org/quartz-scheduler/quartz/2.2.1/quartz-2.2.1.jar:/home/kostas/.m2/repository/c3p0/c3p0/0.9.1.1/c3p0-0.9.1.1.jar > com.intellij.rt.execution.junit.JUnitStarter -ideVersion5 > {code} > > The stacktrace > {code} > g.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in > stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 > (TID 3, 10.130.35.52): java.lang.IllegalArgumentException: requirement > failed: Overflowed precision > at scala.Predef$.require(Predef.scala:233) > at org.apache.spark.sql.types.Decimal.set(Decimal.scala:111) > at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:335) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.getNext(JDBCRDD.scala:406) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.hasNext(JDBCRDD.scala:472) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply$mcV$sp(PairRDDFunctions.scala:1108) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1108) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1108) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1206) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1116) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1095) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > at org.apache.spark.scheduler.Task.run(Task.scala:88) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1280) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1268) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1267) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1267) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > at scala.Option.foreach(Option.scala:236) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1493) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1455) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1444) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1813) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1826) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scala:1124) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1065) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1065) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:306) > at > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1065) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply$mcV$sp(PairRDDFunctions.scala:989) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply(PairRDDFunctions.scala:965) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply(PairRDDFunctions.scala:965) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:306) > at > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:965) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$3.apply$mcV$sp(PairRDDFunctions.scala:951) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$3.apply(PairRDDFunctions.scala:951) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$3.apply(PairRDDFunctions.scala:951) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:306) > at > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:950) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$2.apply$mcV$sp(PairRDDFunctions.scala:909) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$2.apply(PairRDDFunctions.scala:907) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$2.apply(PairRDDFunctions.scala:907) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:306) > at > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:907) > at > org.apache.spark.rdd.RDD$$anonfun$saveAsTextFile$2.apply$mcV$sp(RDD.scala:1444) > at > org.apache.spark.rdd.RDD$$anonfun$saveAsTextFile$2.apply(RDD.scala:1432) > at > org.apache.spark.rdd.RDD$$anonfun$saveAsTextFile$2.apply(RDD.scala:1432) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:306) > at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1432) > at > org.apache.spark.api.java.JavaRDDLike$class.saveAsTextFile(JavaRDDLike.scala:530) > at > org.apache.spark.api.java.AbstractJavaRDDLike.saveAsTextFile(JavaRDDLike.scala:47) > at > velti.tech.reporting.test.commons.spark.jdbc.TestRunSparkJdbcJob.testRunSqlDirectlyOnJDBC(TestRunSparkJdbcJob.java:56) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at > org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50) > at > org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12) > at > org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47) > at > org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17) > at > org.springframework.test.context.junit4.statements.RunBeforeTestMethodCallbacks.evaluate(RunBeforeTestMethodCallbacks.java:74) > at > org.springframework.test.context.junit4.statements.RunAfterTestMethodCallbacks.evaluate(RunAfterTestMethodCallbacks.java:85) > at > org.springframework.test.context.junit4.statements.SpringRepeat.evaluate(SpringRepeat.java:86) > at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325) > at > org.springframework.test.context.junit4.SpringJUnit4ClassRunner.runChild(SpringJUnit4ClassRunner.java:241) > at > org.springframework.test.context.junit4.SpringJUnit4ClassRunner.runChild(SpringJUnit4ClassRunner.java:87) > at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290) > at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71) > at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288) > at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58) > at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268) > at > org.springframework.test.context.junit4.statements.RunBeforeTestClassCallbacks.evaluate(RunBeforeTestClassCallbacks.java:61) > at > org.springframework.test.context.junit4.statements.RunAfterTestClassCallbacks.evaluate(RunAfterTestClassCallbacks.java:70) > at org.junit.runners.ParentRunner.run(ParentRunner.java:363) > at > org.springframework.test.context.junit4.SpringJUnit4ClassRunner.run(SpringJUnit4ClassRunner.java:180) > at org.junit.runner.JUnitCore.run(JUnitCore.java:137) > at > com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:78) > at > com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:212) > at > com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStarter.java:68) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at com.intellij.rt.execution.application.AppMain.main(AppMain.java:140) > Caused by: java.lang.IllegalArgumentException: requirement failed: Overflowed > precision > at scala.Predef$.require(Predef.scala:233) > at org.apache.spark.sql.types.Decimal.set(Decimal.scala:111) > at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:335) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.getNext(JDBCRDD.scala:406) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.hasNext(JDBCRDD.scala:472) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply$mcV$sp(PairRDDFunctions.scala:1108) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1108) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1108) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1206) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1116) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1095) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > at org.apache.spark.scheduler.Task.run(Task.scala:88) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > 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) > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) 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