I notice columns are quoted wit double quotes in the error message ('"user","age","state”)) . By chance did you override the MySQL JDBC dialect, default MySQL identifiers are quoted with ` override def quoteIdentifier(colName: String): String = { s"`$colName`" } Just wondering if the error you are running into is related to quotes.
Thanks -suresh > On Jan 26, 2017, at 1:28 AM, Didac Gil <didacg...@gmail.com> wrote: > > Are you sure that “age” is a numeric field? > > Even numeric, you could pass the “44” between quotes: > > INSERT into your_table ("user","age","state") VALUES ('user3’,’44','CT’) > > Are you sure there are no more fields that are specified as NOT NULL, and > that you did not provide a value (besides user, age and state)? > > >> On 26 Jan 2017, at 04:42, Xuan Dzung Doan <doanxuand...@yahoo.com.INVALID> >> wrote: >> >> Hi, >> >> Spark version 2.1.0 >> MySQL community server version 5.7.17 >> MySQL Connector Java 5.1.40 >> >> I need to save a dataframe to a MySQL table. In spark shell, the following >> statement succeeds: >> >> scala> df.write.mode(SaveMode.Append).format("jdbc").option("url", >> "jdbc:mysql://127.0.0.1:3306/mydb").option("dbtable", >> "person").option("user", "username").option("password", "password").save() >> >> I write an app that basically does the same thing, issuing the same >> statement saving the same dataframe to the same MySQL table. I run it using >> spark-submit, but it fails, reporting some error in the SQL syntax. Here's >> the detailed stack trace: >> >> 17/01/25 16:06:02 INFO DAGScheduler: Job 2 failed: save at >> DataIngestionJob.scala:119, took 0.159574 s >> Exception in thread "main" org.apache.spark.SparkException: Job aborted due >> to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: >> Lost task 0.0 in stage 2.0 (TID 3, localhost, executor driver): >> java.sql.BatchUpdateException: You have an error in your SQL syntax; check >> the manual that corresponds to your MySQL server version for the right >> syntax to use near '"user","age","state") VALUES ('user3',44,'CT')' at line 1 >> at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) >> at >> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) >> at >> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) >> at java.lang.reflect.Constructor.newInstance(Constructor.java:423) >> at com.mysql.jdbc.Util.handleNewInstance(Util.java:425) >> at com.mysql.jdbc.Util.getInstance(Util.java:408) >> at >> com.mysql.jdbc.SQLError.createBatchUpdateException(SQLError.java:1162) >> at >> com.mysql.jdbc.PreparedStatement.executeBatchSerially(PreparedStatement.java:1773) >> at >> com.mysql.jdbc.PreparedStatement.executeBatchInternal(PreparedStatement.java:1257) >> at com.mysql.jdbc.StatementImpl.executeBatch(StatementImpl.java:958) >> at >> org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:597) >> at >> org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:670) >> at >> org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:670) >> at >> org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:925) >> at >> org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:925) >> at >> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944) >> at >> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944) >> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) >> at org.apache.spark.scheduler.Task.run(Task.scala:99) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) >> at >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >> at java.lang.Thread.run(Thread.java:745) >> Caused by: com.mysql.jdbc.exceptions.jdbc4.MySQLSyntaxErrorException: You >> have an error in your SQL syntax; check the manual that corresponds to your >> MySQL server version for the right syntax to use near '"user","age","state") >> VALUES ('user3',44,'CT')' at line 1 >> at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) >> at >> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) >> at >> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) >> at java.lang.reflect.Constructor.newInstance(Constructor.java:423) >> at com.mysql.jdbc.Util.handleNewInstance(Util.java:425) >> at com.mysql.jdbc.Util.getInstance(Util.java:408) >> at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:943) >> at com.mysql.jdbc.MysqlIO.checkErrorPacket(MysqlIO.java:3970) >> at com.mysql.jdbc.MysqlIO.checkErrorPacket(MysqlIO.java:3906) >> at com.mysql.jdbc.MysqlIO.sendCommand(MysqlIO.java:2524) >> at com.mysql.jdbc.MysqlIO.sqlQueryDirect(MysqlIO.java:2677) >> at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2549) >> at >> com.mysql.jdbc.PreparedStatement.executeInternal(PreparedStatement.java:1861) >> at >> com.mysql.jdbc.PreparedStatement.executeUpdateInternal(PreparedStatement.java:2073) >> at >> com.mysql.jdbc.PreparedStatement.executeBatchSerially(PreparedStatement.java:1751) >> ... 15 more >> >> Driver stacktrace: >> at >> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422) >> at >> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) >> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) >> at >> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) >> at scala.Option.foreach(Option.scala:257) >> at >> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802) >> at >> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650) >> at >> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605) >> at >> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594) >> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) >> at >> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628) >> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918) >> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931) >> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944) >> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958) >> at >> org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:925) >> at >> org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:923) >> at >> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) >> at >> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) >> at org.apache.spark.rdd.RDD.withScope(RDD.scala:362) >> at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:923) >> at >> org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply$mcV$sp(Dataset.scala:2305) >> at >> org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2305) >> at >> org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2305) >> at >> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) >> at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765) >> at org.apache.spark.sql.Dataset.foreachPartition(Dataset.scala:2304) >> at >> org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.saveTable(JdbcUtils.scala:670) >> at >> org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:77) >> at >> org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:426) >> at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:215) >> at >> io.optics.analytics.dataingestion.DataIngestion.run(DataIngestionJob.scala:119) >> at >> io.optics.analytics.dataingestion.DataIngestionJob$.main(DataIngestionJob.scala:28) >> at >> io.optics.analytics.dataingestion.DataIngestionJob.main(DataIngestionJob.scala) >> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> at >> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) >> at >> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >> at java.lang.reflect.Method.invoke(Method.java:498) >> at >> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:738) >> at >> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187) >> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212) >> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126) >> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) >> >> Any idea why it's happening? A possible bug in spark? >> >> Thanks, >> Dzung. >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: user-unsubscr...@spark.apache.org >> > > > --------------------------------------------------------------------- > To unsubscribe e-mail: user-unsubscr...@spark.apache.org >