[ https://issues.apache.org/jira/browse/SPARK-21360?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
feroz khan updated SPARK-21360: ------------------------------- Description: I have a table on table on Microsoft SQL server ======================================================= CREATE TABLE [dbo].[aircraftdata]( [ID] [float] NULL, [SN] [float] NULL, [F1] [float] NULL, [F 2] [float] NULL, ) ON [PRIMARY] GO ================================================================= I have a scala component that take data integration request in form of xml and create an sql query to fetch data. Suppose i want to read column "ID" and "F 2" , generated query is - SELECT `id` AS `p_id` , `F 2` AS `p_F2` FROM Maqplex_IrisDataset_aircraftdata WHERE Maqplex_IrisDataset_aircraftdata.`F 2` = '.001' this fails with error - org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): com.microsoft.sqlserver.jdbc.SQLServerException: Incorrect syntax near '2'. at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:216) at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1515) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatement(SQLServerPreparedStatement.java:404) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecCmd.doExecute(SQLServerPreparedStatement.java:350) at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:5696) at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:1715) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:180) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:155) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeQuery(SQLServerPreparedStatement.java:285) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:408) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:379) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39) at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2193) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199) at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1935) at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1934) at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2576) at org.apache.spark.sql.Dataset.head(Dataset.scala:1934) at org.apache.spark.sql.Dataset.take(Dataset.scala:2149) at org.apache.spark.sql.Dataset.showString(Dataset.scala:239) at org.apache.spark.sql.Dataset.show(Dataset.scala:526) at org.apache.spark.sql.Dataset.show(Dataset.scala:486) at org.apache.spark.sql.Dataset.show(Dataset.scala:495) at org.pangea.translation.core.PangeaTranslationCore$.runMainTranslation(PangeaTranslationCore.scala:92) at org.pangea.translation.core.PangeaTranslationCore$.run(PangeaTranslationCore.scala:55) at org.pangea.translation.api.DataTranslationAPI$.main(DataTranslation.scala:33) at org.pangea.translation.api.DataTranslationAPI.main(DataTranslation.scala) Caused by: com.microsoft.sqlserver.jdbc.SQLServerException: Incorrect syntax near '2'. at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:216) at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1515) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatement(SQLServerPreparedStatement.java:404) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecCmd.doExecute(SQLServerPreparedStatement.java:350) at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:5696) at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:1715) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:180) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:155) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeQuery(SQLServerPreparedStatement.java:285) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:408) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:379) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) I cannot use square brackets in place for backticks (for sql server compatibility) because that is incompatible with spark sql. If i create a similar dataframe on a text file it work properly. var dataset = session.sqlContext.read.format("com.databricks.spark.csv").option("header","true").load("D:\\PangeaProduct\\Deployment\\data\\FPGrowthData\\BMS1.csv")//.schema(schemasave) dataset.show(10) dataset.registerTempTable("transaction") var dataset1 = session.sqlContext.sql("select * from transaction where transaction.`transaction id` = 28") dataset1.show(10) Any help on this issue welcome :) was: I have a table on table on SQL server ======================================================= CREATE TABLE [dbo].[aircraftdata]( [ID] [float] NULL, [SN] [float] NULL, [F1] [float] NULL, [F 2] [float] NULL, ) ON [PRIMARY] GO ================================================================= I have a scala component that take data integration request in form of xml and create an sql query to fetch data. Suppose i want to read column "ID" and "F 2" and generate query as - SELECT `id` AS `p_id` , `F 2` AS `p_F2` FROM Maqplex_IrisDataset_aircraftdata WHERE Maqplex_IrisDataset_aircraftdata.`F 2` = '.001' this fails with error - org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): com.microsoft.sqlserver.jdbc.SQLServerException: Incorrect syntax near '2'. at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:216) at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1515) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatement(SQLServerPreparedStatement.java:404) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecCmd.doExecute(SQLServerPreparedStatement.java:350) at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:5696) at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:1715) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:180) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:155) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeQuery(SQLServerPreparedStatement.java:285) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:408) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:379) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39) at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2193) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199) at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1935) at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1934) at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2576) at org.apache.spark.sql.Dataset.head(Dataset.scala:1934) at org.apache.spark.sql.Dataset.take(Dataset.scala:2149) at org.apache.spark.sql.Dataset.showString(Dataset.scala:239) at org.apache.spark.sql.Dataset.show(Dataset.scala:526) at org.apache.spark.sql.Dataset.show(Dataset.scala:486) at org.apache.spark.sql.Dataset.show(Dataset.scala:495) at org.pangea.translation.core.PangeaTranslationCore$.runMainTranslation(PangeaTranslationCore.scala:92) at org.pangea.translation.core.PangeaTranslationCore$.run(PangeaTranslationCore.scala:55) at org.pangea.translation.api.DataTranslationAPI$.main(DataTranslation.scala:33) at org.pangea.translation.api.DataTranslationAPI.main(DataTranslation.scala) Caused by: com.microsoft.sqlserver.jdbc.SQLServerException: Incorrect syntax near '2'. at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:216) at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1515) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatement(SQLServerPreparedStatement.java:404) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecCmd.doExecute(SQLServerPreparedStatement.java:350) at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:5696) at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:1715) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:180) at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:155) at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeQuery(SQLServerPreparedStatement.java:285) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:408) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:379) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) I cannot use square brackets in place for backticks (for sql server compatibility) because that is incompatible with spark sql. If i create a similar dataframe on a text file it work properly. var dataset = session.sqlContext.read.format("com.databricks.spark.csv").option("header","true").load("D:\\PangeaProduct\\Deployment\\data\\FPGrowthData\\BMS1.csv")//.schema(schemasave) dataset.show(10) dataset.registerTempTable("transaction") var dataset1 = session.sqlContext.sql("select * from transaction where transaction.`transaction id` = 28") dataset1.show(10) Any help on this issue welcome :) > Spark failing to query SQL Server. Query contains a column having space in > where clause > ----------------------------------------------------------------------------------------- > > Key: SPARK-21360 > URL: https://issues.apache.org/jira/browse/SPARK-21360 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.0.0 > Reporter: feroz khan > > I have a table on table on Microsoft SQL server > ======================================================= > CREATE TABLE [dbo].[aircraftdata]( > [ID] [float] NULL, > [SN] [float] NULL, > [F1] [float] NULL, > [F 2] [float] NULL, > > ) ON [PRIMARY] > GO > ================================================================= > I have a scala component that take data integration request in form of xml > and create an sql query to fetch data. Suppose i want to read column "ID" and > "F 2" , generated query is - > SELECT `id` AS `p_id` , `F 2` AS `p_F2` FROM Maqplex_IrisDataset_aircraftdata > WHERE Maqplex_IrisDataset_aircraftdata.`F 2` = '.001' > this fails with error - > org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in > stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 > (TID 0, localhost): com.microsoft.sqlserver.jdbc.SQLServerException: > Incorrect syntax near '2'. > at > com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:216) > at > com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1515) > at > com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatement(SQLServerPreparedStatement.java:404) > at > com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecCmd.doExecute(SQLServerPreparedStatement.java:350) > at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:5696) > at > com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:1715) > at > com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:180) > at > com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:155) > at > com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeQuery(SQLServerPreparedStatement.java:285) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:408) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:379) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:86) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > at java.lang.Thread.run(Thread.java:745) > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) > at scala.Option.foreach(Option.scala:257) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916) > at > org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347) > at > org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39) > at > org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2193) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) > at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546) > at > org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192) > at > org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199) > at > org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1935) > at > org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1934) > at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2576) > at org.apache.spark.sql.Dataset.head(Dataset.scala:1934) > at org.apache.spark.sql.Dataset.take(Dataset.scala:2149) > at org.apache.spark.sql.Dataset.showString(Dataset.scala:239) > at org.apache.spark.sql.Dataset.show(Dataset.scala:526) > at org.apache.spark.sql.Dataset.show(Dataset.scala:486) > at org.apache.spark.sql.Dataset.show(Dataset.scala:495) > at > org.pangea.translation.core.PangeaTranslationCore$.runMainTranslation(PangeaTranslationCore.scala:92) > at > org.pangea.translation.core.PangeaTranslationCore$.run(PangeaTranslationCore.scala:55) > at > org.pangea.translation.api.DataTranslationAPI$.main(DataTranslation.scala:33) > at > org.pangea.translation.api.DataTranslationAPI.main(DataTranslation.scala) > Caused by: com.microsoft.sqlserver.jdbc.SQLServerException: Incorrect syntax > near '2'. > at > com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:216) > at > com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1515) > at > com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatement(SQLServerPreparedStatement.java:404) > at > com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecCmd.doExecute(SQLServerPreparedStatement.java:350) > at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:5696) > at > com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:1715) > at > com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:180) > at > com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:155) > at > com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeQuery(SQLServerPreparedStatement.java:285) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:408) > at > org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:379) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:86) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > at java.lang.Thread.run(Thread.java:745) > I cannot use square brackets in place for backticks (for sql server > compatibility) because that is incompatible with spark sql. > If i create a similar dataframe on a text file it work properly. > var dataset = > session.sqlContext.read.format("com.databricks.spark.csv").option("header","true").load("D:\\PangeaProduct\\Deployment\\data\\FPGrowthData\\BMS1.csv")//.schema(schemasave) > dataset.show(10) > dataset.registerTempTable("transaction") > var dataset1 = session.sqlContext.sql("select * from transaction where > transaction.`transaction id` = 28") > dataset1.show(10) > Any help on this issue welcome :) > -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org