本文总结了几个本人在使用 Carbondata 的时候遇到的几个问题及其解决办法。这里使用的环境是：Spark 2.1.0、Carbondata 1.2.0。

必须指定 HDFS nameservices

在初始化 CarbonSession 的时候，如果不指定 HDFS nameservices，在数据导入是没啥问题的；但是数据查询会出现相关数据找不到问题： scala> val carbon = SparkSession.builder().tempnfig(sc.getConf).getOrCreateCarbonSession("hdfs:///user/iteblog/carb")

scala> carbon.sql("""CREATE TABLE temp.iteblog(id bigint) STORED BY 'carbondata'""")

17/11/09 16:20:58 AUDIT command.CreateTable: [www.iteblog.com][iteblog][Thread-1]Creating Table with Database name [temp] and Table name [iteblog]

17/11/09 16:20:58 WARN hive.HiveExternalCatalog: Couldn't find corresponding Hive SerDe for data source provider org.apache.spark.sql.CarbonSource. Persisting data source table `temp`.`iteblog` into Hive metastore in Spark SQL specific format, which is NOT tempmpatible with Hive.

17/11/09 16:20:59 AUDIT command.CreateTable: [www.iteblog.com][iteblog][Thread-1]Table created with Database name [temp] and Table name [iteblog]

res2: org.apache.spark.sql.DataFrame = []

scala> carbon.sql("insert overwrite table temp.iteblog select id from temp.mytable limit 10")

17/11/09 16:21:46 AUDIT rdd.CarbonDataRDDFactory$: [www.iteblog.com][iteblog][Thread-1]Data load request has been received for table temp.iteblog

17/11/09 16:21:46 WARN util.CarbonDataProcessorUtil: main sort scope is set to LOCAL_SORT

17/11/09 16:23:03 AUDIT rdd.CarbonDataRDDFactory$: [www.iteblog.com][iteblog][Thread-1]Data load is successful for temp.iteblog

res3: org.apache.spark.sql.DataFrame = []

scala> carbon.sql("select * from temp.iteblog limit 10").show(10,100)

17/11/09 16:23:15 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 3.0 (TID 1011, static.iteblog.com, executor 2): java.lang.RuntimeException: java.io.FileNotFoundException: /user/iteblog/carb/temp/iteblog/Fact/Part0/Segment_0/part-0-0_batchno0-0-1510215706696.carbondata (No such file or directory)

at org.apache.carbondata.tempre.indexstore.blockletindex.IndexWrapper.(IndexWrapper.java:39)

at org.apache.carbondata.tempre.scan.executor.impl.AbstractQueryExecutor.initQuery(AbstractQueryExecutor.java:141)

at org.apache.carbondata.tempre.scan.executor.impl.AbstractQueryExecutor.getBlockExecutionInfos(AbstractQueryExecutor.java:216)

at org.apache.carbondata.tempre.scan.executor.impl.VectorDetailQueryExecutor.execute(VectorDetailQueryExecutor.java:36)

at org.apache.carbondata.spark.vectorreader.VectorizedCarbonRetemprdReader.initialize(VectorizedCarbonRetemprdReader.java:116)

at org.apache.carbondata.spark.rdd.CarbonScanRDD.internalCompute(CarbonScanRDD.scala:229)

at org.apache.carbondata.spark.rdd.CarbonRDD.tempmpute(CarbonRDD.scala:62)

at org.apache.spark.rdd.RDD.tempmputeOrReadCheckpoint(RDD.scala:323)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)

at org.apache.spark.rdd.MapPartitionsRDD.tempmpute(MapPartitionsRDD.scala:38)

at org.apache.spark.rdd.RDD.tempmputeOrReadCheckpoint(RDD.scala:323)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)

at org.apache.spark.rdd.MapPartitionsRDD.tempmpute(MapPartitionsRDD.scala:38)

at org.apache.spark.rdd.RDD.tempmputeOrReadCheckpoint(RDD.scala:323)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)

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.tempncurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)

at java.util.tempncurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)

at java.lang.Thread.run(Thread.java:745)

Caused by: java.io.FileNotFoundException: /user/iteblog/carb/temp/iteblog/Fact/Part0/Segment_0/part-0-0_batchno0-0-1510215706696.carbondata (No such file or directory)

at java.io.FileInputStream.open(Native Method)

at java.io.FileInputStream.(FileInputStream.java:138)

at java.io.FileInputStream.(FileInputStream.java:93)

at org.apache.carbondata.tempre.datastore.impl.FileFactory.getDataInputStream(FileFactory.java:128)

at org.apache.carbondata.tempre.reader.ThriftReader.open(ThriftReader.java:77)

at org.apache.carbondata.tempre.reader.CarbonHeaderReader.readHeader(CarbonHeaderReader.java:46)

at org.apache.carbondata.tempre.util.DataFileFooterConverterV3.getSchema(DataFileFooterConverterV3.java:90)

at org.apache.carbondata.tempre.util.CarbonUtil.readMetadatFile(CarbonUtil.java:925)

at org.apache.carbondata.tempre.indexstore.blockletindex.IndexWrapper.(IndexWrapper.java:37)

... 20 more

可以看出，如果创建 CarbonSession 的时候，如果不指定 HDFS nameservices，在数据导入是没啥问题的；查找的时候就会出现文件找不到。这个最直接的解决版本就是创建 CarbonSession 的时候指定 HDFS nameservices。针对这个问题一个改进措施是让 Carbondata 能够根据提供的 hadoop 配置信息自动补充 HDFS nameservices 信息。

不支持 tinyint 数据类型 scala> carbon.sql("""CREATE TABLE temp.iteblog(status tinyint) STORED BY 'carbondata'""")

org.apache.carbondata.spark.exception.MalformedCarbonCommandException: Unsupported data type: StructField(status,ByteType,true).getType

at org.apache.spark.sql.parser.CarbonSpark2SqlParser$$anonfun$getFields$1.apply(CarbonSpark2SqlParser.scala:427)

at org.apache.spark.sql.parser.CarbonSpark2SqlParser$$anonfun$getFields$1.apply(CarbonSpark2SqlParser.scala:417)

at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)

at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)

at scala.collection.immutable.List.foreach(List.scala:381)

at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)

at scala.collection.immutable.List.map(List.scala:285)

at org.apache.spark.sql.parser.CarbonSpark2SqlParser.getFields(CarbonSpark2SqlParser.scala:417)

at org.apache.spark.sql.parser.CarbonSqlAstBuilder.visitCreateTable(CarbonSparkSqlParser.scala:135)

at org.apache.spark.sql.parser.CarbonSqlAstBuilder.visitCreateTable(CarbonSparkSqlParser.scala:72)

at org.apache.spark.sql.catalyst.parser.SqlBaseParser$CreateTableContext.accept(SqlBaseParser.java:578)

at org.antlr.v4.runtime.tree.AbstractParseTreeVisitor.visit(AbstractParseTreeVisitor.java:42)

at org.apache.spark.sql.catalyst.parser.AstBuilder$$anonfun$visitSingleStatement$1.apply(AstBuilder.scala:66)

at org.apache.spark.sql.catalyst.parser.AstBuilder$$anonfun$visitSingleStatement$1.apply(AstBuilder.scala:66)

at org.apache.spark.sql.catalyst.parser.ParserUtils$.withOrigin(ParserUtils.scala:93)

at org.apache.spark.sql.catalyst.parser.AstBuilder.visitSingleStatement(AstBuilder.scala:65)

at org.apache.spark.sql.catalyst.parser.AbstractSqlParser$$anonfun$parsePlan$1.apply(ParseDriver.scala:54)

at org.apache.spark.sql.catalyst.parser.AbstractSqlParser$$anonfun$parsePlan$1.apply(ParseDriver.scala:53)

at org.apache.spark.sql.catalyst.parser.AbstractSqlParser.parse(ParseDriver.scala:82)

at org.apache.spark.sql.parser.CarbonSparkSqlParser.parse(CarbonSparkSqlParser.scala:68)

at org.apache.spark.sql.catalyst.parser.AbstractSqlParser.parsePlan(ParseDriver.scala:53)

at org.apache.spark.sql.parser.CarbonSparkSqlParser.parsePlan(CarbonSparkSqlParser.scala:49)

at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)

... 50 elided

这是因为 Carbondata 目前不支持 tinyint 类型，Carbondata 目前支持的数据类型可以参见：http://carbondata.apache.org/supported-data-types-in-carbondata.html。但是奇怪的是 CARBONDATA-18 这里面已经解决了这个问题，不知道为啥到当前版本却不支持了。

添加分区出现NoSuchTableException

如果你使用 ALTER TABLE temp.iteblog ADD PARTITION('2017') 语句来添加分区，你会遇到下面的异常： scala> carbon.sql("ALTER TABLE temp.iteblog ADD PARTITION('2012')")

org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 'iteblog' not found in database 'default';

at org.apache.spark.sql.hive.client.HiveClient$$anonfun$getTable$1.apply(HiveClient.scala:76)

at org.apache.spark.sql.hive.client.HiveClient$$anonfun$getTable$1.apply(HiveClient.scala:76)

at scala.Option.getOrElse(Option.scala:121)

at org.apache.spark.sql.hive.client.HiveClient$class.getTable(HiveClient.scala:76)

at org.apache.spark.sql.hive.client.HiveClientImpl.getTable(HiveClientImpl.scala:78)

at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$org$apache$spark$sql$hive$HiveExternalCatalog$$getRawTable$1.apply(HiveExternalCatalog.scala:110)

at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$org$apache$spark$sql$hive$HiveExternalCatalog$$getRawTable$1.apply(HiveExternalCatalog.scala:110)

at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:95)

at org.apache.spark.sql.hive.HiveExternalCatalog.org$apache$spark$sql$hive$HiveExternalCatalog$$getRawTable(HiveExternalCatalog.scala:109)

at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$getTable$1.apply(HiveExternalCatalog.scala:601)

at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$getTable$1.apply(HiveExternalCatalog.scala:601)

at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:95)

at org.apache.spark.sql.hive.HiveExternalCatalog.getTable(HiveExternalCatalog.scala:600)

at org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation(HiveMetastoreCatalog.scala:106)

at org.apache.spark.sql.hive.HiveSessionCatalog.lookupRelation(HiveSessionCatalog.scala:69)

at org.apache.spark.sql.hive.CarbonSessionCatalog.lookupRelation(CarbonSessionState.scala:83)

at org.apache.spark.sql.internal.CatalogImpl.refreshTable(CatalogImpl.scala:461)

at org.apache.spark.sql.execution.command.AlterTableSplitPartitionCommand.processSchema(carbonTableSchema.scala:283)

at org.apache.spark.sql.execution.command.AlterTableSplitPartitionCommand.run(carbonTableSchema.scala:229)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:135)

at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)

at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)

at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)

at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:87)

at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:87)

at org.apache.spark.sql.Dataset.(Dataset.scala:185)

at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)

at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)

... 50 elided

运行上面的SQL语句，Carbondata 表相关的分区其实已经添加好了，但是通过 Spark 刷新表的相关信息就出错了。从出错的信息可以看出，虽然我们已经传递了表所在的 DB 相关信息，但是 Spark 的 catalyst 并没有获取到，这个 bug 是因为代码里面并没有将表数据相关信息传递给 catalyst， 这个 bug 还影响分区的 split 相关操作。不过此 bug 在 CARBONDATA-1593 里面已经解决。

insert overwrite 操作超过三次将会出现 NPE

如果你在导数的时候执行 insert overwrite 大于等于三次，那么恭喜你，你肯定会遇到下面的异常，如下： scala> carbon.sql("insert overwrite table temp.iteblog select id from co.order_common_p where dt = '2012-10'")

17/10/26 13:00:05 AUDIT rdd.CarbonDataRDDFactory$: [www.iteblog.com][iteblog][Thread-1]Data load request has been received for table temp.iteblog

17/10/26 13:00:05 WARN util.CarbonDataProcessorUtil: main sort scope is set to LOCAL_SORT

17/10/26 13:00:08 ERROR filesystem.AbstractDFSCarbonFile: main Exception occurred:File does not exist: hdfs://mycluster/user/iteblog/carb/temp/iteblog/Fact/Part0/Segment_0

17/10/26 13:00:09 ERROR command.LoadTable: main

java.lang.NullPointerException

at org.apache.carbondata.core.datastore.filesystem.AbstractDFSCarbonFile.isDirectory(AbstractDFSCarbonFile.java:88)

at org.apache.carbondata.core.util.CarbonUtil.deleteRecursive(CarbonUtil.java:364)

at org.apache.carbondata.core.util.CarbonUtil.access$100(CarbonUtil.java:93)

at org.apache.carbondata.core.util.CarbonUtil$2.run(CarbonUtil.java:326)

at org.apache.carbondata.core.util.CarbonUtil$2.run(CarbonUtil.java:322)

at java.security.AccessController.doPrivileged(Native Method)

at javax.security.auth.Subject.doAs(Subject.java:422)

at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491)

at org.apache.carbondata.core.util.CarbonUtil.deleteFoldersAndFiles(CarbonUtil.java:322)

at org.apache.carbondata.spark.load.CarbonLoaderUtil.recordLoadMetadata(CarbonLoaderUtil.java:333)

at org.apache.carbondata.spark.rdd.CarbonDataRDDFactory$.updateStatus$1(CarbonDataRDDFactory.scala:595)

at org.apache.carbondata.spark.rdd.CarbonDataRDDFactory$.loadCarbonData(CarbonDataRDDFactory.scala:1107)

at org.apache.spark.sql.execution.command.LoadTable.processData(carbonTableSchema.scala:1046)

at org.apache.spark.sql.execution.command.LoadTable.run(carbonTableSchema.scala:754)

at org.apache.spark.sql.execution.command.LoadTableByInsert.processData(carbonTableSchema.scala:651)

at org.apache.spark.sql.execution.command.LoadTableByInsert.run(carbonTableSchema.scala:637)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:135)

at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)

at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)

at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)

at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:87)

at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:87)

at org.apache.spark.sql.Dataset.(Dataset.scala:185)

at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)

at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)

at $line20.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.(:31)

at $line20.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.(:36)

at $line20.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.(:38)

at $line20.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw.(:40)

at $line20.$read$$iw$$iw$$iw$$iw$$iw$$iw.(:42)

at $line20.$read$$iw$$iw$$iw$$iw$$iw.(:44)

at $line20.$read$$iw$$iw$$iw$$iw.(:46)

at $line20.$read$$iw$$iw$$iw.(:48)

at $line20.$read$$iw$$iw.(:50)

at $line20.$read$$iw.(:52)

at $line20.$read.(:54)

at $line20.$read$.(:58)

at $line20.$read$.()

at $line20.$eval$.$print$lzycompute(:7)

at $line20.$eval$.$print(:6)

at $line20.$eval.$print()

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 scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786)

at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047)

at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:638)

at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:637)

at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31)

at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19)

at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637)

at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569)

at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)

at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807)

at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681)

at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395)

at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:415)

at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:923)

at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)

at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)

at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)

at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)

at org.apache.spark.repl.Main$.doMain(Main.scala:68)

at org.apache.spark.repl.Main$.main(Main.scala:51)

at org.apache.spark.repl.Main.main(Main.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)

17/10/26 13:00:09 AUDIT command.LoadTable: [www.iteblog.com][iteblog][Thread-1]Dataload failure for temp.iteblog. Please check the logs

java.lang.NullPointerException

at org.apache.carbondata.core.datastore.filesystem.AbstractDFSCarbonFile.isDirectory(AbstractDFSCarbonFile.java:88)

at org.apache.carbondata.core.util.CarbonUtil.deleteRecursive(CarbonUtil.java:364)

at org.apache.carbondata.core.util.CarbonUtil.access$100(CarbonUtil.java:93)

at org.apache.carbondata.core.util.CarbonUtil$2.run(CarbonUtil.java:326)

at org.apache.carbondata.core.util.CarbonUtil$2.run(CarbonUtil.java:322)

at java.security.AccessController.doPrivileged(Native Method)

at javax.security.auth.Subject.doAs(Subject.java:422)

at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491)

at org.apache.carbondata.core.util.CarbonUtil.deleteFoldersAndFiles(CarbonUtil.java:322)

at org.apache.carbondata.spark.load.CarbonLoaderUtil.recordLoadMetadata(CarbonLoaderUtil.java:333)

at org.apache.carbondata.spark.rdd.CarbonDataRDDFactory$.updateStatus$1(CarbonDataRDDFactory.scala:595)

at org.apache.carbondata.spark.rdd.CarbonDataRDDFactory$.loadCarbonData(CarbonDataRDDFactory.scala:1107)

at org.apache.spark.sql.execution.command.LoadTable.processData(carbonTableSchema.scala:1046)

at org.apache.spark.sql.execution.command.LoadTable.run(carbonTableSchema.scala:754)

at org.apache.spark.sql.execution.command.LoadTableByInsert.processData(carbonTableSchema.scala:651)

at org.apache.spark.sql.execution.command.LoadTableByInsert.run(carbonTableSchema.scala:637)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)

at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)

at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:135)

at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)

at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)

at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)

at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:87)

at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:87)

at org.apache.spark.sql.Dataset.(Dataset.scala:185)

at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)

at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)

... 50 elided

scala>

虽然出现 NPE 异常，但是数据其实已经导到 Carbondata 相关表里面了。引起这个异常的原因其实是因为每次执行完 insert overwrite 操作的时候，都需要删除之前的数据(也就是Segment目录)。但是 Segment 目录存在重复删除，导致找不到相关目录所以出现了 NPE 异常。这个问题在 CARBONDATA-1486 解决了。

不支持超过32767个字符的列

如果你有一列数据长度大于32767(Short.MaxValue)，并且 enable.unsafe.sort=true ，那么你往 Carbondata 表导数据的时候会出现异常，如下： java.lang.NegativeArraySizeException

at org.apache.carbondata.processing.newflow.sort.unsafe.UnsafeCarbonRowPage.getRow(UnsafeCarbonRowPage.java:182)

at org.apache.carbondata.processing.newflow.sort.unsafe.holder.UnsafeInmemoryHolder.readRow(UnsafeInmemoryHolder.java:63)

at org.apache.carbondata.processing.newflow.sort.unsafe.merger.UnsafeSingleThreadFinalSortFilesMerger.startSorting(UnsafeSingleThreadFinalSortFilesMerger.java:114)

at org.apache.carbondata.processing.newflow.sort.unsafe.merger.UnsafeSingleThreadFinalSortFilesMerger.startFinalMerge(UnsafeSingleThreadFinalSortFilesMerger.java:81)

at org.apache.carbondata.processing.newflow.sort.impl.UnsafeParallelReadMergeSorterImpl.sort(UnsafeParallelReadMergeSorterImpl.java:105)

at org.apache.carbondata.processing.newflow.steps.SortProcessorStepImpl.execute(SortProcessorStepImpl.java:62)

at org.apache.carbondata.processing.newflow.steps.DataWriterProcessorStepImpl.execute(DataWriterProcessorStepImpl.java:87)

at org.apache.carbondata.processing.newflow.DataLoadExecutor.execute(DataLoadExecutor.java:51)

at org.apache.carbondata.spark.rdd.NewDataFrameLoaderRDD$$anon$2.(NewCarbonDataLoadRDD.scala:442)

at org.apache.carbondata.spark.rdd.NewDataFrameLoaderRDD.internalCompute(NewCarbonDataLoadRDD.scala:405)

at org.apache.carbondata.spark.rdd.CarbonRDD.compute(CarbonRDD.scala:62)

at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)

这是 Carbondata 设计的缺陷，目前没有办法解决这个问题，不过可以实现一个类似于 varchar(size) 的数据类型。

日期格式错误导致数据丢失

如果你将带有日期类型的数据导入到 Carbondata 表中，可能会出现数据丢失： scala> carbon.sql("""CREATE TABLE temp.iteblog(dt DATE) STORED BY 'carbondata'""")

17/11/09 16:44:46 AUDIT temp.mand.CreateTable: [www.iteblog.com][iteblog][Thread-1]Creating Table with Database name [temp] and Table name [iteblog]

17/11/09 16:44:47 WARN hive.HiveExternalCatalog: Couldn't find temp.responding Hive SerDe for data source provider org.apache.spark.sql.CarbonSource. Persisting data source table `temp`.`iteblog` into Hive metastore in Spark SQL specific format, which is NOT temp.patible with Hive.

17/11/09 16:44:47 AUDIT temp.mand.CreateTable: [www.iteblog.com][iteblog][Thread-1]Table created with Database name [temp] and Table name [iteblog]

res1: org.apache.spark.sql.DataFrame = []

scala> carbon.sql("select dt from temp.mydate").show(10,100)

17/11/09 16:44:52 ERROR lzo.LzoCodec: Failed to load/initialize native-lzo library

+--------+

| dt|

+--------+

|20170509|

|20170511|

|20170507|

|20170504|

|20170502|

|20170506|

|20170501|

|20170508|

|20170510|

|20170505|

+--------+

only showing top 10 rows

scala> carbon.sql("insert into table temp.iteblog select dt from temp.mydate limit 10")

17/11/09 16:45:14 AUDIT rdd.CarbonDataRDDFactory$: [www.iteblog.com][iteblog][Thread-1]Data load request has been received for table temp.iteblog

17/11/09 16:45:14 WARN util.CarbonDataProcessorUtil: main sort scope is set to LOCAL_SORT

17/11/09 16:45:16 AUDIT rdd.CarbonDataRDDFactory$: [www.iteblog.com][iteblog][Thread-1]Data load is successful for temp.iteblog

res3: org.apache.spark.sql.DataFrame = []

scala> carbon.sql("select * from temp.iteblog limit 10").show(10,100)

+----+

| dt|

+----+

|null|

|null|

|null|

|null|

|null|

|null|

|null|

|null|

|null|

|null|

+----+

这是因为 Carbondata 对数据类型(DATE)有默认的格式，由参数 carbon.date.format 控制，默认值是 yyyy-MM-dd。所以你使用 yyyy-MM-dd 格式去解析 20170505 数据肯定会出现错误，从而导致数据丢失了。同理，时间戳类型(TIMESTAMP) 也有默认的格式，由参数 carbon.timestamp.format 空值，默认值为 yyyy-MM-dd HH:mm:ss。