[CARBONDATA-2741] Exception occurs after alter add few columns and selecting in random order

• Type: Bug
• Status: Resolved
• Priority: Minor
• Resolution: Fixed
• Affects Version/s: 1.5.0
• Fix Version/s: 1.4.1
• Component/s: spark-integration
• Environment: 3 node cluster with spark2.2
• Assignee: Jatin
• Reporter: Jatin
• Created: 13/Jul/18 15:26
• Updated: 18/Jul/18 12:12
• Resolved: 18/Jul/18 12:12

Description

create table tb1 (imei string,AMSize string,channelsId string,ActiveCountry string, Activecity string,gamePointId double,deviceInformationId double,productionDate Timestamp,deliveryDate timestamp,deliverycharge double) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('table_blocksize'='1','COLUMN_META_CACHE'='AMSize');

 LOAD DATA INPATH 'hdfs://hacluster/csv/vardhandaterestruct.csv' INTO TABLE tb1 OPTIONS('DELIMITER'=',', 'QUOTECHAR'= '"','BAD_RECORDS_ACTION'='FORCE','FILEHEADER'= 'imei,deviceInformationId,AMSize,channelsId,ActiveCountry,Activecity,gamePointId,productionDate,deliveryDate,deliverycharge');

alter table tb1 add columns(age int, name string);

select * from tb1 where name is NULL or channelsId =4;

Exception occurs :

Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 6508.0 failed 4 times, most recent failure: Lost task 0.3 in stage 6508.0 (TID 140476, linux-49, executor 3): java.lang.RuntimeException: internal error: org.apache.carbondata.core.datastore.page.encoding.adaptive.AdaptiveFloatingCodec[src type: DOUBLE, target type: INT, stats(min: 1.0, max: 1000000.0, decimal: 1 )]
 at org.apache.carbondata.core.datastore.page.encoding.adaptive.AdaptiveFloatingCodec$3.decodeLong(AdaptiveFloatingCodec.java:185)
 at org.apache.carbondata.core.datastore.page.LazyColumnPage.getLong(LazyColumnPage.java:64)
 at org.apache.carbondata.core.scan.result.vector.MeasureDataVectorProcessor$IntegralMeasureVectorFiller.fillMeasureVector(MeasureDataVectorProcessor.java:73)
 at org.apache.carbondata.core.scan.result.impl.FilterQueryScannedResult.fillColumnarMeasureBatch(FilterQueryScannedResult.java:129)
 at org.apache.carbondata.core.scan.collector.impl.DictionaryBasedVectorResultCollector.fillResultToColumnarBatch(DictionaryBasedVectorResultCollector.java:167)
 at org.apache.carbondata.core.scan.collector.impl.RestructureBasedVectorResultCollector.collectResultInColumnarBatch(RestructureBasedVectorResultCollector.java:127)
 at org.apache.carbondata.core.scan.processor.DataBlockIterator.processNextBatch(DataBlockIterator.java:245)
 at org.apache.carbondata.core.scan.result.iterator.VectorDetailQueryResultIterator.processNextBatch(VectorDetailQueryResultIterator.java:48)
 at org.apache.carbondata.spark.vectorreader.VectorizedCarbonRecordReader.nextBatch(VectorizedCarbonRecordReader.java:290)
 at org.apache.carbondata.spark.vectorreader.VectorizedCarbonRecordReader.nextKeyValue(VectorizedCarbonRecordReader.java:180)
 at org.apache.carbondata.spark.rdd.CarbonScanRDD$$anon$1.hasNext(CarbonScanRDD.scala:497)
 at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.scan_nextBatch$(Unknown Source)
 at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
 at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
 at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:381)
 at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
 at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
 at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:381)
 at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231)
 at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225)
 at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:828)
 at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:828)
 at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
 at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
 at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
 at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
 at org.apache.spark.scheduler.Task.run(Task.scala:99)
 at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:325)
 at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
 at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
 at java.lang.Thread.run(Thread.java:748)

Driver stacktrace: (state=,code=0)