[jira] [Created] (CARBONDATA-3422) fix missing complex dimensions when prepare the data from raw object

[Akash R Nilugal (Jira)]

lamber-ken created CARBONDATA-3422:
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             Summary: fix missing complex dimensions when prepare the data from raw object
                 Key: CARBONDATA-3422
                 URL: https://issues.apache.org/jira/browse/CARBONDATA-3422
             Project: CarbonData
          Issue Type: Bug
          Components: data-load, spark-integration
    Affects Versions: 1.5.3
            Reporter: lamber-ken
             Fix For: NONE


When use compact command for streaming table which contains complex column like array, it'll thow +ArrayIndexOutOfBoundsException.+

*Compact command*

 
{code:java}
ALTER TABLE streaming1.stream_table_filter_complex COMPACT 'close_streaming'
{code}
*Stackstrace*
{code:java}
java.lang.ArrayIndexOutOfBoundsException: 9
    at org.apache.carbondata.processing.loading.sort.SortStepRowHandler.packNoSortFieldsToBytes(SortStepRowHandler.java:808)
    at org.apache.carbondata.processing.loading.sort.SortStepRowHandler.writeRawRowAsIntermediateSortTempRowToOutputStream(SortStepRowHandler.java:481)
    at org.apache.carbondata.processing.sort.sortdata.SortDataRows.writeDataToFile(SortDataRows.java:244)
    at org.apache.carbondata.processing.sort.sortdata.SortDataRows.startSorting(SortDataRows.java:222)
    at org.apache.carbondata.processing.merger.CompactionResultSortProcessor.processResult(CompactionResultSortProcessor.java:257)
    at org.apache.carbondata.processing.merger.CompactionResultSortProcessor.execute(CompactionResultSortProcessor.java:175)
    at org.apache.carbondata.spark.rdd.StreamHandoffRDD.internalCompute(StreamHandoffRDD.scala:123)
    at org.apache.carbondata.spark.rdd.CarbonRDD.compute(CarbonRDD.scala:82)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(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:108)
{code}
 

 

 

 



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