[GitHub] [carbondata] akashrn5 commented on a change in pull request #3935: [CARBONDATA-3993] Remove auto data deletion in IUD processs

2020-10-15 Thread GitBox 


akashrn5 commented on a change in pull request #3935:
URL: https://github.com/apache/carbondata/pull/3935#discussion_r505226878



##
File path: 
integration/spark/src/main/scala/org/apache/spark/sql/execution/command/mutation/CarbonProjectForDeleteCommand.scala
##
@@ -149,14 +149,10 @@ private[sql] case class CarbonProjectForDeleteCommand(
   case e: HorizontalCompactionException =>
 LOGGER.error("Delete operation passed. Exception in Horizontal 
Compaction." +
  " Please check logs. " + e.getMessage)
-CarbonUpdateUtil.cleanStaleDeltaFiles(carbonTable, 
e.compactionTimeStamp.toString)
 Seq(Row(0L))
 
   case e: Exception =>
 LOGGER.error("Exception in Delete data operation " + e.getMessage, e)
-// ** start clean up.

Review comment:
   i dont think we can remove this directly, it might create problem, as 
mentioned in comments

##
File path: 
integration/spark/src/main/scala/org/apache/spark/sql/execution/command/mutation/DeleteExecution.scala
##
@@ -374,8 +374,6 @@ object DeleteExecution {
   blockMappingVO.getSegmentNumberOfBlockMapping)
   }
 } else {
-  // In case of failure , clean all related delete delta files
-  CarbonUpdateUtil.cleanStaleDeltaFiles(carbonTable, timestamp)

Review comment:
   same as above





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[GitHub] [carbondata] akashrn5 commented on a change in pull request #3935: [CARBONDATA-3993] Remove auto data deletion in IUD processs

2020-10-11 Thread GitBox 


akashrn5 commented on a change in pull request #3935:
URL: https://github.com/apache/carbondata/pull/3935#discussion_r503037126



##
File path: 
integration/spark/src/main/scala/org/apache/carbondata/spark/rdd/CarbonDataRDDFactory.scala
##
@@ -267,9 +266,8 @@ object CarbonDataRDDFactory {
 throw new Exception("Exception in compaction " + 
exception.getMessage)
   }
 } finally {
-  executor.shutdownNow()
   try {
-compactor.deletePartialLoadsInCompaction()

Review comment:
   @Pickupolddriver We cannot remove the clean stale files in case of 
IUD and wait for clean files command to clean them, we should immediately clean 
the stale ones in the respective command itself, as there will be chances of 
extra data or data inconsistency. @QiangCai we can avoid this may be once we 
implement the writing the update data to new segment and writing only the 
delete delta files to the updated segment.





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[GitHub] [carbondata] akashrn5 commented on a change in pull request #3935: [CARBONDATA-3993] Remove auto data deletion in IUD processs

2020-10-11 Thread GitBox 


akashrn5 commented on a change in pull request #3935:
URL: https://github.com/apache/carbondata/pull/3935#discussion_r503037126



##
File path: 
integration/spark/src/main/scala/org/apache/carbondata/spark/rdd/CarbonDataRDDFactory.scala
##
@@ -267,9 +266,8 @@ object CarbonDataRDDFactory {
 throw new Exception("Exception in compaction " + 
exception.getMessage)
   }
 } finally {
-  executor.shutdownNow()
   try {
-compactor.deletePartialLoadsInCompaction()

Review comment:
   > We cannot remove the clean stale files in case of IUD and wait for 
clean files command to clean them, we should immediately clean the stale ones 
in the respective command itself, as there will be chances of extra data or 
data inconsistency. 





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[GitHub] [carbondata] akashrn5 commented on a change in pull request #3935: [CARBONDATA-3993] Remove auto data deletion in IUD processs

2020-10-11 Thread GitBox 


akashrn5 commented on a change in pull request #3935:
URL: https://github.com/apache/carbondata/pull/3935#discussion_r503036710



##
File path: 
integration/spark/src/main/scala/org/apache/carbondata/spark/rdd/CarbonDataRDDFactory.scala
##
@@ -267,9 +266,8 @@ object CarbonDataRDDFactory {
 throw new Exception("Exception in compaction " + 
exception.getMessage)
   }
 } finally {
-  executor.shutdownNow()
   try {
-compactor.deletePartialLoadsInCompaction()

Review comment:
   @QiangCai how its handled now, without list files? why cant we do list 
files with the timestamp filter, which is load timestamp/fact timestamp, we can 
get from load model or somewhere right?





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