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[HOTFIX-compatibility] Handle Lazy loading with inverted index for ColumnarVectorWrapperDirectWithInvertedIndex #2870
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@kumarvishal09 : please reveiw |
Build Success with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder2.1/1108/ |
Build Success with Spark 2.2.1, Please check CI http://95.216.28.178:8080/job/ApacheCarbonPRBuilder1/1319/ |
Build Success with Spark 2.3.1, Please check CI http://136.243.101.176:8080/job/carbondataprbuilder2.3/9373/ |
@ravipesala : please review It has adaptive encoding compatibility fix also |
Build Success with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder2.1/1129/ |
Build Success with Spark 2.2.1, Please check CI http://95.216.28.178:8080/job/ApacheCarbonPRBuilder1/1340/ |
Build Success with Spark 2.3.1, Please check CI http://136.243.101.176:8080/job/carbondataprbuilder2.3/9393/ |
LGTM |
1 similar comment
LGTM |
…lumnarVectorWrapperDirectWithInvertedIndex Problem: Create a store with 1.4 code with inverted index and read it with vector filling (latest master code). below exception will be thrown from AbstractCarbonColumnarVector. UnsupportedOperationException("Not allowed from here " + getClass().getName()); cause: when the lazy loading with an inverted index, getBlockDataType() was not implemented for ColumnarVectorWrapperDirectWithInvertedIndex. So, Added implementation. This closes #2870
Problem:
Create a store with 1.4 code with inverted index and read it with vector filling (latest master code).
below exception will be thrown from AbstractCarbonColumnarVector.
UnsupportedOperationException("Not allowed from here " + getClass().getName());
cause:
when the lazy loading with an inverted index,
getBlockDataType() was not implemented for ColumnarVectorWrapperDirectWithInvertedIndex.
So, Added implementation.
Be sure to do all of the following checklist to help us incorporate
your contribution quickly and easily:
Any interfaces changed? NA
Any backward compatibility impacted? NA
Document update required? NA
Testing done
yes.
For large changes, please consider breaking it into sub-tasks under an umbrella JIRA. NA