Details
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Bug
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Status: Resolved
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Major
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Resolution: Incomplete
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0.13.1
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None
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None
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None
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hive
Description
In a Group by heavy vectorized Reducer vertex 25% of CPU is spent in VectorizedBatchUtil.addRowToBatchFrom().
Looked at the code of VectorizedBatchUtil.addRowToBatchFrom and it looks like it wasn't optimized for Vectorized processing.
addRowToBatchFrom is called for every row and for each row and every column in the batch getPrimitiveCategory is called to figure the type of each column, column types are stored in a HashMap, for VectorGroupByOperator columns types won't change between batches, so column types shouldn't be looked up for every row.
I recommend storing the column type in StructObjectInspector so that other components can leverage this optimization.
Also addRowToBatchFrom has a case statement for every row and every column used for type casting I recommend encapsulating the type logic in templatized methods.
Stack Trace Sample Count Percentage(%) VectorizedBatchUtil.addRowToBatchFrom 86 26.543 AbstractPrimitiveObjectInspector.getPrimitiveCategory() 34 10.494 LazyBinaryStructObjectInspector.getStructFieldData 25 7.716 StandardStructObjectInspector.getStructFieldData 4 1.235
The query used :
select ss_sold_date_sk from store_sales where ss_sold_date between '1998-01-01' and '1998-06-01' group by ss_item_sk , ss_customer_sk , ss_sold_date_sk having sum(ss_list_price) > 50000000000000;
Attachments
Attachments
Issue Links
- is superceded by
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HIVE-9937 LLAP: Vectorized Field-By-Field Serialize / Deserialize to support new Vectorized Map Join
- Closed
- links to