Hi dev,
Please help review this PR
https://github.com/apache/incubator-carbondata/pull/716It can improve performance of queries with below pre-condition:
— No Sort
— No Filters(Where clause)
— No Having(a special Filter)
— Has Group by
— Has Limit
For example :
Select A, B, C, sum(D)
From t3
Group by A, B, C
Limit n
The solution is to convert limit condition as Filters. It take the advantage of CarbonData Dictionary files to get the distinct value list and generate the filters so that we can reduce the scan IO.
The optimization happens at CarbonOptimizor Step and will not impact the physical steps.
Test Result:
Environment: MacOS X EI Capitan
IntelliJ IDEA + Spark 1.6.2 + CarbonData 1.1.0
Data Volumn: 100M rows
Query duration(ms):
Before: 128532, 129150
After: 4012, 1002, 988
Future:
1. The optimisation is only applied on spark1.6 for now, we can extend to spark2.0 later.
2. TBD
Thanks,
Cao, Lu
On 3/31/17, 2:10 PM, "Cao, Lionel (JIRA)" <
[hidden email]<mailto:
[hidden email]>> wrote:
Cao, Lionel created CARBONDATA-840:
--------------------------------------
Summary: Limit query performance optimization [Group By]
Key: CARBONDATA-840
URL:
https://issues.apache.org/jira/browse/CARBONDATA-840 Project: CarbonData
Issue Type: Improvement
Components: data-query
Reporter: Cao, Lionel
Assignee: Cao, Lionel
Currently limit query will still scan all data first and limit in the last step. In carbon we can convert limit to filters with dictionary distinct value list...
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