Details
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Improvement
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Status: Closed
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Major
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Resolution: Fixed
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Description
In interactive data exploration use case, one common and probably first query that users would use is " SELECT * from table LIMIT n", where n is a small number. Such query will give user idea about the columns in the table.
Normally, user would expect such query should be completed in very short time, since it's just asking for small amount of rows, without any sort/aggregation.
When table is small, there is no big problem for Drill. However, when the table is extremely large, Drill's response time is not as fast as what user would expect.
In case of parquet table, it seems that query planner could do a bit better job : by applying row count based pruning for such LIMIT n query. The pruning is kind of similar to what partition pruning will do, except that it uses row count, in stead of partition column values. Since row count is available in parquet table, it's possible to do such pruning.
The benefit of doing such pruning is clear: 1) for small "n", such pruning would end up with a few parquet files, in stead of thousands, or millions of files to scan. 2) execution probably does not have to put scan into multiple minor fragments and start reading the files concurrently, which will cause big IO overhead. 3) the physical plan itself is much smaller, since it does not include the long list of parquet files, reduce rpc cost of sending the fragment plans to multiple drillbits, and the overhead to serialize/deserialize the fragment plans.