Aggregate Predicate Pushdown And Data Types

Niko Neugebauer shows an example of how a slightly different data type can cause columnstore queries to be much faster:

Even though they are estimated to cost the same (50% for each one) with the estimated cost of 0.275286 to be more precise in this sense.
To be more precise in the reality you will notice the Aggregate Predicate Pushdown taking place on the first query, while the second query is using the Storage Engine to read out all of the 2 million rows from the table and filter it in the Hash Match iterator.

Actual Number of Locally Aggregated Rows
is the one property on the Columnstore Index Scan iterator that will give you an insight on what happened within the Columnstore Index Scan, since the Aggregate Predicate Pushdown is not shown as a filter on the property. This is not the most fortunate solution as far as I am concerned, but since the 0 rows flowing out of the Columnstore Index Scan will serve as a good indication that Aggregate Predicate Pushdown took place, but if you want to be sure of all the details you will need to check the properties of the involved iterators.

Definitely worth reading.

Related Posts

Cloning And Columnstore Statistics

Niko Neugebauer points out a fix in SQL Server 2019: I have a huge love for the DBCC CLONEDATABASE command – it has been made available (backported) to every SQL Server version starting with SQL Server 2012, since the original release in SQL Server 2014, while being constantly improved in the Service Packs and Cumulative Updates. This […]

Read More

Hybrid Columnstore And B+ Tree Designs

Adrian Colyer reviews a Microsoft paper on the combination of columnstore and B+ tree indexes on a single table: The authors conducted a series of microbenchmarks as follows: scans with single predicates with varying selectivity to study the trade-off between the range scan of a B+ tree vs a columnstore scan sort and group-by queries […]

Read More

Categories

April 2017
MTWTFSS
« Mar May »
 12
3456789
10111213141516
17181920212223
24252627282930