Ordered Columnstore Indexes on SQL Server 2022 CTP 2.0

Brent recently blogged about ordered columnstore indexes in SQL Server 2022 and had some trouble with them, so I decided to take a look into the mechanics of the feature. I’m testing on SQL Server 2022 CTP 2.0.

What does the ordered columnstore feature do?

  1. A sort operator may be added to query plans that insert into the table. The sort operator is a bit unusual in that the data may not be fully sorted.
  2. A sort operator is added when initially creating an ordered columnstore index. The level of rowgroup elimination fragmentation will depend on memory, DOP, and other factors.
  3. A sort operator is added when rebuilding an ordered columnstore index. The level of rowgroup elimination fragmentation will depend on memory, DOP, and other factors.

Technical details for insert

The sort for inserting into an ordered columnstore is a DML request sort. It appears to use the same internal mechanism as the sort that’s added for inserting into partitioned columnstore tables. The difference is that the data is sorted by the specified columns instead of a calculated partition id. In my testing, the sort appears to be a best effort sort that does not spill to tempdb. This means that if SQL Server thinks there won’t be enough memory then the data will not be fully sorted. Parallel inserts have an additional complication. Consider the following query plan image:

That is a row mode sort. It is a row mode sort because a batch mode parallel sort would put all resulting rows on a single thread which would make the parallel insert pointless. However, there’s no repartition streams operator as a child of the sort. Data is sorted on each thread in a best effort fashion. Even if there is enough memory to fully sort the data, you will end up with DOP threads of sorted data instead. The data will not be sorted globally. The split into threads will increase rowgroup elimination fragmentation.

As mentioned earlier, the sort operator does not always appear. It is not present when the cardinality estimate is very low (around 250 rows). I suspect that the same logic is used for adding the sort as adding the memory grant for compression. For very low cardinality estimates, the data will be inserted into delta rowgroups, even if there’s more than 102399 rows. By that same reasoning, I expect that there is no sort operator if the INSERT query hits a memory grant timeout.

For more information on this sort, see CQScanPartitionSortNew in Paul White’s blog post about different sort types in SQL Server.

Technical details for CREATE/REBUILD index

I spent less time looking into the sort that’s added as part of CREATE or REBUILD index. In my testing, the sort again does not spill to tempdb. The sort is also performed on a per thread basis for parallel index operations. The minimum fragmentation level will be achieved for a MAXDOP 1 operation with sufficient memory. Reducing memory or running the create index in parallel will increase fragmentation. This is unfortunate because ordered columnstore indexes do not support online index creation or rebuilds.

An unpopular opinion

I think that the community worries too much with columnstore with respect to achieving perfect segment ordering and keeping rowgroups at exactly 1048576 rows. If you perform basic maintenance and partition tables appropriately then that should be good enough for most data warehouse workloads. Most query performance issues are going to be caused by getting no elimination at all, scanning through too many soft-deleted rows, or the usual query performance problems. Scanning 11 rowgroups instead of 5 probably isn’t why your queries on columnstore indexes are slow today.

Final thoughts

As is, this feature can be described as a poor man’s partitioning. The sweet spot for this functionality feels very limited to me in its current state, but we’re still on CTP 2.0. Maybe there will be changes before RTM. Thanks for reading!

3 thoughts on “Ordered Columnstore Indexes on SQL Server 2022 CTP 2.0

  1. Thanks for the “unpopular opinion”. I needed to hear that. 😁
    I’ve been spending too much time chasing perfection lately, when we’re probably talking a few dozen milliseconds difference at best.

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