![]() It would be expensive to uncompress a rowgroup, delete the row, and then recompress it. Removing compressed rows from a rowgroup is not a synchronous operation. Switching out and truncating partitions that are not needed anymore is an efficient strategy to delete data without generating fragmentation introduced by having smaller rowgroups.Īvoid deleting large amounts of data. Also, consider using table partitioning if there's a need to remove data from the columnstore. Each partition will contain rows in time order for specific customer. A common query pattern is to find quarterly purchases done by a specific customer, you can combine the insert order with partitioning on customer column. For example, a fact table stores purchases made by customers. You can partition the columnstore index and then use partition elimination to reduce number of rowgroups to scan. As new rows are inserted or older rows are updated, you may need to repeat the process as the analytics query performance may deteriorate One important point to note is that columnstore index does not inherently maintain the order of rows. In this case, the resultant nonclustered columnstore index will automatically be ordered. Note, for nonclustered columnstore index (NCCI), if the base rowstore table has a clustered index, the rows are already ordered. A common case of this strategy when you initially create columnstore index with large set of data. If you specify MAXDOP = 8, then you will see overlap of values across eight rowgroups. ![]() if you create the clustered columnstore index explicitly using MAXDOP = 1, the resulting clustered columnstore index is perfectly ordered on column C1. If the common query predicate is on a column (for example, C1) that is unrelated to the insert order of the row, you can create a rowstore clustered index on columns C1 and then create clustered columnstore index by dropping the rowstore clustered index. In SQL Server 2016 (13.x), you can find out number rowgroups skipped as part of query processing. For this kind of workload, the rowgroup elimination happens automatically. In common case in traditional data warehouse, the data is indeed inserted in time order and analytics is done in time dimension. Organize data to eliminate more rowgroups from a full table scan Here are some recommendations for achieving the high-performance columnstore indexes are designed to provide. Recommendations for improving query performance Further explanations about columnstore performance are at the end. These recommendations help your queries achieve the very fast query performance that columnstore indexes are designed to provide. ![]() Recommendations for achieving the very fast query performance that columnstore indexes are designed to provide.Ĭolumnstore indexes can achieve up to 100x better performance on analytics and data warehousing workloads and up to ten times better data compression than traditional rowstore indexes.
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