Updating sql server 2016 r2
Statistics are small, lightweight objects that describe the distribution of data in a SQL Server table. First Name By Year and you run this query: SQL Server needs to estimate how many rows will come back for First Name Id=74846. Statistics are lightweight little pieces of information that SQL Server keeps on tables and indexes to help the optimizer do a good job. First Name By Year table was freshly created when we ran our query, it would have no column statistics.
I’m also not talking about statistics for memory optimized tables in this article. Back when I read philosophy, I found Aristotle a bit annoying because he talked so much about “moderation”. You shouldn’t run statistics maintenance against a database at the same time you’re checking for corruption, rebuilding indexes, or running other IO intensive processes.
You should also consider creating statistics when your query selects from a subset of data or the query predicate contains multiple correlated columns.
The statistics can be created by using the CREATE STATISTICS command: --Create statistics on all rows CREATE STATISTICS statistics_name ON Your DBName. Your Table (Your Column1, Your Column2) WITH FULLSCAN--Create statistics using a random 10 percent sampling rate CREATE STATISTICS statistics_name ON Your DBName. Your Table (Your Column1, Your Column2) WITH SAMPLE 10 PERCENT If your queries are executing slower, then it is time to update the statistics.
I don’t dig into the internals of statistics and optimization in this post. ⇒ Be a proactive: If you have millions of rows in some of your tables, you can get burned by doing no statistics maintenance at all if query performance stats to get slow and out of date statistics are found to be the cause.
If you’re interested in that, head on over and read the fahhhbulous white paper, Statistics Used by the Query Optimizer in SQL Server 2008. Unfortunately, Aristotle was right when it comes to statistics maintenance in SQL Server. This is because you didn’t do any proactive work at all.