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While the software may work, but it may not scale and in some occasions, may perform poorly especially if you are hitting memory object scaling issues (CMEMTHREAD) as now you have more resources to run concurrent threads in parallel, but all threads wait on a single memory object for memory which becomes a point of contention and bottleneck on the high-end server.
The following SQLOS and memory enhancements in SQL Server 2016/2017 allows SQL Server engine to scale out of the box on high end servers.
It is one line of code that will update all the statistics in the database using the default sample size of 20,000 rows per table.
This command gives much better granularity of control: [cc lang=”sql”] — Update all statistics on a table UPDATE STATISTICS Sales.
In addition, upgrading to SQL Server 2016/2017 allows you to leverage new features like Columnstore Indexes, In-Memory schema only temp tables, table variables, parallel inserts to further scale your workload if you can afford some database schema changes.
In most scenarios, customers choose to add new hardware as opposed to upgrading their SQL Server since the general perception is that cost of upgrade is high.
Let me back the above theory and claim with some data as we recently put this approach to practice with one of our customer running Tier 1 mission critical workload on SQL Server 2008 R2.
Later, you can test to change the DBCompat level to the latest level and use query store to identify the queries which have regressed.Set the @Max Days Old variable to the number of days you will allow the statistics to be out of date by.