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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.
Then wait a couple days and chase it with it’s charming cousin, Optimizing Your Query Plans with the SQL Server 2014 Cardinality Estimator. ⇒ If you’re too proactive, you’ll eventually be sorry: If you set up statistics maintenance too aggressively, your maintenance windows can start to run long.
As an example, we can transform a JSON array in the @orders variable into a set of rows and insert them into a standard table: Four columns in the result set that is returned by OPENJSON are defined in the WITH clause.
OPENJSON will try to find the properties Number, Date, Customer, and Quantity in each JSON object and convert their values into columns in the result set.
These are not considered ‘user created’ even though our user query was the cause of them being auto-generated.
Since JSON is regular text, you can use standard full text index.
You just need to specify column names and types and OPENJSON will find properties in JSON that match these columns.