Personally, I think this makes JSON that much easier (and practical) to use in SQL Server 2016. This is how SQL is able to parse indexed JSON properties so fast instead of needing to do a table scan and parsing the JSON data for each row of our table, SQL Server can go look up the pre-parsed values in the index and return the correct data incredibly fast. SQL will only compute the "Make" value on a row's insert or update into the table (or during the initial index creation) - all future retrievals of our computed column will come from the pre-computed index page. This is basically a cheat code for indexing computed columns. However if we create an index on our non-persisted computed column, the computed value What does this mean? I thought non-persisted computed columns aren't saved to disk!Įxactly right: our non-persisted computed column "Make" isn't saved to the data page on the disk. Additional details on the column definitions inĭBCC PAGE ( 'Sandbox', 1, 305088, 3 ) WITH TABLERESULTS DBCC PAGE ( 'Sandbox', 1, 305096, 3 ) WITH TABLERESULTSīut our index page contains the parsed values for our "Make" column: We do this by first turning on trace flag 3604 and using In the rest of this post we'll be looking at how data pages (where the actual table data in SQL is stored) and index pages (where our index data is stored) are affected by non-persisted computed columns - and how they make JSON querying super fast.įirst, let's take a look at the existing data we have. Page files are how SQL Server stores its data Is an undocumented SQL Server function that shows what the raw data stored in a SQL page file looks like. However, when you combine a computed column with an index, something interesting happens. The performance of this isn't great - it's essentially a scalar function running for each row of our output :(. Table, SQL Server will calculate the value for each row. Instead, every time a query runs against our DealerInventory /* Output: Id Year JsonData Make - 1 2017 Subaru */īy default, the above Make computed column is non-persisted, meaning its values are never stored to the database (persisted computed columns can also be created, but that's a topic for a different time). DealerInventory ADD Make AS JSON_VALUE ( JsonData, '$.Make' ) SELECT * FROM dbo. A computed column is basically a column that performs a function to calculate its values.įor example, let's say we have a table with some car JSON data in it:ĪLTER TABLE dbo. The only way to get JSON indexes working on SQL server is to use a *"Parse" here is actually a lie -it's doing something else behind the scenes. In this post I want to take a look at how SQL is able to parse* with such great performance. Using indexes on JSON parsed computed columns Even better is that it's possible to make queries against JSON data run at ludicrous speeds by It turns out that performance is pretty good with the standalone SQL Server JSON functions. Here’s a simple example to demonstrate.One of the hesitations many people have with using JSON in SQL Server is that they think that querying it must be really slow - SQL is supposed to excel at relational data, not string parsing right? For example, in $.pets.dogs, dogs is a member of pets. Array indexes are zero-based, so this example selects the second element in the array. If the key name starts with a dollar sign or contains special characters such as spaces, it must be surrounded with quotes (for example $."my pets"). Path steps can contain the following elements and operators: A dollar sign ( $), which represents the context item.It also allows you to select a nested JSON fragment from the JSON document. The OPENJSON() syntax allows you to convert JSON documents into a tabular view. If you’re using OPENJSON(), but you’re trying to remember how to select an inner fragment from the JSON document, read on.
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