I will introduce a small usage sample for the JSON_VALUE function in combination with indexes to improve information retrieval from a table containing one JSON object. For our testes, we have a UserDetailTest table that has more than 500k rows with 2 columns: an UserId and a nvarchar(max) to hold a small JSON details string like the following:

SELECT *, LEN(DetailsJSON) AS [Len(DetailsJSON)] FROM UserDetailTest

I will activate time statistics and clean SQL Server cache between each query to have some consistency across the execution times using the following SQL statements:

CHECKPOINT
DBCC DROPCLEANBUFFERS
SET STATISTICS TIME ON

JSON_VALUE Function intro

The JSON_VALUE function extracts a value from a JSON string. This functions receives 2 arguments, the first being an expression for the JSON value and the second a path for the value we want to obtain. A simple sample with an inline JSON object would be the following:

SELECT JSON_VALUE('{"PostalCode":"376-3765","PhoneNumber":"351003765718"}', '$.PhoneNumber')

The return is a scalar value (nvarchar(4000)) for the PhoneNumber element.

Query scenarios

Starting with one of the really worst case scenario (yes, this can happen…):

More than 17 seconds really seems like a worst scenario! Next, we will use the JSON_VALUE function to get the PhoneNumber from the JSON string and use it in our where clause:

This still takes more than 3 seconds. A good improvement, but yet a high cost if we need to search information in this way.

Index creation

Let’s add a new virtual column to table that displays the result from the JSON_VALUE function – this will allow us to create an index and simplify the SELECT queries.

ALTER TABLE UserDetailTest 
	ADD vPhoneNumber AS 
	CAST(JSON_VALUE(DetailsJSON, '$.PhoneNumber') AS NVARCHAR(255));

The cast truncates the output from the JSON_VALUE to ensure that it does not exceed the maximum lenght for the index key. Now, if we search using the column, the result is still more or less the same 3 seconds has before:

Let’s create an index and perform the search again:

CREATE INDEX idx_vPhoneNumber ON [UserDetailTest] (vPhoneNumber);

Consequently the improvement is huge, 13 miliseconds is more interesting! But what’s the cost?

The cost

When we create an index, we’re basically trading space for time – more occupied space versus faster operations. Therefore let’s see what the increase is using sp_spaceused function before and after index creation:

Probably, an interesting comparison would be if the PhoneNumber column was an explicit column in that table containing the value. Let’s do that!

ALTER TABLE UserDetailTest  
	ADD PhoneNumberCopy NVARCHAR(255)

UPDATE UserDetailTest
	SET PhoneNumberCopy = vPhoneNumber

The sp_spaceused remained the same – SQL Server internal black magic regarding space allocation (for another time!). But performance wise, for this approach in my machine this query still took more than 2 seconds to complete:

Slightly better than the query with the JSON function but the advantage is that in this scenario SQL can better optimize the searches. The following runs of the same query without clearing the cache returns results much faster – each took around 220 miliseconds to complete:

Summary Results

Just to sum up all the results for the different types of searches comparing the first execution after cache clean up and the following runs. I did several iterations for each step just to make sure the results were consistent although the goal was just to have a baseline. Certanly, the use of this will depend on each case.

WHERE DetailsJson LIKE '%PhoneNumber":"351003765718"%'

WHERE JSON_VALUE(DetailsJson, '$.PhoneNumber') = '351003765718'

WHERE vPhoneNumber = '351003765718'

WHERE vPhoneNumber = '351003765718'

WHERE PhoneNumberCopy  = '351003765718'

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Lets say we have a table of customers where we have an Id, a CompanyName and an Address, although these customers can have some information related to a service, for example they may have a specific customer id for each service.

Customer

Id: the id

CompanyName: the company name

Address: the address

--- ServiceId: 1

--- ServiceCustomerId: the customer id for service 1

--- ServiceId: 2

--- ServiceCustomerId: the customer id for service 2

One way we could store this on a single table could be with these columns: Id / Name / Address / ServicesDataInJson

So for this example, the information on the ServicesDataInJson is an array of ‘objects’ that contains the information of our customer on each service. Since there is no native JSON format on SQL Server, the data type of this column is just a nvarchar(max)

Here’s how a simple SELECT looks like:

Now we want to query our customers table by a customer service id (which is inside that json). How can we query this?

SELECT *

FROM Customers c

CROSS APPLY OPENJSON(c.ServicesDataInJson)

WITH (ServiceId int '$.ServiceId',

ServiceCustomerId nvarchar(255) '$.ServiceCustomerId') as jsonValues

WHERE jsonValues.ServiceCustomerId = @TheIdWeWantToSearchFor

The OPENJSON is a table-valued function that parses the json into a row/column result and the WITH clause let us define how we want that output.

Here is the query without the WHERE clause:

Note: The OPENJSON function will not work if the database compatibility level is lower than 130.

To change it:

ALTER DATABASE DatabaseName SET COMPATIBILITY_LEVEL = 130

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