*Alternate method to extract scalar attributs from single level nested objects JSON_QUERY(., '$.attribute_with_nested_values') , JSON_QUERY(., '$.attribute_with_nested_values') AS Returns a scalar value, while JSON_QUERY returns an object or an array. The key difference between JSON_VALUE and JSON_QUERY is that JSON_VALUE We can use JSON_VALUE to extract a scalar value from the nested object. Not JSON_VALUE because we are working with nested objects.Īfter we have queried the complex object, Note here we are using JSON_QUERY first , *Query fields with nested objects or arrays , JSON_VALUE(., '$.stores_purchased_at') AS *Normal Sacalar attributes at parent level in the document in the column*/ (JSON_QUERY(, '$.attribute_with_nested_array')) /*Note, if you want only the top most record from this array, replace this line with "(JSON_QUERY(, '$.attribute_with_nested_array'))"*/ The path to the attribute is using the normal path to the attribute name that contains the array */ JSON QUERY SQL SERVER FULLfield since that is the column with the full JSON Document we want to extract dat from. *Use JSON_QUERY here because we are querying a nested array, so we cant use JSON_VALUE. varchar(MAX) /*This now contains the full JSON document from the file. *Scalar attributes extraction from a nested array of objects via OPENJSON and JSON_QUERY*/ , JSON_VALUE(, '$.stores_purchased_at') AS Figure 4 shows a T-SQL statement that converts the results from our fictitious Fruit Sales data mart into JSON./*Scalar attributes extraction using JSON_VALUE*/ In this mode, the structure of the JSON output is determined by a combination of the order of columns in your SELECT statement as well as the tables that are referenced by the SELECT statement. This is the simplest way to convert relational data into a JSON format as all that you have to do is to add FOR JSON AUTO clause at the end of your SELECT statement. There are two ways that relational results can be converted into JSON, namely, the AUTO and PATH options. As can be seen in Figure 3, the JSON output from Figure 2 is now properly formatted. For the purposes of this discussion, I will be using JSONFormatter from. It is therefore advisable that whilst you teach yourself JSON in SQL Server that you find yourself a JSON editor. Varbinary, binary, image, timestamp, rowversionĪlthough SQL Server’s support for XML allowed for graphical representation of the data via an editor (shown in Figure 1), attempting to view JSON data via an editor may be frustrating as JSON data is shown as an unformatted single row. SQL Server data stored in the following data types cannot be converted into JSON:Ī breakdown of supported data types is shown in Table1 SQL Server Data TypeĬhar, nchar, varchar, nvarchar, date, datetime, datetime2, time, datetimeoffset, uniqueidentifier, money Thus, it is important that we take note of the supported data types. Like many of the features in SQL Server, there are terms and conditions to using them and JSON is no different. In this article we take a look at how such a requirement can be implemented by data teams using SQL Server 2016 FOR JSON clause SQL Server to JSON Supported Data Types reporting tools, web services etc.) in a JSON format. The increased popularity of JSON in modern web applications may create a requirement for data teams to expose some of their data to client applications (i.e. In my article, Warehousing JSON Formatted Data in SQL Server 2016, we had a look at available T-SQL options for converting JSON data into rows and columns for the purposes of populating a SQL Server based data warehouse.
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