In this case, we see Type 2 (numeric data) and Type 1 (string data) represented. JSON, unlike XML, has type definitions for each value in a document. Running the query produces a result set with three columns: key, value, and type. We then pass the variable to the OPENJSON function in a SELECT statement. The approach involves first defining a string variable and passing our JSON object as a parameter to this variable. Listing 3 shows an example of this using the first object in the sample JSON document referred to in Listing 1. OPENJSON can be used to revert JSON formatted data to a relational format. In each object, the column name is translated to the JSON name and the value for that column in that row is represented as the JSON value. In essence, SQL Server converts each row in the source table to a JSON object. Listing 2 shows the feedback from SQL Server Management Studio upon the query execution: “9 Rows affected”. The document in Listing 1 was extracted from a regular SQL Server database table using the query from Listing 2. The following shows the format of a JSON document based on the EMCA-404 standard: JSON objects can increase in complexity as we introduce components which are not just single values but arrays in themselves. JSON documents are represented as a series of JSON objects that contain name-value pairs. SQL Server introduced support for JSON in SQL Server 2016. Now, we will look at the syntax of this function. JSON was standardized in 2013 and the latest version of the standard (ECMA-404: The JSON Data Interchange Syntax) was released in 2017. OPENJSON is a table-valued function that helps to parse JSON in SQL Server and it returns the data values and types of the JSON text in a table format. I am sure you begin to get the idea of how widespread its applications have become. Virtually all the Social Media giants expose APIs that are based on JSON. JSON is also used extensively in NoSQL databases such as the increasingly popular MongoDB. Producing JSON Documents From SQL Server Queries via TSQL (May 2014) Consuming hierarchical JSON documents in SQL Server using OpenJSON (Sept 2017) Importing JSON data from Web Services and Applications into SQL Server(October 2017) One of the surprises that I got from writing for Simple-Talk was the popularity of my article Consuming JSON. In AWS CloudFormation, templates, which are actually JSON (or YAML) formatted documents, are used to describe AWS resources when automating deployments. It is reported to be lightweight and easier to manipulate compared to XML. In SQL Server 2016 CTP2 is introduced FOR JSON clause that formats results of SQL query as JSON text. JSON has nearly replaced XML as a cross-platform data exchange format. JSON is essentially a data format, it was popularized by Douglas Crockford, a well-known programmer with an interesting history who was also involved in the development of JavaScript. Here’s a simple example to demonstrate.JSON is an acronym for JavaScript Object Notation, that became popular a little over seventeen years ago. 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:
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