In DuckDB, the json_group_object() function is a convenient way to aggregate data into JSON objects by pairing keys and values across rows within groups.
The function is especially useful when we’re transforming tabular data into a more hierarchical or nested JSON structure for web APIs, reporting, or downstream processing. It helps pivot rows into a single JSON object, making the data more compact and easier to consume in applications that require JSON formats.
DuckDB provides us with a json_transform_strict() function that works just like the json_transform() function, except that it throws an error when type casting fails. The json_transform() function on the other hand, returns NULL for the respective field in such cases.
One of the many JSON functions that DuckDB provides is the json() function, which parses and minifies JSON values. We pass the JSON data to the function, and it parses and minifies the JSON, then returns the result.
DuckDB has a json_keys() function that we can use to extract the keys from a JSON object. It returns the keys as a list of strings (LIST of VARCHAR).
Occasionally we might need to filter data based on the existence of a given path in a JSON document in the database. When using DuckDB, we can achieve this outcome with the JSON_EXISTS() function. This function returns true or false, depending on whether the specified path exists. Therefore, we can use it to help us filter our query on that basis.
In DuckDB, we can use the json_contains() function to check whether a specified JSON value is contained within another JSON structure. It returns a boolean (TRUE or FALSE) that indicates whether or not the value was found. We can also check for key value pairs, or even a full JSON object within the JSON document.
The json_group_array() function in DuckDB is used to aggregate values into a JSON array, making it especially useful when working with structured or semi-structured data such as JSON. This function is part of DuckDB’s JSON extension and works similarly to DuckDB’s string_agg() or the group_concat() function in some other RDBMSs, but instead of returning a delimited string, it returns a well-formed JSON array.
This function is particularly helpful when we need to represent grouped or hierarchical data in a JSON format for export, reporting, or further transformation.
DuckDB makes it easy to export query results to JSON format, which can help us integrate database outputs with web applications, APIs, and data processing pipelines. This article explores how to generate JSON files from DuckDB queries.
The json_transform() function in DuckDB is a handy tool for converting JSON strings into structured data types like STRUCT, MAP, and LIST. This allows you to directly query and manipulate nested JSON data using standard SQL, making it much easier to work with complex JSON objects and arrays.
Think of it as a way to cast your JSON data into a more usable, typed format within your database.
DuckDB has a bunch of functions that allow us to extract data from JSON documents. For example, there’s the json_extract() function, which extracts JSON from the specified JSON document.
Often times we’ll need to extract multiple values within the same query. For example, we may need to extract both a user’s name and age, so that they’re returned in two separate columns.