In SQL Server, STRING_AGG() is an aggregate function that concatenates string values from a group into a single string. It’s a handy tool for doing things like creating comma-separated lists from related data.
In this article we’ll check out how to use STRING_AGG() with different separators. We’ll also see how we can control the order of the concatenated strings.
When formatting dates in SQL Server you may be wondering whether to use CONVERT() or CAST(). After all, both functions allow us to convert between data types. Let’s take a look at at these two functions and figure out when to use each one.
DuckDB has a list_select() function and a list_slice() function, and both do a similar thing. They allow us to extract values from lists based on their index in the list. But they’re quite different in the way they work. One function allows us to select elements based on a range, while the other function allows us to handpick each element we want returned.
DuckDB provides us with a good selection of list functions. This includes a list_any_value() function, which returns the first non-NULL value from a given list.
DuckDB offers two handy functions for generating sequences of numbers: range() and generate_series(). While they both do the same thing, and share basically the same syntax, there is one important difference between them.
The primary difference between them is in their inclusivity behavior with regard to the stop value.
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 list_extract() function that extracts a value from a list, based on the element’s index in that list.
But as if one function isn’t enough, it also provides us with a couple of aliases that we can use instead of list_extract() if we prefer.
So let’s call it three functions that we can use to extract a value from a list.
The duckdb_tables() function is a system function in DuckDB that provides useful metadata about all tables in your database. The function returns a table containing information about each table, including its schema, name, and various properties. It can be quite a handy tool for database introspection and management.
DuckDB offers a versatile set of functions to handle timestamps at various levels of precision. This article explores some of DuckDB’s functions that help us to convert between epoch representations and timestamps.
These specialized time conversion functions can be handy tools when working with temporal data, allowing seamless translation between human-readable timestamps and machine-optimized epoch representations at varying levels of precision.