The make_timestamp() function in DuckDB is a handy tool for creating timestamp values from individual components. It allows us to construct timestamp values using two alternative approaches; by specifying the number of milliseconds from epoch, or by specifying the year, month, day, hour, minute, and second components separately.
Let’s take a look at the make_timestamp() function, along with some examples.
The json_group_structure() function in DuckDB is an aggregate function that inspects all JSON values within a group and returns a JSON representation of their structure. It essentially infers a “schema” for the JSON objects in that group. This can be useful for understanding the shape and consistency of your JSON data.
In DuckDB, the json_structure() is used to parse and introspect JSON data, returning the structure of a JSON document. This is especially useful when you’re working with semi-structured JSON data and you want to understand its schema — including nested keys, arrays, and types — without manually inspecting the raw JSON.
DuckDB provides an epoch_ns() function that returns the Unix epoch time from a given date/time value in nanoseconds.
Unix epoch time is typically expressed as the number of seconds that have elapsed since January 1, 1970 (UTC), but it can also be expressed in other units, such as milliseconds, microseconds, and nanoseconds. DuckDB has specific functions for each of these units, with epoch_ns() being the function that returns it in nanoseconds.
Most of the major RDBMSs that support JSON also include a json_valid() function for checking the validity of a JSON document, and DuckDB’s no exception. Like the other RDBMSs, DuckDB’s implementation of json_valid() checks its argument and returns a boolean value to indicate whether or not it’s valid JSON.
DuckDB provides us with a few functions that prepend a value to a list. Actually, these functions are synonymous, so they all do the same thing, with the same/similar basic syntax.
Continue readingThe list_intersect() can be quite a handy function when working with lists in DuckDB. It accepts two lists as arguments, and it returns a list of elements that are common to both lists. It essentially performs a set intersection operation while preserving the list data type.
Duplicate values are ignored, so only one value is returned even if there are multiple occurrences in one or both lists.
Continue readingWhen it comes to concatenating lists in DuckDB, we can use the list_concat() function (and its aliases), or the list concatenation operator (||). Often when we have a choice like this, we can use either option interchangeably. But that isn’t quite true in this case.
There’s an important difference between list_concat() and the || operator in DuckDB, and it all comes down to how it handles NULL values.
DuckDB provides a handful of functions for getting data from JSON documents. We can use them as long as the JSON extension is installed and loaded (which it is in most distributions). One such function for getting data from a JSON document is json_value(). This function extracts scalar data from the specified path in the JSON document. If the value isn’t scalar, then a NULL value is returned.
DuckDB has a json_extract_string() function that works similar to json_extract(), except that it returns its result as a string (varchar). The json_extract() function, on the other hand, returns its result as JSON.
The purpose of these two functions is to extract data from a JSON document. We’ll focus on the json_extract_string() function in this article.