DuckDB has a function called list_distinct() that enables us to remove duplicate values from a list. Any value that appears more than once is “deduped” and is returned once in the resulting list.
The function also removes any NULL values.
Continue readingDuckDB has enhanced its user experience with the introduction of a new web-based user interface in the v1.2.1 release. This addition brings graphical interaction capabilities to the analytical database system, making it more accessible to users who prefer visual interfaces over command-line operations.
Continue readingThe DuckDB command line interface (CLI) provides us with the ability to output query results in various formats. One of these formatting options is HTML.
This article shows you how to output your DuckDB query results as HTML tables, which can be useful when you need to include the results in web pages or documentation.
Continue readingWhen working with DuckDB, we may need to determine whether a specific value exists within a list or array. Fortunately, DuckDB offers four synonymous functions that enable us to accomplish this.
Continue readingDuckDB has an unnest() function that we can use to unnest lists and structs. Well, it can also be applied to NULL, but that’ll return an empty result.
By “unnest” I mean it takes the list or struct, and it returns its contents as rows in a table. You might say that it converts lists and structs into tables, where each item in the list or struct becomes a row in the table.
Below are examples of using DuckDB’s unnest() function to unnest lists and structs.
If you’re getting an error that reads “Binder Error: ‘list_has_all’ cannot compare lists of different types” in DuckDB, it appears that you’re passing two different types of lists to the list_has_all() function.
DuckDB’s list_has_all() function accepts two lists as arguments. These need to be of the same type.
To fix this issue, make sure that both lists are of the same type.
Continue readingDuckDB provides us with an easy way to add one or more months to date values, as well as subtract from them. This applies to the various date related data types, such as DATE and TIMESTAMP.
Actually, DuckDB provides us with a choice; We can use the + operator or the date_add() function.
If you’re getting an error that reads something like “Sample method System cannot be used with a discrete sample count” when using the SAMPLE clause in DuckDB, it looks like you’re specifying an invalid sampling method for the context with which you’re using the SAMPLE clause. Perhaps you’re using system or bernoulli, when you should be using reservoir.
The GREATEST() function in DuckDB is a versatile utility that returns the greatest value from a list of expressions. The function works across various data types and provides flexible comparison capabilities for data analysis tasks.
This article takes a look at DuckDB’s GREATEST() function, along with some simple examples.
When working with lists in DuckDB, we sometimes need to check whether a list contains specific elements. The list_has_all() function is a handy tool that allows us to verify if all elements of one list exist within another. This function is particularly useful in filtering queries, data validation, and advanced list-based operations.
In this article, we’ll explore how list_has_all() works in DuckDB.