DuckDB has a arg_min_null() function that works in a similar way to the arg_min() function. That is, it finds the row with the minimum value in one column and returns the corresponding value from another column at that row.

But there’s also a difference between these two functions. The main difference is in the way they deal with NULL values. Also, arg_min_null() only accepts two arguments, whereas arg_min() accepts an optional third argument. Additionally, there aren’t any aliases for arg_min_null() at the time of writing (arg_min() has a couple of aliases).

In this article we’ll look at how arg_min_null() works, and we’ll compare it with arg_min() to see how each function handles NULL values.

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DuckDB has a fsum() function that can be used instead of the regular sum() function in order to get more accurate results. fsum() calculates the sum using a floating point summation method known as Kahan summation (or compensated summation).

This method helps reduce the accumulation of rounding errors that can occur when summing many floating point numbers when using the regular sum() function.

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In analytical SQL workloads, expressing weighted averages can sometimes involve verbose expressions such as combining the sum() function with other operators. DuckDB streamlines this with its native weighted_avg() aggregate function, allowing us to compute weighted averages directly and efficiently. The weighted_avg() function enhances both clarity and speed when dealing with data where values contribute unequally — such as population-adjusted metrics or revenue-weighted scores.

This article explores the weighted_avg() in DuckDB, along with examples to demonstrate its usage.

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DuckDB has a string_agg() function, which allows us to concatenate strings from a group of rows into a single string. This function can be useful when we need to aggregate text data in a meaningful way.

In this article, we’ll explore how the string_agg() function works, along with some simple examples to demonstrate its usage.

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DuckDB is an in-process SQL OLAP database management system designed for analytical workloads. Among its various aggregate functions is the product() function, which calculates the product of a set of numeric values.

In this article, we’ll explore how the product() function works with some basic examples.

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In DuckDB, bool_and() is an aggregate function that returns true if every input value is true, otherwise it returns false.

Here are some basic examples that demonstrate how it works.

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