how to – Page 16

Create a Resource Group in the Azure Portal

July 26, 2025 by Ian

An Azure resource group is a container that logically organizes related Azure resources, allowing for easier management, deployment, and access control of those resources. When we do things like create a SQL database, we need to create a resource group for the database to belong to. We can create the resource group while creating the database, but we can also create the resource group separately.

This article shows the steps for creating a resource group separately, from the Azure portal home page.

Extracting the First Non-NULL Value from a List with DuckDB’s LIST_ANY_VALUE() Function

July 25, 2025 by Ian

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.

4 Ways to Get the Last Value from a List in DuckDB

July 24, 2025 by Ian

When it comes to working with lists, DuckDB often provides us with multiple methods of performing a given task. Getting the last value from a list is no exception.

Here are four options we can use to extract the last value from a list in DuckDB.

Subtract Months from a Date in DuckDB

July 22, 2025 by Ian

If you find yourself in the situation where you need to subtract a number of months from a date in DuckDB, here are two options for you.

Convert a Table to a JSON Document with JSON_GROUP_OBJECT() in DuckDB

July 20, 2025 by Ian

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.

2 Ways to Get the Month Name from a Date in DuckDB

July 19, 2025 by Ian

DuckDB offers a pretty good range of functions that enable us to get date parts from date or timestamp value. For example, we can extract the month part from a given date value. In most cases, this will be the month number, for example 08 or just 8.

But sometimes we might want to get the actual month name, like October for example. And other times we might just want the abbreviated month name, like Oct.

Fortunately, DuckDB’s got our back. Here are two ways to return the month name from a date or timestamp value in DuckDB.

Appending Values to Lists with 3 DuckDB Functions

July 18, 2025 by Ian

Appending values to lists is a common task when working with DuckDB and other DBMSs (not to mention programming languages in general). Usually we’ll get a function that’s purpose built for the task. As it turns out, DuckDB provides us with at least three functions to do this task.

3 Functions for Extracting a Value from a List in DuckDB

July 17, 2025 by Ian

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.

Generating Date Ranges with DuckDB Queries

July 15, 2025 by Ian

Working with date ranges is a common requirement in data analysis, reporting, and time-series operations. DuckDB provides us with several approaches for generating date ranges. This article explores various techniques for creating date ranges in DuckDB.

6 Functions for Working with the Unix Epoch in DuckDB

July 14, 2025 by Ian

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.