Database Management Systems
DuckDB’s SAMPLE clause is a handy feature that allows us to work with a random subset of our data. This is particularly useful when dealing with large datasets where processing the entire dataset might be time-consuming or unnecessary for exploratory data analysis, testing queries, or creating representative samples.
When we use this clause, we can specify the absolute number of rows to return, or a percentage of rows. We also have an option of sampling method to use.
Continue readingThe range() function is a handy utility in DuckDB that enables us to generate sequences of numbers or timestamps. We specify the starting point, the end point, and the step to use for each value in the range.
In this article, we’ll take a look at DuckDB’s range() function, along with some basic examples.
One of SQLite’s unique features is the WITHOUT ROWID table, which can be used to optimize performance and storage in specific scenarios.
While it’s easy enough to create a WITHOUT ROWID table (just add WITHOUT ROWID to the definition), how to identify a WITHOUT ROWID table might not be so obvious.
In this article, we’ll start by briefly revising what WITHOUT ROWID tables are and how they differ from ordinary tables. Then we’ll look at how to identify these tables by using SQLite’s PRAGMA commands.
The generate_subscripts() function in DuckDB creates a series of index values for accessing elements in an array. It can help us iterate through array indices when we need to work with array elements.
Here’s a quick look at DuckDB’s generate_subscripts() function, along with examples.
If you’re getting an error that reads “Conversion Error: Could not convert …etc” while using the COALESCE() function in DuckDB, it appears that you’re using arguments with incompatible types.
To fix this issue, try using CAST() or TRY_CAST() to ensure that all arguments are compatible. Alternatively, make sure the arguments to COALESCE() are of the same type (or at least, compatible types).
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.
If you’ve ever used the strptime() function to create a timestamp in DuckDB, you may be aware that it will return an error if it can’t construct the timestamp from the format string/s provided.
While such an error could be useful in some situations, it could also be annoying in others.
Fortunately, DuckDB also provides the try_strptime() function, which will suppress any error that we might ordinarily get in such cases. This function returns null instead of an error.
In DuckDB, the generate_series() function is a powerful tool for generating sequences of values, which can be very useful for data analysis, testing, and creating sample datasets. This function enables us to easily create series of numbers, dates, and timestamps with minimal code.
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.
Continue readingWhen working with date and time data in DuckDB, calculating the difference between two dates is a common requirement. Whether we’re determining a person’s age from their birthdate or measuring the duration between two events, DuckDB’s age() function provides a straightforward solution. This function returns an interval representing the difference between two timestamps or dates, making it especially useful for time-based analyses.
In this article, we’ll explore how to use the age() function in DuckDB. We’ll cover its syntax, and provide some simple examples.