Partial indexing is a feature in many DBMSs, including SQLite, that allows developers to optimize database performance by creating indexes only for specific subsets of data. This can significantly reduce the index size and improve query speed, especially in cases where only a portion of the data is frequently queried.
In this article, we’ll look at how to create a partial index in SQLite, why it’s useful, and provide an example to illustrate its use.
Continue readingThe FLOOR() function in SQLite returns the largest integer value that is less than or equal to a given numeric expression. Essentially, it “rounds down” a decimal number to the nearest integer below it.
This function is useful in cases where you want to discard the decimal portion of a number without rounding up.
Continue readingSQLite is a widely-used lightweight database engine that powers many mobile, embedded, and desktop applications. One of its key features is its dynamic type system, which allows flexibility in handling data. While this is advantageous in many scenarios, there are cases where developers need precise control over how data is treated or converted between types. This is where SQLite’s CAST() expression comes in.
If you’re getting an error that reads “AUTOINCREMENT not allowed on WITHOUT ROWID tables” in SQLite, it appears that you’re trying to define a column as an AUTOINCREMENT in a WITHOUT ROWID table.
SQLite doesn’t allow us to create AUTOINCREMENT columns on WITHOUT ROWID tables.
To address this issue, either remove the AUTOINCREMENT attribute or remove the WITHOUT ROWID from the table definition.
Despite its simplicity, SQLite includes advanced optimization techniques to ensure efficient query execution. One of the lesser-known but potentially useful features it offers is the unlikely() function, a tool designed to guide SQLite’s query planner in making better decisions.
This article looks at how the unlikely() function works in SQLite.
SQLite provides a range of tools to help optimize query execution. One of these is the likely() function, which helps developers guide the query planner by hinting at the probability of certain conditions being true.
In this article, we’ll look at the likely() function, understanding how it works, its syntax, some use cases, and its impact on query performance.
SQLite is a lightweight, serverless database engine widely used for its simplicity and flexibility. Among its many functions, the likelihood() function is a handy option that allows you to influence query planning by providing hints about the probability of certain conditions being true.
This article explores the details of the likelihood() function, its syntax, use cases, and a practical example to demonstrate its application.
If you’re getting an error that reads something like “unknown datatype for (columnname): “DATE”” in SQLite, it appears that you’re trying to define a column as a DATE type in a strict table.
SQLite doesn’t support the DATE type, however, this error should only occur on strict tables (i.e. a table defined as STRICT).
To fix this issue, either use a supported data type or make the table a regular (non-strict) table.
Continue readingSQLite is a lightweight, self-contained SQL database engine known for its simplicity and versatility. In version 3.37.0, SQLite introduced strict tables, offering stricter type enforcement compared to its regular tables.
This feature allows developers to define tables with precise data types, ensuring better data consistency.
In this article, we’ll look at the six supported data types for strict tables—INT, INTEGER, REAL, TEXT, BLOB, and ANY—and provide simple examples to illustrate their usage.
The ACOSH() function in SQLite calculates the inverse hyperbolic cosine of a given number. The inverse hyperbolic cosine of a number is the value whose hyperbolic cosine equals that number.