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.
Julian day is a concept you might occasionally encounter in SQL code or database operations, particularly when working with date and time functions. While it may seem esoteric at first, understanding Julian day can be incredibly useful for handling date calculations, especially in fields like astronomy, data analysis, and historical research.
This article looks at the origins, calculations, and practical applications of Julian day, including examples of converting between Julian day and other date formats in SQL.
Continue readingIf 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.
The COSH() function in SQLite calculates the hyperbolic cosine of a number, which is similar to the regular cosine function, but for hyperbolic geometry.
In most relational database management systems (RDBMSs) the PRIMARY KEY is used to define the unique row identifier for a table. But in SQLite, not all primary keys are handled the same way when it comes to indexing.
Depending on how the primary key is defined in a table, it may or may not show up in the list of indexes returned by the PRAGMA index_list() command. In particular, when the primary key is an INTEGER PRIMARY KEY, SQLite doesn’t explicitly create a separate index for it.
This article will explain why this happens and provide examples with different types of primary key definitions.
Continue readingSQLite is widely known for its simplicity, flexibility, and lightweight architecture. One feature that sets it apart from most other SQL databases is its dynamic typing system, which allows columns in a table to store data of any type, regardless of their declared type.
While some developers welcome this departure from the traditional SQL approach, others find it extremely problematic, due to its non-enforcement of data types, which could potentially lead to data integrity issues.
Continue reading