This topic offers a detailed overview of SQL functions, enabling you to become acquainted with the capabilities and features of various SQL functions.
Overview
Classification | Description | Common Functions |
Perform summary calculations on the target dataset to generate a single statistical result. | ||
Process text data, including search, replace, substring, concatenate, format, and more. | ||
Perform format conversion, grouping, and aggregation on dates and times in logs. | ||
Process JSON objects, including extraction, transformation, and statistics. | ||
Pattern matching and text processing. | ||
Calculate relative changes in time series data. | ||
Perform addition, deletion, modification, query, traversal, and transformation on arrays. | ||
Operate on key-value pairs. | ||
Numerical calculations, rounding, random numbers, trigonometric functions, and more. | ||
Data distribution analysis and numerical calculations. | ||
Handle conversions between data types. | ||
Aggregation or sorting based on data windows. | ||
Parse and calculate IP addresses. | ||
Parse URL structures. | ||
Predict data or fill in missing values. | ||
Process binary data types. | ||
Directly operate on binary bits. | ||
Process spatial geometries. | ||
Geographic location analysis and map calculations. | ||
Color representation and conversion. | ||
Perform statistical processing on large datasets, sacrificing accuracy to save memory. | ||
Determine the size relationship of parameters, applicable to any comparable data type (double, bigint, varchar, timestamp, and date). | ||
Combine multiple Boolean conditions to control logical flow. | ||
Convert units of data size or time intervals. | ||
Analyze user behavior, app traffic, product goal conversion, and other data. | ||
Define lambda expressions in SQL analytic statements and SPL statements, and pass the expressions to specified functions to enrich the expression of functions. | ||
Return different values based on conditional branches. | ||
Implement predefined operations or methods for specific algorithms or models. Used in various stages such as data preprocessing, feature engineering, model training, evaluation, and prediction. |