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Simple Log Service:SQL Functions

Last Updated:Feb 17, 2025

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

Aggregate functions

Perform summary calculations on the target dataset to generate a single statistical result.

String functions

Process text data, including search, replace, substring, concatenate, format, and more.

Date and time functions

Perform format conversion, grouping, and aggregation on dates and times in logs.

JSON functions

Process JSON objects, including extraction, transformation, and statistics.

Regular expression functions

Pattern matching and text processing.

Year-on-year and month-on-month functions

Calculate relative changes in time series data.

Array functions and operators

Perform addition, deletion, modification, query, traversal, and transformation on arrays.

Map mapping functions and operators

Operate on key-value pairs.

Mathematical calculation functions

Numerical calculations, rounding, random numbers, trigonometric functions, and more.

Mathematical statistics functions

Data distribution analysis and numerical calculations.

Type conversion functions

Handle conversions between data types.

Window functions

Aggregation or sorting based on data windows.

IP functions

Parse and calculate IP addresses.

URL functions

Parse URL structures.

Estimation functions

Predict data or fill in missing values.

Binary functions

Process binary data types.

Bitwise operation functions

Directly operate on binary bits.

Spatial geometry functions

Process spatial geometries.

Geographic functions

Geographic location analysis and map calculations.

Color functions

Color representation and conversion.

HyperLogLog functions

Perform statistical processing on large datasets, sacrificing accuracy to save memory.

Comparison operators

Determine the size relationship of parameters, applicable to any comparable data type (double, bigint, varchar, timestamp, and date).

Logical operators

Combine multiple Boolean conditions to control logical flow.

Unit conversion functions

Convert units of data size or time intervals.

Window funnel functions

Analyze user behavior, app traffic, product goal conversion, and other data.

Lambda expressions

Define lambda expressions in SQL analytic statements and SPL statements, and pass the expressions to specified functions to enrich the expression of functions.

Conditional expressions

Return different values based on conditional branches.

AI machine learning functions

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.