What types of functions does Impala support?
Impala supports a variety of functions, including scalar functions, aggregate functions, and analytic functions. These functions can be used in queries to manipulate data, perform calculations, and produce results. Here are some common types of functions supported by Impala.
- Scalar functions are used to manipulate individual values, such as string functions like CONCAT and SUBSTRING, mathematical functions like ROUND and ABS, and date-time functions like YEAR and MONTH.
- Aggregate functions are used to perform aggregation operations on a dataset, such as COUNT, SUM, AVG, MIN, MAX, etc. They can be used for statistical analysis on the results.
- Analytic Functions: Used to achieve the functionality of window functions, allowing for calculations to be performed on subsets (windows) of the query result. Common examples of analytic functions include RANK, LEAD, LAG, and NTILE, which can be used for sorting, ranking, and calculating moving averages, among other operations.
In addition to the mentioned function types, Impala also supports User-Defined Functions (UDFs) and User-Defined Aggregate Functions (UDAFs), allowing users to write custom functions to extend Impala’s functionality as needed. By effectively utilizing both built-in and custom functions, users can have more flexibility in data processing and analysis, enabling more complex data operations.
