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Overview of aggregate function

  • Recent Updates: April 15, 2022

    • 1. Overview

    1.1 Version

              FineBI       JARFunction Changes
    5.1  --
    5.1.62020-09-30

    Add [APPROX_COUNTD_AGG] to [Real-time data]

    Note： supported databases include CLICKHOUSE, ORACLE(12.1 and higher), SQLSERVER(2019 and higher), PRESTO, REDSHIFT, VERTICA and MAXCOMPUTE

    5.1.72020-11-05

    Optimize definition of functions

    Clarify the validity of function parameters

    5.1.112021-04-02Enhance real-time data function check

    1.2 Application scenario

    Comonent edit pane: Add caculation indicator

    1.3 Function description

    • Aggregate functions can summarize a group of data. In general, aggregate functions are used to summarize the values and then calculate.

    • Different aggregate functions correspond to different aggregate methods, including sum, average, medium, maximum, minimum, standard deviation, variance, distinct count and count.

    • The column to be calculated is changed dynamically according to the dimensions when users swich the analysis dimension.

    The sum aggregate function [SUM_AGG] is the most frequently used aggregate function and the following passage will use [SUM_AGG] as an exaple to explain aggregate function in details.

    2. Function list

    Function
    		Definition
    SUM_AGG
    		Summarize the data in specified dimension(dragged to the analysis panel).
    AVG_AGGReturn the summarized average of the indicator column according to current analysis dimension. The result is a column of data and the number of rows is the same as the number of rows in current analysis dimension.
    COUNT_AGGCount the data(the number of cells that are not null) in specified dimension(dragged to the analysis panel).
    COUNTD_AGG

    Count the distinct not null values(the number of distinct cells that are not null) in specified dimension(dragged to the analysis panel).

    MIN_AGGReturn the minimum value of the indicator column according to current analysis dimension. The result is a column of data and the number of rows is the same as the number of rows in current analysis dimension.
    MAX_AGGReturn the maximum value of the indicator column according to current analysis dimension. The result is a column of data and the number of rows is the same as the number of rows in current analysis dimension.
    MEDIAN_AGGReturn the median of the indicator column according to current analysis dimension. The result is a column of data and the number of rows is the same as the number of rows in current analysis dimension.
    VAR_AGGReturn the variance of the indicator column dynamically according to current analysis dimension. The result is a column of data and the number of rows is the same as the number of rows in current analysis dimension.
    STDEV_AGGReturn the standard deviation of the indicator column according to current analysis dimension. The result is a column of data and the number of rows is the same as the number of rows in current analysis dimension.
    PERCENTILE_AGG
    		Return the value from the expression according to current analysis dimension and the value is at the percentile corresponding to the specified number. The specified number must be between 0 and 1(include 0 and 1), e.g. 0.66 and must be a numerical constant.
    APPROX_COUNTD_AGGCount the approximate distinct values dynamically according to current analysis dimension. The result is a dynamic column of data and the number of rows is the same as the number of rows in current analysis dimension.


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