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- Getting Started
- Operation Guide
- Resource Management
- Permission Management
- Log Collection
- Collection Overview
- Collecting Logs in Self-Built Kubernetes Cluster
- Collecting Syslog
- Collection by LogListener
- Collecting Text Log
- Uploading Log over Kafka
- Uploading Logs via Anonymous Write
- Uploading Logs via Logback Appender
- Uploading Logs via Log4j Appender
- Uploading Log via SDK
- Uploading Log via API
- Importing Data
- Tencent Cloud Service Log Access
- Metric Collection
- Log Storage
- Metric Storage
- Search and Analysis (Log Topic)
- Syntax and Rules
- Statistical Analysis (SQL)
- Quick Analysis
- SQL Syntax
- SQL Functions
- String Function
- Date and Time Functions
- IP Geographic Function
- URL Function
- Mathematical Calculation Functions
- Mathematical Statistical Function
- General Aggregate Function
- Geospatial Function
- Binary String Function
- Estimation Function
- Type Conversion Function
- Logical Function
- Operators
- Bitwise Operation
- Regular Expression Function
- Lambda Function
- Conditional Expressions
- Array Functions
- Interval-Valued Comparison and Periodicity-Valued Comparison Functions
- JSON Functions
- Window Functions
- Sampling Analysis
- Configuring Indexes
- Reindexing
- Context Search and Analysis
- Downloading Log
- Search and Analysis (Metric Topic)
- Dashboard
- Data Processing documents
- Data Processing
- Creating Processing Task
- Viewing Data Processing Details
- Data Processing Functions
- Function Overview
- Key-Value Extraction Functions
- Enrichment Functions
- Flow Control
- Row Processing Functions
- Field Processing Functions
- Value Structuring Functions
- Regular Expression Processing Functions
- Time Value Processing Functions
- String Processing Functions
- Type Conversion Functions
- Logical and Mathematical Functions
- Encoding and Decoding Functions
- IP Parsing Functions
- Processing Cases
- Scheduled SQL Analysis
- SCF
- Data Processing
- Shipping and Consumption
- Monitoring Alarm
- Historical Documentation
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- Developer Guide
- API Documentation
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- Introduction
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- Collection Configuration APIs
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- Scheduled SQL Analysis APIs
- COS Data Import Task APIs
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- Glossary
This document introduces the basic syntax and examples of estimation functions.
Function | Syntax | Description |
approx_distinct | approx_distinct(x) | Returns the approximate number of distinct input values (column x). |
approx_percentile | approx_percentile(x,percentage) | Sorts the values in the x column in ascending order and returns the value approximately at the given `percentage` position. |
| approx_percentile(x,array[percentage01, percentage02...]) | Sorts the values in the x column in ascending order and returns the values approximately at the given `percentage` positions (percentage01, percentage02...). |
approx_distinct
The
approx_distinct function is used to get the approximate number of distinct input values of a field. The standard result deviation is 2.3%.Syntax
approx_distinct(x)
Field description
Parameter | Description |
x | The parameter value can be of any data type. |
Return value type
Bigint
Sample
Use the
count function to calculate the PV value and use the approx_distinct function to get the approximate number of distinct input values of the client_ip field and use it as the UV value.* | SELECT count(*) AS PV, approx_distinct(ip) AS UV
approx_percentile
The
approx_percentile function is used to sort values of the target field in ascending order and return the value in the position around percentage. It uses the T-Digest algorithm for estimation, which has a low deviation and can meet the most statistical analysis requirements. If needed, you can use * | select count_if(x<(select approx_percentile(x,percentage))),count(*) to accurately count the number of field values below percentage and the total number of field values respectively and then verify the statistical deviation.Syntax
Return the value (double) approximately at the given
percentage positionapprox_percentile(x, percentage)
Return the value (array) approximately at the given
percentage positions (percentage01,percentage02...)approx_percentile(x, array[percentage01,percentage02...])
Field description
Parameter | Description |
x | Value type: double |
percentage | Value range: [0,1] |
Return value type
double or array.
Sample
Sample 1
Sort the values of the resTotalTime column and return the value of resTotalTime approximately at the 50% position.
* | select approx_percentile(resTotalTime,0.5)
Sample 2
Sort the values of the resTotalTime column and return the values of resTotalTime approximately at the 10%, 20%, and 60% positions.
* | select approx_percentile(resTotalTime, array[0.2,0.4,0.6])
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