- Release Notes and Announcements
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- Getting Started
- Operation Guide
- Resource Management
- Permission Management
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- Collection Overview
- Collecting Logs in Self-Built Kubernetes Cluster
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- Collection by LogListener
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- 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
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- 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
- Practical Tutorial
- Developer Guide
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- Topic Management APIs
- Log Set Management APIs
- Index APIs
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- Data Processing APIs
- Kafka Protocol Consumption APIs
- CKafka Shipping Task APIs
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- COS Shipping Task APIs
- SCF Delivery Task APIs
- Scheduled SQL Analysis APIs
- COS Data Import Task APIs
- Data Types
- Error Codes
- FAQs
- CLS Service Level Agreement
- CLS Policy
- Contact Us
- Glossary
- Release Notes and Announcements
- User Guide
- Product Introduction
- Purchase Guide
- 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
- Practical Tutorial
- Developer Guide
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- Topic Management APIs
- Log Set Management APIs
- Index APIs
- Topic Partition APIs
- Machine Group APIs
- Collection Configuration APIs
- Log APIs
- Metric APIs
- Alarm Policy APIs
- Data Processing APIs
- Kafka Protocol Consumption APIs
- CKafka Shipping Task APIs
- Kafka Data Subscription APIs
- COS Shipping Task APIs
- SCF Delivery Task APIs
- Scheduled SQL Analysis APIs
- COS Data Import Task APIs
- Data Types
- Error Codes
- FAQs
- CLS Service Level Agreement
- CLS Policy
- Contact Us
- Glossary
This document introduces the basic syntax and examples of mathematical calculation functions.
CLS's log analysis feature allows you to analyze logs by analyzing fields of int, long, and double types via mathematical calculation functions and mathematical statistical functions.
Note:
Mathematical calculation functions support operators +-*/%.
x and y in the following functions can be numbers, log fields, or expressions with numerical calculation results.Basic Syntax
Function | Description |
abs(x) | Returns the absolute value of x. |
cbrt(x) | Returns the cube root of x. |
sqrt(x) | Returns the square root of x. |
cosine_similarity(x,y) | Returns the cosine similarity between the vectors x and y.For example, * | SELECT cosine_similarity(MAP(ARRAY['x','y'], ARRAY[1.0,0.0]), MAP(ARRAY['x','y'], ARRAY[0.0,1.0])) returns 0. |
degrees(x) | Converts angle x in radians to degrees. |
radians(x) | Converts angle x in degrees to radians. |
e() | Returns the natural logarithm of the number. |
exp(x) | Returns the exponent of the natural logarithm. |
ln(x) | Returns the natural logarithm of x. |
log2(x) | Returns the base-2 logarithm of x. |
log10(x) | Returns the base-10 logarithm of x. |
log(x,b) | Returns the base-b logarithm of x. |
pi() | Returns the value of Pi, accurate to 14 decimal places. |
pow(x,b) | Returns x raised to the power of b. |
rand() | Returns a random value. |
random(0,n) | Returns a random number within the [0,n) range. |
round(x) | Returns the rounded value of x. |
round(x, N) | Returns x rounded to N decimal places. |
floor(x) | Returns x rounded down to the nearest integer. |
ceiling(x) | Returns x rounded up to the nearest integer. |
from_base(varchar, bigint) | Converts a string into a number based on BASE encoding. |
to_base(x, radix) | Converts a number into a string based on BASE encoding. |
truncate(x) | Returns x rounded to an integer by dropping digits after the decimal point. |
acos(x) | Returns the arc cosine of x. |
asin(x) | Returns the arc sine of x. |
atan(x) | Returns the arc tangent of x. |
atan2(y,x) | Returns the arc tangent of the result of dividing y by x. |
cos(x) | Returns the cosine of x. |
sin(x) | Returns the sine of x. |
cosh(x) | Returns the hyperbolic cosine of x. |
tan(x) | Returns the tangent of x. |
tanh(x) | Returns the hyperbolic tangent of x. |
infinity() | Returns the constant representing positive infinity. |
is_nan(x) | Determines if the target value is Not a Number (NaN). |
nan() | Returns a "Not a Number" (NaN) value. |
mod(x, y) | Returns the remainder when x is divided by y. |
sign(x) | Returns the sign of x represented by 1, 0, or -1. |
width_bucket(x, bound1, bound2, n) | Returns the bucket number of x in an equi-width histogram, with n buckets within bounds of bound1 and bound2. For example, * | select timeCost,width_bucket(timeCost,10,1000,5) |
width_bucket(x, bins) | Returns the bin number of x with specific bins specified by the array bins. For example, * | select timeCost,width_bucket(timeCost,array[10,100,1000]) |
Examples
To compare the PV values of today and yesterday and express the result as a percentage, the query and analysis statement is as follows:
* | SELECT diff [1] AS today, round((diff [3] -1.0) * 100, 2) AS growth FROM (SELECT compare(pv, 86400) as diff FROM (SELECT COUNT(*) as pv FROM log))
Ya
Tidak
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