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- 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
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- Monitoring Alarm
- Historical Documentation
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- API Documentation
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- COS Shipping Task APIs
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- COS Data Import Task APIs
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- Glossary
This document introduces the basic syntax and examples of nested subqueries.
Syntax Format
In some complex statistical analysis scenarios, you need to perform statistical analysis on the original data first and then perform secondary statistical analysis on the analysis results. In this case, you need to nest a
SELECT statement into another SELECT statement. This query method is called nested subquery.* | SELECT key FROM (subquery)
subquery: subquery, which needs to be enclosed in parentheses.
key: fields that need to be obtained from a subquery for secondary statistical analysis.
Two or more levels of nesting is supported.
Syntax Example
Calculate the ratio of the page views (PVs) of the current hour to the PVs of the same time period the day before:
Set the time range for search and analysis to 1 hour and execute the following search and analysis statement, where
86400 indicates the current time minus 86400 seconds (1 day).Search and analysis statement
* | SELECT compare(PV, 86400) FROM (SELECT count(*) AS PV)
SELECT count(*) AS PV is level-1 statistical analysis: analyze the website PV based on raw logs.SELECT compare(PV, 86400) FROM is level-2 statistical analysis: perform secondary statistical analysis based on the PV result of the level-1 statistical analysis. Use the compare function to obtain the website PV of the day before.Search and analysis result
1860: indicates the PVs of the current 1 hour.
1656: indicates the PVs of the same time period the day before.
1.1231884057971016: indicates the ratio of the PVs of the current hour to the PVs of the same time period the day before.
To display the search and analysis result in multiple columns, perform a further nested search:
Search and analysis statement
* |SELECT compare[1] AS today, compare[2] AS yesterday, compare[3] AS ratioFROM (SELECT compare(PV, 86400) AS compareFROM (SELECT COUNT(*) AS PV))
SELECT compare[1] AS today, compare[2] AS yesterday, compare[3] AS ratio FROM is to get the value of a specified position in the result of the compare function based on the array subscript.Search and analysis result
Yes
No
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