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- Data Types
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- 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)
- Overview of Search and Analysis
- 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
- Multi-Topic Search
- Context Search and Analysis
- Custom Redirect
- Downloading Log
- Search and Analysis (Metric Topic)
- Dashboard
- Data Processing documents
- Data Processing
- Data Processing Overview
- 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
Heatmaps display statistical charts by coloring the blocks. For statistical indicators, higher values are represented by darker colors and lower values are represented by lighter colors. Heatmaps are suitable for viewing the overall situation, detecting anomalies, displaying differences among multiple variables, and checking whether there is any correlation between them.
Directions
1. Log in to the CLS console, click Dashboard > Dashboard List, select the dashboard you want to view, click Add Chart, create a new chart, and choose Heat Map as the chart type.
2. Configure the chart according to needs.
Chart Configuration
General configuration
Configuration Item | Description |
Basic Information | Chart Name: Set the display name of the table, which can be left empty. |
Statistical Analysis Field | Define the chart fields and support manually specifying the fields corresponding to the chart content with default automatic adaptation. X-axis field: Select the field corresponding to the heatmap X-axis. Y-axis field: Select the field corresponding to the heatmap Y-axis. Metric field: Select the field corresponding to the heatmap block. |
Axes | Show X-axis: Show/hide X-axis. Y-axis position: Configure the display position of the Y-axis. |
Standard configuration | |
Visual mapping | Show/hide Visual Map Configuration. |
Interaction event | Support clicking the numbers in the chart to trigger interactive events, such as jumping to the set URL address, opening the search analysis page, opening the dashboard page, adding filter conditions, etc. For details, see Interaction Event. |
Heatmap configuration
Configuration Item | Description |
Heat Map | Counts: Setting the display and hide of heatmap block value tags. The value is hidden by default. |
Sample Statement
Statistics of average request delays from ISPs on the timestamp:
* | select histogram(__TIMESTAMP__,interval 1 hour) as time,isp,round(avg( "request_time" ),1) as "request_time" group by time,isp order by time limit 10000
Statistics of URL access the province distribution of PV:
* | select url,prov, count(*) as count group by url,prov order by count desc limit 1000
Yes
No
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