- Introduction
-
Concepts
- Architecture
-
Key Features
- Horizontal Scalability
- MySQL Compatible Syntax
- Replicate from and to MySQL
- Distributed Transactions with Strong Consistency
- Cloud Native Architecture
- Minimize ETL with HTAP
- Fault Tolerance & Recovery with Raft
- Automatic Rebalancing
- Deployment and Orchestration with Ansible, Kubernetes, Docker
- JSON Support
- Spark Integration
- Read Historical Data Without Restoring from Backup
- Fast Import and Restore of Data
- Hybrid of Column and Row Storage
- SQL Plan Management
- Open Source
- Online Schema Changes
- How-to
-
Reference
-
SQL
- MySQL Compatibility
- SQL Language Structure
- Attributes
- Data Types
-
Functions and Operators
- Function and Operator Reference
- Type Conversion in Expression Evaluation
- Operators
- Control Flow Functions
- String Functions
- Numeric Functions and Operators
- Date and Time Functions
- Bit Functions and Operators
- Cast Functions and Operators
- Encryption and Compression Functions
- Information Functions
- JSON Functions
- Aggregate (GROUP BY) Functions
- Window Functions
- Miscellaneous Functions
- Precision Math
- List of Expressions for Pushdown
-
SQL Statements
- `ADD COLUMN`
- `ADD INDEX`
- `ADMIN`
- `ALTER DATABASE`
- `ALTER TABLE`
- `ALTER USER`
- `ANALYZE TABLE`
- `BEGIN`
- `COMMIT`
- `CREATE DATABASE`
- `CREATE INDEX`
- `CREATE TABLE LIKE`
- `CREATE TABLE`
- `CREATE USER`
- `CREATE VIEW`
- `DEALLOCATE`
- `DELETE`
- `DESC`
- `DESCRIBE`
- `DO`
- `DROP COLUMN`
- `DROP DATABASE`
- `DROP INDEX`
- `DROP TABLE`
- `DROP USER`
- `DROP VIEW`
- `EXECUTE`
- `EXPLAIN ANALYZE`
- `EXPLAIN`
- `FLUSH PRIVILEGES`
- `FLUSH STATUS`
- `FLUSH TABLES`
- `GRANT <privileges>`
- `INSERT`
- `KILL [TIDB]`
- `LOAD DATA`
- `MODIFY COLUMN`
- `PREPARE`
- `RECOVER TABLE`
- `RENAME INDEX`
- `RENAME TABLE`
- `REPLACE`
- `REVOKE <privileges>`
- `ROLLBACK`
- `SELECT`
- `SET [NAMES|CHARACTER SET]`
- `SET PASSWORD`
- `SET TRANSACTION`
- `SET [GLOBAL|SESSION] <variable>`
- `SHOW CHARACTER SET`
- `SHOW COLLATION`
- `SHOW [FULL] COLUMNS FROM`
- `SHOW CREATE TABLE`
- `SHOW CREATE USER`
- `SHOW DATABASES`
- `SHOW ENGINES`
- `SHOW ERRORS`
- `SHOW [FULL] FIELDS FROM`
- `SHOW GRANTS`
- `SHOW INDEXES [FROM|IN]`
- `SHOW INDEX [FROM|IN]`
- `SHOW KEYS [FROM|IN]`
- `SHOW PRIVILEGES`
- `SHOW [FULL] PROCESSSLIST`
- `SHOW SCHEMAS`
- `SHOW [FULL] TABLES`
- `SHOW TABLE REGIONS`
- `SHOW TABLE STATUS`
- `SHOW [GLOBAL|SESSION] VARIABLES`
- `SHOW WARNINGS`
- `SPLIT REGION`
- `START TRANSACTION`
- `TRACE`
- `TRUNCATE`
- `UPDATE`
- `USE`
- Constraints
- Generated Columns
- Partitioning
- Character Set
- SQL Mode
- Views
- Configuration
- Security
- Transactions
- System Databases
- Errors Codes
- Supported Client Drivers
- Garbage Collection (GC)
- Performance
- Key Monitoring Metrics
- Alert Rules
- Best Practices
- TiSpark
- TiFlash
- TiDB Binlog
- Tools
-
SQL
- TiDB in Kubernetes
- FAQs
- Support
- Contribute
- Adopters
- Roadmap
- Releases
- Glossary
TiDB Monitoring Framework Overview
The TiDB monitoring framework adopts two open source projects: Prometheus and Grafana. TiDB uses Prometheus to store the monitoring and performance metrics and Grafana to visualize these metrics.
About Prometheus in TiDB
As a time series database, Prometheus has a multi-dimensional data model and flexible query language. As one of the most popular open source projects, Prometheus has been adopted by many companies and organizations and has a very active community. PingCAP is one of the active developers and adopters of Prometheus for monitoring and alerting in TiDB, TiKV and PD.
Prometheus consists of multiple components. Currently, TiDB uses the following of them:
- The Prometheus Server to scrape and store time series data
- The client libraries to customize necessary metrics in the application
- An Alertmanager for the alerting mechanism
The diagram is as follows:
About Grafana in TiDB
Grafana is an open source project for analyzing and visualizing metrics. TiDB uses Grafana to display the performance metrics as follows: