TiDB RC3 Release Notes
On June 16, 2017, TiDB RC3 is released! This release is focused on MySQL compatibility, SQL optimization, stability, and performance.
Highlight
- The privilege management is refined to enable users to manage the data access privileges using the same way as in MySQL.
- DDL is accelerated.
- The load balancing policy and process are optimized for performance.
- TiDB Ansible is open sourced. By using TiDB-Ansible, you can deploy, upgrade, start and shutdown a TiDB cluster with one click.
Detailed updates
TiDB
- The following features are added or improved in the SQL query optimizer:
- Support incremental statistics
- Support the
Merge Sort Join
operator - Support the
Index Lookup Join
operator - Support the
Optimizer Hint
Syntax - Optimize the memory consumption of the
Scan
,Join
,Aggregation
operators - Optimize the Cost Based Optimizer (CBO) framework
- Refactor
Expression
- Support more complete privilege management
- DDL acceleration
- Support using HTTP API to get the data distribution information of tables
- Support using system variables to control the query concurrency
- Add more MySQL built-in functions
- Support using system variables to automatically split a big transaction into smaller ones to commit
Placement Driver (PD)
- Support gRPC
- Provide the Disaster Recovery Toolkit
- Use Garbage Collection to clear stale data automatically
- Support more efficient data balance
- Support hot Region scheduling to enable load balancing and speed up the data importing
- Performance
- Accelerate getting Client TSO
- Improve the efficiency of Region Heartbeat processing
- Improve the
pd-ctl
function- Update the Replica configuration dynamically
- Get the Timestamp Oracle (TSO)
- Use ID to get the Region information
TiKV
- Support gRPC
- Support the Sorted String Table (SST) format snapshot to improve the load balancing speed of a cluster
- Support using the Heap Profile to uncover memory leaks
- Support Streaming SIMD Extensions (SSE) and speed up the CRC32 calculation
- Accelerate transferring leader for faster load balancing
- Use Batch Apply to reduce CPU usage and improve the write performance
- Support parallel Prewrite to improve the transaction write speed
- Optimize the scheduling of the coprocessor thread pool to reduce the impact of big queries on point get
- The new Loader supports data importing at the table level, as well as splitting a big table into smaller logical blocks to import concurrently to improve the data importing speed.