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Release date: June 28, 2019

TiKV version: 3.0.0

TiKV

  • Engine

    • Introduce Titan, a key-value plugin that improves write performance for scenarios with value sizes greater than 1KiB, and relieves write amplification in certain degrees
    • Optimize memory management to reduce memory allocation and copying for Iterator Key Bound Option
    • Support block cache sharing among different column families

  • Server

    • Support reversed raw_scan and raw_batch_scan
    • Support batch receiving and sending Raft messages, improving TPS by 7% for write intensive scenarios
    • Support getting monitoring information via HTTP
    • Support Local Reader in RawKV to improve performance
    • Reduce context switch overhead from batch commands

  • Raftstore

    • Support Multi-thread Raftstore and Multi-thread Apply to improve scalabilities, concurrency capacity, and resource usage within a single node. Performance improves by 70% under the same level of pressure
    • Support checking RocksDB Level 0 files before applying snapshots to avoid write stall
    • Support Hibernate Regions to optimize CPU consumption from RaftStore (Experimental)
    • Remove the local reader thread

  • Transaction

    • Support distributed GC and concurrent lock resolving for improved GC performance
    • Support the pessimistic transaction model (Experimental)
    • Modify the semantics of Insert to allow Prewrite to succeed only when there is no Key
    • Remove txn scheduler
    • Add monitoring items related to read index and GC worker

  • Coprocessor

    • Refactor the computation framework to implement vector operators, computation using vector expressions, and vector aggregations to improve performance
    • Support providing operator execution status for the EXPLAIN ANALYZE statement in TiDB
    • Switch to the work-stealing thread pool model to reduce context switch cost

  • Misc

    • Develop a unified log format specification with restructured log system to facilitate collection and analysis by tools
    • Add performance metrics related to configuration information and key bound crossing.

PD

  • Support re-creating a cluster from a single node

  • Migrate Region metadata from etcd to the go-leveldb storage engine to solve the storage bottleneck in etcd for large-scale clusters

  • API

    • Add the remove-tombstone API to clear Tombstone stores
    • Add the ScanRegions API to batch query Region information
    • Add the GetOperator API to query running operators
    • Optimize the performance of the GetStores API

  • Configurations

    • Optimize configuration check logic to avoid configuration item errors
    • Add enable-one-way-merge to control the direction of Region merge
    • Add hot-region-schedule-limit to control the scheduling rate for hot Regions
    • Add hot-region-cache-hits-threshold to identify hotspot when hitting multiple thresholds consecutively
    • Add the store-balance-rate configuration item to control the maximum numbers of balance Region operators allowed per minute

  • Scheduler Optimizations

    • Add the store limit mechanism for separately controlling the speed of operators for each store
    • Support the waitingOperator queue to optimize the resource race among different schedulers
    • Support scheduling rate limit to actively send scheduling operations to TiKV. This improves the scheduling rate by limiting the number of concurrent scheduling tasks on a single node.
    • Optimize the Region Scatter scheduling to be not restrained by the limit mechanism
    • Add the shuffle-hot-region scheduler to facilitate TiKV stability test in scenarios of poor hotspot scheduling

  • Simulator

    • Add simulator for data import scenarios
    • Support setting different heartbeats intervals for the Store

  • Others

    • Upgrade etcd to solve the issues of inconsistent log output formats, Leader selection failure in prevote, and lease deadlocking.
    • Develop a unified log format specification with restructured log system to facilitate collection and analysis by tools
    • Add monitoring metrics including scheduling parameters, cluster label information, time consumed by PD to process TSO requests, Store ID and address information, etc.