Нет описания

Yang Shuang c00345d0bb 170 supporting set statement (#177) 1 год назад
.gitee eb4f0a02de Initial commit 2 лет назад
.github c00345d0bb 170 supporting set statement (#177) 1 год назад
conf f6906c0f8d 141 agent if no specified schema return hint msg (#164) 1 год назад
dockerfiles 4809ccd744 fix: add my.conf to support utf8 (#139) 1 год назад
docs 7fc26e168d async-conn: rename from async-connector. (#122) 1 год назад
script c00345d0bb 170 supporting set statement (#177) 1 год назад
src c00345d0bb 170 supporting set statement (#177) 1 год назад
tests d573388dde 154 dtc supporting limit in dtc (#169) 1 год назад
.clang-format 8bec0f37c1 update markdown. (#12) 2 лет назад
.gitignore 81b21677a6 V0.2.0 mysql protocol compatible (#29) 2 лет назад
.travis.yml f46d41664f dockerfile: fix bug. (#115) 1 год назад
CMakeLists.txt f55a6ad480 fix bigs (#18) 2 лет назад
LICENSE 222612cab3 license change. 2 лет назад
README.md f878825695 Update README.md 1 год назад
README.zh.md 645754e729 README: update CN readme file for github actions. (#59) 1 год назад

README.md

DTC

DTC - Distributed Table Cache

Overview

DTC is a high performance Distributed Table Cache system designed by JD.com that offering hotspot data cache for databases in order to reduce pressure of database and improve QPS.

The DTC system consists of the following components:

  • Agent - Provides key consistent hash routing in order to reduce connections and improve performance.
  • Dtcd - Provides hot data caching service.
  • Connector - Provides connection and communication between cache and persistent storage database such as MYSQL.

Feature

  • Database Protection
    • protection for null node, prevent cache breakdown.
    • provide long-term data caching, and prevent cache penetration.
    • data source thread available, protect the database with a limited number of connections.
    • Estimated timeout policy to reduce invalid database requests.
  • Data consistency
    • write-through policy, ensure cache and database data consistent.
    • barrier policy to prevent update requests lost while concurrcy.
  • Performance
    • integrated memroy allocation policy to avoid frequent system calls.
    • I/O multiplexing to handle concurrcy requests.
    • multiple data structure models to improve memory performance.
  • Scalability

    • cache node expands horizontally to enhance cache capacity.
    • cache node expands vertically, supports slave reading, and solve the bottleneck of hot keys.
    • provide sharding, supports for persistent storage scalable.

      Performance

  • DTC can process 90,000 QPS of query requests at single-core cpu & single dtc instance.

  • DTC can provide above 3,000,000 QPS query capability with above 99.9% hit rate and less than 200 μs response time in actual distributed scenarios.

    How to Build

    DTC provides docker images for quick start:

  • Start server docker:

    docker pull dtc8/server:latest
    docker run -i -t --name dtc-server -p 127.0.0.1:20015:20015 dtc8/server:latest
    

    Depending on 3rd-party sql parsing engine hsql . For more compile information, click Building.
    Trying a demo, visit QuickStart.

License

JD.com © Copyright 2022 JD.com, Inc.
Apache 2.0. Visit LICENSE for more details.