. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 xi 1 概览 星评增长时间线 贡献者增长时间线 Apache ShardingSphere 产品定位为 Database Plus，旨在构建异构数据库上层的标准和生态。它关 注如何充分合理地利用数据库的计算和存储能力，而并非实现一个 my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int) my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 xi 1 概览 星评增长时间线 贡献者增长时间线 Apache ShardingSphere 产品定位为 Database Plus，旨在构建异构数据库上层的标准和生态。它关 注如何充分合理地利用数据库的计算和存储能力，而并非实现一个 my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int) my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int)

291 7.24 ANTLR 插件在 src 同级目录下生成代码，容易误提交，如何避免？ . . . . . . . . . . . . 292 viii 1 概览 星评增长时间线 贡献者增长时间线 Apache ShardingSphere 是一套开源的分布式数据库解决方案组成的生态圈，它由 JDBC、Proxy 和 Sidecar （规划中）这 3 款既能够独立部署，又支持混合 每台机器部署一个 MySQL 实例，而对比 MySQL 场景为单机单实例部署。 测试场景 单路由 在 1000 数据量的基础上分库分表，根据 id 分为 4 个库，部署在同一台机器上，根据 k 分为 1024 个表，查 询操作路由到单库单表；作为对比，MySQL 运行在 1000 数据量的基础上，使用 INSERT+UPDATE+DELETE 和单路由查询语句。 主从 基本主从场景 个库，部署在四台不同的机器上，根据 k 分为 1024 个表，c 使用 aes 加密，pad 使用 md5 加密，查询操作路由到单库单表；作为对比，MySQL 运行在 1000 数据量 的基础上，使用 INSERT+UPDATE+DELETE 和单路由查询语句。 全路由 在 1000 数据量的基础上，分库分表，根据 id 分为 4 个库，部署在四台不同的机器上，根据 k 分为 1 个表， 查询操作使用全路由。作为对比，MySQL

缓存会存储列表集合或对象(无论查询方法返回什么)的 1024 个引用。 缓存会被视为是 read/write(可读/可写)的缓存,意味着对象检索不是共享的,而 且可以安全地被调用者修改,而不干扰其他调用者或线 程所做的潜在修改。 所有的这些属性都可以通过缓存元素的属性来修改。比如: List selectList(String statement, Object parameter) <K,V> Map<K,V> selectMap(String statement, Object parameter, String mapKey) int insert(String statement, Object your application? Try the PDFmyURL HTML to PDF API! List selectList(String statement) <K,V> Map<K,V> selectMap(String statement, String mapKey) int insert(String statement) int update(String

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 x 1 概览 星评增长时间线 贡献者增长时间线 Apache ShardingSphere 产品定位为 Database Plus，旨在构建多模数据库上层的标准和生态。它关 注如何充分合理地利用数据库的计算和存储能力，而并非实现一个 分库策略 使用默认分库策略 tab leShar dingSt rat‐ egy (?) S harding Strateg yConfig uration 分表策略 使用默认分表策略 k eyGene rateSt rategy (?) KeyG enerato rConfig uration 自增列生成器 使用默认自增主键生成 器 自动分片表配置 类名称：org.apache 275 Apache ShardingSphere document, v5.0.0 测试场景 单路由 在 1000 数据量的基础上分库分表，根据 id 分为 4 个库，部署在同一台机器上，根据 k 分为 1024 个表，查 询操作路由到单库单表；作为对比，MySQL 运行在 1000 数据量的基础上，使用 INSERT+UPDATE+DELETE 和单路由查询语句。 主从 基本主从场景

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 xi 1 概览 星评增长时间线 贡献者增长时间线 Apache ShardingSphere 产品定位为 Database Plus，旨在构建异构数据库上层的标准和生态。它关 注如何充分合理地利用数据库的计算和存储能力，而并非实现一个 my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int) my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int)

generally needs to deal with three issues as followings: • How to encrypt the historical data, a.k.a.s clean data. • How to encrypt the newly added data and store it in the database without changing deployed on the same machine and each contains 1024 tables with id used for database sharding and k used for table sharding are designed for this scenario, single route select sql statement is chosen are deployed on different machines and each contains 1024 tables with id used for database sharding, k used for table sharding, c encrypted with aes and pad encrypted with md5 are designed for this scenario

my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int) my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int) generally needs to deal with three issues as followings: • How to encrypt the historical data, a.k.a.s data clean. • How to encrypt the newly added data and store it in the database without changing

my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int) my_avg(int4) (stype = avg_state, sfunc = avg_transfn, finalfunc = avg_finalfn) CREATE TABLE agg_data_2k AS SELECT g FROM generate_series(0, 1999) g; CREATE SCHEMA alt_nsp1; ALTER AGGREGATE alt_agg3(int) generally needs to deal with three issues as followings: • How to encrypt the historical data, a.k.a.s data clean. • How to encrypt the newly added data and store it in the database without changing

generally needs to deal with three issues as followings: • How to encrypt the historical data, a.k.a.s data clean. • How to encrypt the newly added data and store it in the database without changing ration Tables sharding strat‐ egy Use default tables sharding strategy keyG enera teStr ategy (?) K eyGene ratorC on‐ figu ration Key generator configu‐ ration Use default key gener‐ ator Sharding x‐co nnec tion s‐si ze‐p er‐q uery (?) i n t Max opened connec‐ tion size for each query. 1 chec k‐ta ble‐ meta data ‐ena bled (?) b o o l e a n Whether validate table meta data consistency when