heterogeneous database. It focuses on how to make full and reasonable use of the computing and storage capabilities of existing databases rather than creating a brand new database. It attaches greater importance hybrid engine based on XA and BASE transac‐ tions, ShardingSphere provides distributed transaction capabilities on top of standalone databases, enabling data security across underlying data sources. Re ad with business access with high stress. Sharding‐ Sphere provides flexible read/write splitting capabilities and can achieve read access load balancing based on the understanding of SQL semantics and the

heterogeneous database. It focuses on how to make full and reasonable use of the computing and storage capabilities of existing databases rather than creating a brand new database. It attaches greater importance hybrid engine based on XA and BASE transac‐ tions, ShardingSphere provides distributed transaction capabilities on top of standalone databases, enabling data security across underlying data sources. Re ad with business access with high stress. Sharding‐ Sphere provides flexible read/write splitting capabilities and can achieve read access load balancing based on the understanding of SQL semantics and the

heterogeneous database. It focuses on how to make full and reasonable use of the computing and storage capabilities of existing databases rather than creating a brand new database. It attaches greater importance hybrid engine based on XA and BASE trans‐ actions, ShardingSphere provides distributed transaction capabilities on top of standalone databases, enabling data security across underlying data sources. Read/write with business access with high stress. Sharding‐ Sphere provides flexible read/write splitting capabilities and can achieve read access load balancing based on the understanding of SQL semantics and the

heterogeneous database. It focuses on how to make full and reasonable use of the computing and storage capabilities of existing databases rather than creating a brand new database. It attaches greater importance of the underlying database, ShardingSphere provides flexible and secure read/write splitting capabilities and can achieve load balancing for read access. High Avail‐ ability High availability is flexibility thanks to custom systems based on multi‐level (kernel, feature, and ecosystem) plugin capabilities. 1.1. What is ShardingSphere 3 Apache ShardingSphere document, v5.2.0 1.1.4 Roadmap 1.1.5

Kernel Layer, L2 Feature Layer and L3 Ecosystem Layer. L1 Kernel Layer An abstraction of basic capabilities of database. All components are required and the specific imple‐ mentation can be replaced by (algorithmDefinition) rateLimiter: RATE_LIMITER (algorithmDefinition) streamChannel: STREAM_CHANNEL (algorithmDefinition) workerThread: WORKER_THREAD=intValue batchSize: BATCH_SIZE=intValue intValue: BATCH_SIZE=1000 ), 5.2. ShardingSphere-Proxy 170 Apache ShardingSphere document, v5.1.1 STREAM_CHANNEL(TYPE(NAME=MEMORY, PROPERTIES("block-queue-size"=10000))), COMPLETION_DETECTOR(TYPE(NAME=IDLE, P

Kernel Layer, L2 Feature Layer and L3 Ecosystem Layer. L1 Kernel Layer An abstraction of basic capabilities of database. All components are required and the specific imple‐ mentation can be replaced by (algorithmDefinition) rateLimiter: RATE_LIMITER (algorithmDefinition) streamChannel: STREAM_CHANNEL (algorithmDefinition) workerThread: WORKER_THREAD=intValue batchSize: BATCH_SIZE=intValue intValue: WORKER_THREAD=40, BATCH_SIZE=1000 ), OUTPUT( WORKER_THREAD=40, BATCH_SIZE=1000 ), STREAM_CHANNEL(TYPE(NAME=MEMORY, PROPERTIES("block-queue-size"=10000))), COMPLETION_DETECTOR(TYPE(NAME=IDLE, P

Kernel Layer, L2 Feature Layer and L3 Ecosystem Layer. L1 Kernel Layer An abstraction of basic capabilities of database. All components are required and the specific imple‐ mentation can be replaced by seamlessly with ShardingSphere. There are currently Log, metrics, APM and other observability capabilities available. Usage Local build > cd shardingsphere/shardingsphere-agent > mvn clean install on database‐level solutions in full‐link pressure testing scenarios. Kernel‐based SQL analysis capabilities and a pluggable platform architecture realize the isolation of pressure test data and production

seamlessly with ShardingSphere. There are currently Log, metrics, APM and other observability capabilities available. Usage Local build > cd shardingsphere/shardingsphere-agent > mvn clean install value port Listening port of HTTP server 8888 bloc kQueu eS‐ ize Queue size of data transmission channel 10000 wo rkerT hread Worker thread pool size, the number of migration task threads al‐ lowed to

ShowMigrationRule ::= 'SHOW' 'MIGRATION' 'RULE' 返回值说明 列 说明 read 数据读取配置 write 数据写入配置 stream_channel 数据通道 示例 • 查询数据迁移规则 SHOW MIGRATION RULE; mysql> SHOW MIGRATION RULE; +---------------------- -------------------+-------------------------------------------------------+ | read | write | stream_channel | +--------------------------------------------------------------+------------------- -------- batchSize ',')? ('SHARDING_SIZE' '=' shardingSize ',')? (rateLimiter)? ')' dataChannel ::= 'STREAM_CHANNEL' '(' 'TYPE' '(' 'NAME' '=' algorithmName ',' propertiesDefinition ')' ')' workerThreadPoolSize

ShowMigrationRule ::= 'SHOW' 'MIGRATION' 'RULE' 返回值说明 列 说明 read 数据读取配置 write 数据写入配置 stream_channel 数据通道 9.2. ShardingSphere-Proxy 292 Apache ShardingSphere document 示例 • 查询数据迁移规则 SHOW MIGRATION -------------------+-------------------------------------------------------+ | read | write | stream_channel | +--------------------------------------------------------------+------------------- -------- (rateLimiter)? ')' 9.2. ShardingSphere-Proxy 293 Apache ShardingSphere document dataChannel ::= 'STREAM_CHANNEL' '(' 'TYPE' '(' 'NAME' '=' algorithmName ',' propertiesDefinition ')' ')' workerThreadPoolSize