system accurately. 4.9.2 Challenges pressure testing on production environment is a complex and huge task. Coordination and adjustments between microservices and middlewares required to cope with the transparent ), STREAM_CHANNEL(TYPE(NAME=MEMORY, PROPERTIES("block-queue-size"=10000))), COMPLETION_DETECTOR(TYPE(NAME=IDLE, PROPERTIES("incremental-task-idle-seconds- threshold"=1800))), DATA_CONSISTENCY_CHE {"workerThread":40, "batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":"10000"}} | {"type ":"IDLE","props":{"incremental-task-idle-seconds-threshold":"1800"}} | {"type": "DATA_MATCH","props":

system accurately. 4.9.2 Challenges pressure testing on production environment is a complex and huge task. Coordination and adjustments between microservices and middlewares required to cope with the transparent 1.1 STREAM_CHANNEL(TYPE(NAME=MEMORY, PROPERTIES("block-queue-size"=10000))), COMPLETION_DETECTOR(TYPE(NAME=IDLE, PROPERTIES("incremental-task-idle-minute- threshold"=30))), DATA_CONSISTENCY_CHECKE {"workerThread":40, "batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":"10000"}} | {"type ":"IDLE","props":{"incremental-task-idle-minute-threshold":"30"}} | {"type":"DATA_ MATCH","props":{"chunk-size":"1000"}}

system accurately. 8.9.2 Challenges pressure testing on production environment is a complex and huge task. Coordination and adjustments between microservices and middlewares required to cope with the transparent logs. f a l s e T r u e kerne l‐exe cutor ‐size (?) i n t Set the size of the thread pool for task pro‐ cessing. Each ShardingSphere‐ DataSource uses an independent thread pool, and different "shardingSize":10000000} | {"workerThread ":20,"batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":"2000"}} | +--------------------------------------------------------------+-------------------

and performance of the system. 4.8.2 Challenges Full‐link pressure testing is a complex and huge task. Coordination and adjustments between microser‐ vices and middleware required to cope with the transparent blockQueueSize: 10000 workerThread: 40 clusterAutoSwitchAlgorithm: type: IDLE props: incremental-task-idle-minute-threshold: 30 dataConsistencyCheckAlgorithm: type: DEFAULT mode: type: Cluster repository: Description De fault value bloc kQueu eSize Queue size of data transmission channel 10000 wo rkerT hread Worker thread pool size, the number of migration task threads allowed to run concurrently 40

system accurately. 8.9.2 Challenges pressure testing on production environment is a complex and huge task. Coordination and adjustments between microservices and middlewares required to cope with the transparent logs. f a l s e T r u e kerne l‐exe cutor ‐size (?) i n t Set the size of the thread pool for task pro‐ cessing. Each ShardingSphere‐ DataSource uses an independent thread pool, and different "shardingSize":10000000} | {"workerThread ":20,"batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":"2000"}} | +--------------------------------------------------------------+-------------------

system accurately. 3.9.2 Challenges pressure testing on production environment is a complex and huge task. Coordination and adjustments between microservices and middlewares required to cope with the transparent logs. f a l s e T r u e kern el‐e xecu tor‐ size (?) i n t Set the size of the thread pool for task pro‐ cessing. Each ShardingSphere‐ DataSource uses an independent thread pool，and different "shardingSize":10000000} | {"workerThread ":40,"batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":10000}} | +--------------------------------------------------------------+-------------------

system accurately. 3.9.2 Challenges pressure testing on production environment is a complex and huge task. Coordination and adjustments between microservices and middlewares required to cope with the transparent logs. f a l s e T r u e kernel‐exe cutor‐ size (?) i n t Set the size of the thread pool for task pro‐ cessing. Each ShardingSphere‐ DataSource uses an independent thread pool，and different "shardingSize":10000000} | {"workerThread ":40,"batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":10000}} | +--------------------------------------------------------------+-------------------

each result set (which is realized by Java Comparable interface) and put them into the priority queue. Each time when acquiring the next piece of data, it only needs to move down the result set in the Then put them into the priority queue. the data value of t_score_0 is the biggest, followed by that of t_score_2 and t_score_1 in sequence. Thus, the priority queue is ordered by the sequence of t_score_0 invocation. We can see from the diagram that when using next invocation, t_score_0 at the first of the queue will be popped out. After returning the data value currently pointed by the cursor (i.e., 100) to

), STREAM_CHANNEL(TYPE(NAME=MEMORY, PROPERTIES("block-queue-size"=10000))), COMPLETION_DETECTOR(TYPE(NAME=IDLE, PROPERTIES("incremental-task-idle-seconds- threshold"=1800))), DATA_CONSISTENCY_CHE {"workerThread":40, "batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":"10000"}} | {"type ":"IDLE","props":{"incremental-task-idle-seconds-threshold":"1800"}} | {"type": "DATA_MATCH","props": 算法类型。可选项：MEMORY props: # 算法属性 block-queue-size: # 属性：阻塞队列大小 completionDetector: # 作业是否接近完成检测算法。如果不配置则无法自动进行后续步骤，可以通 过 DistSQL 手动操作。 type: # 算法类型。可选项：IDLE props: # 算法属性 incremental-task-idle-seconds-threshold:

"shardingSize":10000000} | {"workerThread ":20,"batchSize":1000} | {"type":"MEMORY","props":{"block-queue-size":"2000"}} | +--------------------------------------------------------------+------------------- (TYPE(NAME='TPS', PROPERTIES('tps'='2000')))), STREAM_CHANNEL ( TYPE(NAME='MEMORY',PROPERTIES('block-queue-size'='2000'))) ); 保留字 ALTER、MIGRATION、RULE、READ、WRITE、WORKER_THREAD、BATCH_SIZE、SHARDING_SIZE、 +-------------------------------+--------------------------+---------------+ | 0 | ds_1 | EXECUTE_INCREMENTAL_TASK | true | 6 | 100 | 25 | | +------+-------------+--------------------------+--------+-------------------------