access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the system. In availability secondary databases may be inconsistent for a short time. Load balancer policy Channel query requests to different secondary databases through load balancer policy. 3.3.7 Limitations • Data synchronization storage node responsible for the read traffic in a Shard‐ ingSphere cluster receives overloaded requests, the traffic limit function is used to block traffic from compute nodes to the storage node, to

access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the system. In availability secondary databases may be inconsistent for a short time. Load balancer policy Channel query requests to different secondary databases through load balancer policy. 3.3.7 Limitations • Data synchronization storage node responsible for the read traffic in a Shard‐ ingSphere cluster receives overloaded requests, the traffic limit function is used to block traffic from compute nodes to the storage node, to

other Apache ShardingSphere nodes. Request Limit In the face of overload requests, open request limiting to protect some requests can still respond quickly. 4.3 Sharding 4.3.1 Background The traditional access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the system. In availability consumption. Secondly, ShardingSphere further optimizes the query that only falls into single shards. Requests of this kind can guarantee the correctness of records without rewriting SQLs. Under this kind of

other Apache ShardingSphere nodes. Request Limit In the face of overload requests, open request limiting to protect some requests can still respond quickly. 4.3 Sharding 4.3.1 Background The traditional access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the system. In availability consumption. Secondly, ShardingSphere further optimizes the query that only falls into single shards. Requests of this kind can guarantee the correctness of records without rewriting SQLs. Under this kind of

access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the system. In availability send the SQL through JDBC to directly execute in the underlying data source, or put execu‐ tion requests directly to the thread pool to concurrently execute, but focuses more on the creation of a balanced there is some chance for deadlock, if it has not dealt with concurrency properly. As multiple requests waiting for each other to release database connection resources, it will generate hunger wait and

access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the system. In availability secondary databases may be inconsistent for a short time. Load balancer policy Channel query requests to different secondary databases through load balancer policy. 8.3.7 Limitations • Data synchronization storage node responsible for the read traffic in a Shard‐ ingSphere cluster receives overloaded requests, the traffic limit function is used to block traffic from compute nodes to the storage node, to

access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the system. In availability secondary databases may be inconsistent for a short time. Load balancer policy Channel query requests to different secondary databases through load balancer policy. 8.3.7 Limitations • Data synchronization storage node responsible for the read traffic in a Shard‐ ingSphere cluster receives overloaded requests, the traffic limit function is used to block traffic from compute nodes to the storage node, to

--mysql-db=sbtest --tables=10 --table- size=1000000 --report-interval=10 --time=3600 --threads=10 --max-requests=0 -- percentile=99 --mysql-ignore-errors="all" --rand-type=uniform --range_selects=off - -auto_inc=off --mysql-db=sbtest --tables=10 --table- size=1000000 --report-interval=10 --time=3600 --threads=10 --max-requests=0 -- percentile=99 --mysql-ignore-errors="all" --rand-type=uniform --range_selects=off - -auto_inc=off --mysql-db=sbtest --tables=10 --table- size=1000000 --report-interval=30 --time=180 --threads=256 --max-requests=0 -- percentile=99 --mysql-ignore-errors="all" --range_selects=off --rand-type=uniform --auto_inc=off

ZooKeeper 容器的资源限制 {} governance .zookeeper. resource s.requests. memory ZooKeeper 容器申请的内存 2 56Mi governa nce.zookeeper. resou rces.requests.cpu ZooKeeper 容器申请的 cpu 核数 “ 250m“ 4.2. ShardingSphere-Proxy limits ShardingSphere‐Proxy 容器的资 源限制 {} compute.resour ces. requests.memory ShardingSphere‐Proxy 容器申请 的内存 2Gi compute.res ources. requests.cpu ShardingSphere‐Proxy 容器申请 的 cpu 核数 200m compute.replicas enabled: false storageClass: "" accessModes: - ReadWriteOnce size: 8Gi ## ZooKeeper's resource requests and limits ## ref: https://kubernetes.io/docs/user-guide/compute-resources/ ## @param governance

ZooKeeper 容器的资源限制 {} govern ance.zookeeper. resour ces.requests. memory ZooKeeper 容器申请的内存 “ 256Mi“ gov ernance.zookeeper. res ources.requests.cpu ZooKeeper 容器申请的 cpu 核数 ‘ 250m‘ 9.2. ShardingSphere-Proxy limits ShardingSphere‐Proxy 容器的资 源限制 {} compute.resou rces. requests.memory ShardingSphere‐Proxy 容器申请 的内存 2Gi compute.re sources. requests.cpu ShardingSphere‐Proxy 容器申请 的 cpu 核数 200m compute.replicas enabled: false storageClass: "" accessModes: - ReadWriteOnce size: 8Gi ## ZooKeeper's resource requests and limits ## ref: https://kubernetes.io/docs/user-guide/compute-resources/ ## @param governance