From 5bb50b2e9535f0f1641ba93c2c26f38a003fbc45 Mon Sep 17 00:00:00 2001 From: Grace Cai Date: Thu, 23 Jan 2025 11:20:58 +0800 Subject: [PATCH 01/11] Add temp.md --- temp.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 temp.md diff --git a/temp.md b/temp.md new file mode 100644 index 000000000000..af27ff4986a7 --- /dev/null +++ b/temp.md @@ -0,0 +1 @@ +This is a test file. \ No newline at end of file From dbb2782639e36f9e8bd588f9761244239f482c42 Mon Sep 17 00:00:00 2001 From: Grace Cai Date: Thu, 23 Jan 2025 11:21:01 +0800 Subject: [PATCH 02/11] Delete temp.md --- temp.md | 1 - 1 file changed, 1 deletion(-) delete mode 100644 temp.md diff --git a/temp.md b/temp.md deleted file mode 100644 index af27ff4986a7..000000000000 --- a/temp.md +++ /dev/null @@ -1 +0,0 @@ -This is a test file. \ No newline at end of file From b595066e2323c460623c0302259153372a60342f Mon Sep 17 00:00:00 2001 From: qiancai Date: Thu, 23 Jan 2025 11:40:17 +0800 Subject: [PATCH 03/11] Update dashboard-monitoring.md --- dashboard/dashboard-monitoring.md | 122 +++++++++++++++++------------- 1 file changed, 71 insertions(+), 51 deletions(-) diff --git a/dashboard/dashboard-monitoring.md b/dashboard/dashboard-monitoring.md index 6d9ee13204aa..d2caf22132a4 100644 --- a/dashboard/dashboard-monitoring.md +++ b/dashboard/dashboard-monitoring.md @@ -21,99 +21,119 @@ summary: 介绍如何通过 TiDB Dashboard 监控页面查看 Performance Overvi Performance Overview 面板按总分结构对 TiDB、TiKV 和 PD 的性能指标进行了编排组织,包含以下三部分内容: -- 总的概览:数据库时间和 SQL 执行时间概览。通过颜色优化法,你可以快速识别数据库负载特征和性能瓶颈。 -- 资源负载:关键指标和资源利用率,包含数据库 QPS、应用和数据库的连接信息和请求命令类型、数据库内部 TSO 和 KV 请求 OPS、TiDB 和 TiKV 的资源使用概况。 -- 自上而下的延迟分解:Query 延迟和连接空闲时间对比、Query 延迟分解、execute 阶段 TSO 请求和 KV 请求的延迟、TiKV 内部写延迟的分解等。 +- **总体概览**:数据库时间和 SQL 执行时间概览。通过颜色优化法,你可以快速识别数据库负载特征和性能瓶颈。 +- **资源负载**:关键指标和资源利用率,包含数据库 QPS、应用和数据库的连接信息和请求命令类型、数据库内部 TSO 和 KV 请求 OPS、TiDB 和 TiKV 的资源使用概况。 +-**自上而下的延迟分解**:Query 延迟和连接空闲时间对比、Query 延迟分解、execute 阶段 TSO 请求和 KV 请求的延迟、TiKV 内部写延迟的分解等。 以下为 Performance Overview 面板监控说明: ### Database Time by SQL Type -- database time: 每秒的总数据库时间 -- sql_type: 每种 SQL 语句每秒消耗的数据库时间 +- `database time`: 每秒的总数据库时间 +- `sql_type`: 每种 SQL 语句每秒消耗的数据库时间 ### Database Time by SQL Phase -- database time: 每秒的总数据库时间 -- get token/parse/compile/execute: 4 个 SQL 处理阶段每秒消耗的数据库时间 +- `database time`: 每秒的总数据库时间 +- `get token/parse/compile/execute`: 4 个 SQL 处理阶段每秒消耗的数据库时间 execute 执行阶段为绿色,其他三个阶段偏红色系,如果非绿色的颜色占比明显,意味着在执行阶段之外数据库消耗了过多时间,需要进一步分析根源。 ### SQL Execute Time Overview -- execute time: execute 阶段每秒消耗的数据库时间 -- tso_wait: execute 阶段每秒同步等待 TSO 的时间 -- kv request type: execute 阶段每秒等待每种 KV 请求类型的时间,总的 KV request 等待时间可能超过 execute time,因为 KV request 是并发的。 +- `execute time`: execute 阶段每秒消耗的数据库时间 +- `tso_wait`: execute 阶段每秒同步等待 TSO 的时间 +- `kv request type`: execute 阶段每秒等待每种 KV 请求类型的时间,总的 KV request 等待时间可能超过 execute time,因为 KV request 是并发的。 绿色系标识代表常规的写 KV 请求(例如 Prewrite 和 Commit),蓝色系标识代表常规的读 KV 请求,其他色系标识需要注意的问题。例如,悲观锁加锁请求为红色,TSO 等待为深褐色。如果非蓝色系或者非绿色系占比明显,意味着执行阶段存在异常的瓶颈。例如,当发生严重锁冲突时,红色的悲观锁时间会占比明显;当负载中 TSO 等待的消耗时间过长时,深褐色会占比明显。 ### QPS -QPS:按 `SELECT`、`INSERT`、`UPDATE` 等类型统计所有 TiDB 实例上每秒执行的 SQL 语句数量 +- `QPS`: 按 `SELECT`、`INSERT`、`UPDATE` 等类型统计所有 TiDB 实例上每秒执行的 SQL 语句数量 ### CPS By Type -CPS By Type:按照类型统计所有 TiDB 实例每秒处理的命令数(Command Per Second) +- `CPS By Type`: 按照类型统计所有 TiDB 实例每秒处理的命令数(Command Per Second) ### Queries Using Plan Cache OPS -Queries Using Plan Cache OPS:所有 TiDB 实例每秒使用 Plan Cache 的查询数量 +- `Queries Using Plan Cache OPS`: 所有 TiDB 实例每秒使用 Plan Cache 的查询数量 ### KV/TSO Request OPS -- kv request total: 所有 TiDB 实例每秒总的 KV 请求数量 -- kv request by type: 按 `Get`、`Prewrite`、 `Commit` 等类型统计在所有 TiDB 实例每秒的请求数据 -- tso - cmd:所有 TiDB 实例每秒发送的 gRPC 请求的数量,每个 gRPC 请求包含一批 (batch) TSO 请求 -- tso - request:所有 TiDB 实例每秒的 TSO 请求数量 +- `kv request total`: 所有 TiDB 实例每秒总的 KV 请求数量 +- `kv request by type`: 按 `Get`、`Prewrite`、 `Commit` 等类型统计在所有 TiDB 实例每秒的请求数据 +- `tso - cmd`: 所有 TiDB 实例每秒发送的 gRPC 请求的数量,每个 gRPC 请求包含一批 (batch) TSO 请求 +- `tso - request`: 所有 TiDB 实例每秒的 TSO 请求数量 通常 tso - request 除以 tso - cmd 等于 TSO 请求 batch 的平均大小。 ### Connection Count -- total:所有 TiDB 的连接数 -- active connections:所有 TiDB 总的活跃连接数 +- `total`: 所有 TiDB 的连接数 +- `active connections`: 所有 TiDB 总的活跃连接数 - 各个 TiDB 的连接数 -### TiDB CPU +### TiDB CPU/Memory -- avg:所有 TiDB 实例平均 CPU 利用率 -- delta:所有 TiDB 实例中最大 CPU 利用率减去所有 TiDB 实例中最小 CPU 利用率 -- max:所有 TiDB 实例中最大 CPU 利用率 +- `CPU-Avg`: 所有 TiDB 实例的平均 CPU 利用率 +- `CPU-Delta`: 所有 TiDB 实例中最大 CPU 利用率减去所有 TiDB 实例中最小 CPU 利用率 +- `CPU-Max`: 所有 TiDB 实例中最大 CPU 利用率 +- `CPU-Quota`: TiDB 可以使用的 CPU 核数 +- `Mem-Max`: 所有 TiDB 实例中最大内存利用率 -### TiKV CPU/IO MBps +### TiKV CPU/Memory -- CPU-Avg:所有 TiKV 实例平均 CPU 利用率 -- CPU-Delta:所有 TiKV 实例中最大 CPU 利用率减去所有 TiKV 实例中最小 CPU 利用率 -- CPU-MAX:所有 TiKV 实例中最大 CPU 利用率 -- IO-Avg:所有 TiKV 实例平均 MBps -- IO-Delta:所有 TiKV 实例中最大 MBps 减去所有 TiKV 实例中最小 MBps -- IO-MAX:所有 TiKV 实例中最大 MBps +- `CPU-Avg`: 所有 TiKV 实例的平均 CPU 利用率 +- `CPU-Delta`: 所有 TiKV 实例中最大 CPU 利用率减去所有 TiKV 实例中最小 CPU 利用率 +- `CPU-Max`: 所有 TiKV 实例中最大 CPU 利用率 +- `CPU-Quota`: TiKV 可以使用的 CPU 核数 +- `Mem-Max`: 所有 TiKV 实例中最大内存利用率 + +### PD CPU/Memory + +- `CPU-Max`: 所有 PD 实例中最大 CPU 利用率 +- `CPU-Quota`: PD 可以使用的 CPU 核数 +- `Mem-Max`: 所有 PD 实例中最大内存利用率 + +### Read Traffic + +- `TiDB -> Client`: 从 TiDB 到客户端的出站流量统计 +- `Rocksdb -> TiKV`: TiKV 在存储层读操作过程中从 RocksDB 获取的数据流量 + +### Write Traffic + +- `Client -> TiDB`: 从客户端到 TiDB 的入站流量统计 +- `TiDB -> TiKV: general`: 前台事务从 TiDB 写入到 TiKV 的速率 +- `TiDB -> TiKV: internal`: 后台事务从 TiDB 写入到 TiKV 的速率 +- `TiKV -> Rocksdb`: 从 TiKV 写入到 RocksDB 的流量 +- `RocksDB Compaction`: RocksDB compaction 操作产生的总读写 I/O 流量。 ### Duration -- Duration:执行时间解释 +- `Duration`: 执行时间解释 - 从客户端网络请求发送到 TiDB,到 TiDB 执行结束后返回给客户端的时间。一般情况下,客户端请求都是以 SQL 语句的形式发送,但也可以包含 `COM_PING`、`COM_SLEEP`、`COM_STMT_FETCH`、`COM_SEND_LONG_DATA` 之类的命令执行时间。 - 由于 TiDB 支持 Multi-Query,因此,客户端可以一次性发送多条 SQL 语句,如 `select 1; select 1; select 1;`。此时的执行时间是所有 SQL 语句执行完成的总时间。 -- avg:所有请求命令的平均执行时间 -- 99: 所有请求命令的 P99 执行时间 -- avg by type:按 `SELECT`、`INSERT`、`UPDATE` 类型统计所有 TiDB 实例上所有请求命令的平均执行时间 +- `avg`: 所有请求命令的平均执行时间 +- `99`: 所有请求命令的 P99 执行时间 +- `avg by type`: 按 `SELECT`、`INSERT`、`UPDATE` 类型统计所有 TiDB 实例上所有请求命令的平均执行时间 ### Connection Idle Duration Connection Idle Duration 指空闲连接的持续时间。 -- avg-in-txn:处于事务中,空闲连接的平均持续时间 -- avg-not-in-txn:没有处于事务中,空闲连接的平均持续时间 -- 99-in-txn:处于事务中,空闲连接的 P99 持续时间 -- 99-not-in-txn:没有处于事务中,空闲连接的 P99 持续时间 +- `avg-in-txn`: 处于事务中,空闲连接的平均持续时间 +- `avg-not-in-txn`: 没有处于事务中,空闲连接的平均持续时间 +- `99-in-txn`: 处于事务中,空闲连接的 P99 持续时间 +- `99-not-in-txn`: 没有处于事务中,空闲连接的 P99 持续时间 ### Parse Duration、Compile Duration 和 Execute Duration -- Parse Duration:SQL 语句解析耗时统计 -- Compile Duration:将解析后的 SQL AST 编译成执行计划的耗时 -- Execution Duration:执行 SQL 语句执行计划耗时 +- `Parse Duration`: SQL 语句解析耗时统计 +- `Compile Duration`: 将解析后的 SQL AST 编译成执行计划的耗时 +- `Execution Duration`: 执行 SQL 语句执行计划耗时 这三个时间指标均包含均所有 TiDB 实例的平均值和 P99 值。 @@ -127,16 +147,16 @@ Connection Idle Duration 指空闲连接的持续时间。 ### PD TSO Wait/RPC Duration -- wait - avg:所有 TiDB 实例等待从 PD 返回 TSO 的平均时间 -- rpc - avg:所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的平均耗时 -- wait - 99:所有 TiDB 实例等待从 PD 返回 TSO 的 P99 时间 -- rpc - 99:所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的 P99 耗时 +- `wait - avg`: 所有 TiDB 实例等待从 PD 返回 TSO 的平均时间 +- `rpc - avg`: 所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的平均耗时 +- `wait - 99`: 所有 TiDB 实例等待从 PD 返回 TSO 的 P99 时间 +- `rpc - 99`: 所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的 P99 耗时 ### Storage Async Write Duration、Store Duration 和 Apply Duration -- Storage Async Write Duration:异步写所花费的时间 -- Store Duration:异步写 Store 步骤所花费的时间 -- Apply Duration:异步写 Apply 步骤所花费的时间 +- `Storage Async Write Duration`: 异步写所花费的时间 +- `Store Duration`: 异步写 Store 步骤所花费的时间 +- `Apply Duration`: 异步写 Apply 步骤所花费的时间 这三个时间指标都包含所有 TiKV 实例的平均值和 P99 值 @@ -144,8 +164,8 @@ Connection Idle Duration 指空闲连接的持续时间。 ### Append Log Duration、Commit Log Duration 和 Apply Log Duration -- Append Log Duration:Raft append 日志所花费的时间 -- Commit Log Duration:Raft commit 日志所花费的时间 -- Apply Log Duration:Raft apply 日志所花费的时间 +- `Append Log Duration`: Raft append 日志所花费的时间 +- `Commit Log Duration`: Raft commit 日志所花费的时间 +- `Apply Log Duration`: Raft apply 日志所花费的时间 这三个时间指标均包含所有 TiKV 实例的平均值和 P99 值。 \ No newline at end of file From efadaff09bbfe2a99f0ea2a32b103240ff98e589 Mon Sep 17 00:00:00 2001 From: qiancai Date: Thu, 23 Jan 2025 12:10:16 +0800 Subject: [PATCH 04/11] add translation --- dashboard/dashboard-monitoring.md | 114 +++++++++++++++--------------- performance-tuning-methods.md | 90 ++++++++++++++++++----- 2 files changed, 131 insertions(+), 73 deletions(-) diff --git a/dashboard/dashboard-monitoring.md b/dashboard/dashboard-monitoring.md index d2caf22132a4..1306b3887dd9 100644 --- a/dashboard/dashboard-monitoring.md +++ b/dashboard/dashboard-monitoring.md @@ -29,111 +29,111 @@ Performance Overview 面板按总分结构对 TiDB、TiKV 和 PD 的性能指标 ### Database Time by SQL Type -- `database time`: 每秒的总数据库时间 -- `sql_type`: 每种 SQL 语句每秒消耗的数据库时间 +- `database time`:每秒的总数据库时间 +- `sql_type`:每种 SQL 语句每秒消耗的数据库时间 ### Database Time by SQL Phase -- `database time`: 每秒的总数据库时间 -- `get token/parse/compile/execute`: 4 个 SQL 处理阶段每秒消耗的数据库时间 +- `database time`:每秒的总数据库时间 +- `get token/parse/compile/execute`:4 个 SQL 处理阶段每秒消耗的数据库时间 execute 执行阶段为绿色,其他三个阶段偏红色系,如果非绿色的颜色占比明显,意味着在执行阶段之外数据库消耗了过多时间,需要进一步分析根源。 ### SQL Execute Time Overview -- `execute time`: execute 阶段每秒消耗的数据库时间 -- `tso_wait`: execute 阶段每秒同步等待 TSO 的时间 -- `kv request type`: execute 阶段每秒等待每种 KV 请求类型的时间,总的 KV request 等待时间可能超过 execute time,因为 KV request 是并发的。 +- `execute time`:execute 阶段每秒消耗的数据库时间 +- `tso_wait`:execute 阶段每秒同步等待 TSO 的时间 +- `kv request type`:execute 阶段每秒等待每种 KV 请求类型的时间,总的 KV request 等待时间可能超过 execute time,因为 KV request 是并发的。 绿色系标识代表常规的写 KV 请求(例如 Prewrite 和 Commit),蓝色系标识代表常规的读 KV 请求,其他色系标识需要注意的问题。例如,悲观锁加锁请求为红色,TSO 等待为深褐色。如果非蓝色系或者非绿色系占比明显,意味着执行阶段存在异常的瓶颈。例如,当发生严重锁冲突时,红色的悲观锁时间会占比明显;当负载中 TSO 等待的消耗时间过长时,深褐色会占比明显。 ### QPS -- `QPS`: 按 `SELECT`、`INSERT`、`UPDATE` 等类型统计所有 TiDB 实例上每秒执行的 SQL 语句数量 +- `QPS`:按 `SELECT`、`INSERT`、`UPDATE` 等类型统计所有 TiDB 实例上每秒执行的 SQL 语句数量 ### CPS By Type -- `CPS By Type`: 按照类型统计所有 TiDB 实例每秒处理的命令数(Command Per Second) +- `CPS By Type`:按照类型统计所有 TiDB 实例每秒处理的命令数(Command Per Second) ### Queries Using Plan Cache OPS -- `Queries Using Plan Cache OPS`: 所有 TiDB 实例每秒使用 Plan Cache 的查询数量 +- `Queries Using Plan Cache OPS`:所有 TiDB 实例每秒使用 Plan Cache 的查询数量 ### KV/TSO Request OPS -- `kv request total`: 所有 TiDB 实例每秒总的 KV 请求数量 -- `kv request by type`: 按 `Get`、`Prewrite`、 `Commit` 等类型统计在所有 TiDB 实例每秒的请求数据 -- `tso - cmd`: 所有 TiDB 实例每秒发送的 gRPC 请求的数量,每个 gRPC 请求包含一批 (batch) TSO 请求 -- `tso - request`: 所有 TiDB 实例每秒的 TSO 请求数量 +- `kv request total`:所有 TiDB 实例每秒总的 KV 请求数量 +- `kv request by type`:按 `Get`、`Prewrite`、 `Commit` 等类型统计在所有 TiDB 实例每秒的请求数据 +- `tso - cmd`:所有 TiDB 实例每秒发送的 gRPC 请求的数量,每个 gRPC 请求包含一批 (batch) TSO 请求 +- `tso - request`:所有 TiDB 实例每秒的 TSO 请求数量 通常 tso - request 除以 tso - cmd 等于 TSO 请求 batch 的平均大小。 ### Connection Count -- `total`: 所有 TiDB 的连接数 -- `active connections`: 所有 TiDB 总的活跃连接数 +- `total`:所有 TiDB 的连接数 +- `active connections`:所有 TiDB 总的活跃连接数 - 各个 TiDB 的连接数 ### TiDB CPU/Memory -- `CPU-Avg`: 所有 TiDB 实例的平均 CPU 利用率 -- `CPU-Delta`: 所有 TiDB 实例中最大 CPU 利用率减去所有 TiDB 实例中最小 CPU 利用率 -- `CPU-Max`: 所有 TiDB 实例中最大 CPU 利用率 -- `CPU-Quota`: TiDB 可以使用的 CPU 核数 -- `Mem-Max`: 所有 TiDB 实例中最大内存利用率 +- `CPU-Avg`:所有 TiDB 实例的平均 CPU 利用率 +- `CPU-Delta`:所有 TiDB 实例中最大 CPU 利用率减去所有 TiDB 实例中最小 CPU 利用率 +- `CPU-Max`:所有 TiDB 实例中最大 CPU 利用率 +- `CPU-Quota`:TiDB 可以使用的 CPU 核数 +- `Mem-Max`:所有 TiDB 实例中最大内存利用率 ### TiKV CPU/Memory -- `CPU-Avg`: 所有 TiKV 实例的平均 CPU 利用率 -- `CPU-Delta`: 所有 TiKV 实例中最大 CPU 利用率减去所有 TiKV 实例中最小 CPU 利用率 -- `CPU-Max`: 所有 TiKV 实例中最大 CPU 利用率 -- `CPU-Quota`: TiKV 可以使用的 CPU 核数 -- `Mem-Max`: 所有 TiKV 实例中最大内存利用率 +- `CPU-Avg`:所有 TiKV 实例的平均 CPU 利用率 +- `CPU-Delta`:所有 TiKV 实例中最大 CPU 利用率减去所有 TiKV 实例中最小 CPU 利用率 +- `CPU-Max`:所有 TiKV 实例中最大 CPU 利用率 +- `CPU-Quota`:TiKV 可以使用的 CPU 核数 +- `Mem-Max`:所有 TiKV 实例中最大内存利用率 ### PD CPU/Memory -- `CPU-Max`: 所有 PD 实例中最大 CPU 利用率 -- `CPU-Quota`: PD 可以使用的 CPU 核数 -- `Mem-Max`: 所有 PD 实例中最大内存利用率 +- `CPU-Max`:所有 PD 实例中最大 CPU 利用率 +- `CPU-Quota`:PD 可以使用的 CPU 核数 +- `Mem-Max`:所有 PD 实例中最大内存利用率 ### Read Traffic -- `TiDB -> Client`: 从 TiDB 到客户端的出站流量统计 -- `Rocksdb -> TiKV`: TiKV 在存储层读操作过程中从 RocksDB 获取的数据流量 +- `TiDB -> Client`:从 TiDB 到客户端的出站流量统计 +- `Rocksdb -> TiKV`:TiKV 在存储层读操作过程中从 RocksDB 获取的数据流量 ### Write Traffic -- `Client -> TiDB`: 从客户端到 TiDB 的入站流量统计 -- `TiDB -> TiKV: general`: 前台事务从 TiDB 写入到 TiKV 的速率 -- `TiDB -> TiKV: internal`: 后台事务从 TiDB 写入到 TiKV 的速率 -- `TiKV -> Rocksdb`: 从 TiKV 写入到 RocksDB 的流量 -- `RocksDB Compaction`: RocksDB compaction 操作产生的总读写 I/O 流量。 +- `Client -> TiDB`:从客户端到 TiDB 的入站流量统计 +- `TiDB -> TiKV: general`:前台事务从 TiDB 写入到 TiKV 的速率 +- `TiDB -> TiKV: internal`:后台事务从 TiDB 写入到 TiKV 的速率 +- `TiKV -> Rocksdb`:从 TiKV 写入到 RocksDB 的流量 +- `RocksDB Compaction`:RocksDB compaction 操作产生的总读写 I/O 流量。 ### Duration -- `Duration`: 执行时间解释 +- `Duration`:执行时间解释 - 从客户端网络请求发送到 TiDB,到 TiDB 执行结束后返回给客户端的时间。一般情况下,客户端请求都是以 SQL 语句的形式发送,但也可以包含 `COM_PING`、`COM_SLEEP`、`COM_STMT_FETCH`、`COM_SEND_LONG_DATA` 之类的命令执行时间。 - 由于 TiDB 支持 Multi-Query,因此,客户端可以一次性发送多条 SQL 语句,如 `select 1; select 1; select 1;`。此时的执行时间是所有 SQL 语句执行完成的总时间。 -- `avg`: 所有请求命令的平均执行时间 -- `99`: 所有请求命令的 P99 执行时间 -- `avg by type`: 按 `SELECT`、`INSERT`、`UPDATE` 类型统计所有 TiDB 实例上所有请求命令的平均执行时间 +- `avg`:所有请求命令的平均执行时间 +- `99`:所有请求命令的 P99 执行时间 +- `avg by type`:按 `SELECT`、`INSERT`、`UPDATE` 类型统计所有 TiDB 实例上所有请求命令的平均执行时间 ### Connection Idle Duration Connection Idle Duration 指空闲连接的持续时间。 -- `avg-in-txn`: 处于事务中,空闲连接的平均持续时间 -- `avg-not-in-txn`: 没有处于事务中,空闲连接的平均持续时间 -- `99-in-txn`: 处于事务中,空闲连接的 P99 持续时间 -- `99-not-in-txn`: 没有处于事务中,空闲连接的 P99 持续时间 +- `avg-in-txn`:处于事务中,空闲连接的平均持续时间 +- `avg-not-in-txn`:没有处于事务中,空闲连接的平均持续时间 +- `99-in-txn`:处于事务中,空闲连接的 P99 持续时间 +- `99-not-in-txn`:没有处于事务中,空闲连接的 P99 持续时间 ### Parse Duration、Compile Duration 和 Execute Duration -- `Parse Duration`: SQL 语句解析耗时统计 -- `Compile Duration`: 将解析后的 SQL AST 编译成执行计划的耗时 -- `Execution Duration`: 执行 SQL 语句执行计划耗时 +- `Parse Duration`:SQL 语句解析耗时统计 +- `Compile Duration`:将解析后的 SQL AST 编译成执行计划的耗时 +- `Execution Duration`:执行 SQL 语句执行计划耗时 这三个时间指标均包含均所有 TiDB 实例的平均值和 P99 值。 @@ -147,16 +147,16 @@ Connection Idle Duration 指空闲连接的持续时间。 ### PD TSO Wait/RPC Duration -- `wait - avg`: 所有 TiDB 实例等待从 PD 返回 TSO 的平均时间 -- `rpc - avg`: 所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的平均耗时 -- `wait - 99`: 所有 TiDB 实例等待从 PD 返回 TSO 的 P99 时间 -- `rpc - 99`: 所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的 P99 耗时 +- `wait - avg`:所有 TiDB 实例等待从 PD 返回 TSO 的平均时间 +- `rpc - avg`:所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的平均耗时 +- `wait - 99`:所有 TiDB 实例等待从 PD 返回 TSO 的 P99 时间 +- `rpc - 99`:所有 TiDB 实例从向 PD 发送获取 TSO 的请求到接收到 TSO 的 P99 耗时 ### Storage Async Write Duration、Store Duration 和 Apply Duration -- `Storage Async Write Duration`: 异步写所花费的时间 -- `Store Duration`: 异步写 Store 步骤所花费的时间 -- `Apply Duration`: 异步写 Apply 步骤所花费的时间 +- `Storage Async Write Duration`:异步写所花费的时间 +- `Store Duration`:异步写 Store 步骤所花费的时间 +- `Apply Duration`:异步写 Apply 步骤所花费的时间 这三个时间指标都包含所有 TiKV 实例的平均值和 P99 值 @@ -164,8 +164,8 @@ Connection Idle Duration 指空闲连接的持续时间。 ### Append Log Duration、Commit Log Duration 和 Apply Log Duration -- `Append Log Duration`: Raft append 日志所花费的时间 -- `Commit Log Duration`: Raft commit 日志所花费的时间 -- `Apply Log Duration`: Raft apply 日志所花费的时间 +- `Append Log Duration`:Raft append 日志所花费的时间 +- `Commit Log Duration`:Raft commit 日志所花费的时间 +- `Apply Log Duration`:Raft apply 日志所花费的时间 这三个时间指标均包含所有 TiKV 实例的平均值和 P99 值。 \ No newline at end of file diff --git a/performance-tuning-methods.md b/performance-tuning-methods.md index 0feae6e70900..e177af2da029 100644 --- a/performance-tuning-methods.md +++ b/performance-tuning-methods.md @@ -209,34 +209,92 @@ StmtPrepare 每秒执行次数远大于 StmtClose,说明应用程序存在 pre - 每秒总的 KV 请求数据是 35.5,Cop 请求次数是每秒 9.3。 - KV 处理时间主要来源为 `Cop-internal_stats`,说明 Cop 请求来源于内部的 analyze 操作。 -#### TiDB CPU,以及 TiKV CPU 和 IO 使用情况 +#### CPU 和内存使用情况 -在 TiDB CPU 和 TiKV CPU/IO MBps 这两个面板中,你可以观察到 TiDB 和 TiKV 的逻辑 CPU 使用率和 IO 吞吐,包含平均、最大和 delta(最大 CPU 使用率减去最小 CPU 使用率),从而用来判定 TiDB 和 TiKV 总体的 CPU 使用率。 +在 TiDB、TiKV 和 PD 的 CPU/Memory 面板中,你可以监控它们各自的逻辑 CPU 使用率和内存消耗情况,例如平均 CPU 利用率、最大 CPU 利用率、CPU 利用率差值(最大 CPU 使用率减去最小 CPU 使用率)、CPU 配额以及最大内存使用率。基于这些指标,你可以确定 TiDB、TiKV 和 PD 的整体资源使用情况。 -- 通过 `delta` 值,你可以判断 TiDB 是否存在 CPU 使用负载不均衡(通常伴随着应用连接不均衡),TiKV 是否存在热点。 -- 通过 TiDB 和 TiKV 的资源使用概览,你可以快速判断集群是否存在资源瓶颈,最需要扩容的组件是 TiDB 还是 TiKV。 +- 根据 `delta` 值,你可以判断 TiDB 或 TiKV 的 CPU 使用是否存在不均衡的情况。对于 TiDB,较高的 `delta` 值通常意味着应用程序的连接在 TiDB 实例之间分布不均衡;对于 TiKV,较高的 `delta` 值通常意味着集群中存在读写热点。 +- 通过 TiDB、TiKV 和 PD 的资源使用概览,你可以快速判断集群是否存在资源瓶颈,以及是否需要对 TiKV、TiDB 或 PD 进行扩容或升级。 -**示例 1:TiDB 资源使用率高** +**示例 1:TiKV 资源使用率高** -下图负载中,每个 TiDB 和 TiKV 配置 8 CPU。 +在以下 TPC-C 负载中,每个 TiDB 和 TiKV 配置了 16 个 CPU,PD 配置了 4 个 CPU。 -![TPC-C](/media/performance/tidb_high_cpu.png) +![TPC-C](/media/performance/tpcc_cpu_memory.png) -- TiDB 平均 CPU 为 575%。最大 CPU 为 643%,delta CPU 为 136%。 -- TiKV 平均 CPU 为 146%,最大 CPU 215%。delta CPU 为 118%。TiKV 的平均 IO 吞吐为 9.06 MB/s,最大 IO 吞吐为 19.7 MB/s,delta IO 吞吐为 17.1 MB/s。 +- TiDB 的平均、最大和 delta CPU 使用率分别为 761%、934% 和 322%。最大内存使用率为 6.86 GiB。 +- TiKV 的平均、最大和 delta CPU 使用率分别为 1343%、1505% 和 283%。最大内存使用率为 27.1 GiB。 +- PD 的最大 CPU 使用率为 59.1%。最大内存使用率为 221 MiB。 -由此可以判断,TiDB 的 CPU 消耗明显更高,并接近于 8 CPU 的瓶颈,可以考虑扩容 TiDB。 +显然,TiKV 消耗了更多的 CPU,在 TPC-C 这样的写密集场景中,这是符合预期的。建议通过扩容 TiKV 来提升性能。 -**示例 2:TiKV 资源使用率高** +#### 数据流量 -下图 TPC-C 负载中,每个 TiDB 和 TiKV 配置 16 CPU。 +Read traffic 和 Write traffic 面板可以帮助你深入分析 TiDB 集群内部的流量模式,全面监控从客户端到数据库以及内部组件之间的数据流情况。 -![TPC-C](/media/performance/tpcc_cpu_io.png) +- Read traffic (读流量) + - `TiDB -> Client`:从 TiDB 到客户端的出站流量统计 + - `Rocksdb -> TiKV`:TiKV 在存储层读操作期间从 RocksDB 获取的数据流量 -- TiDB 平均 CPU 为 883%。最大 CPU 为 962%,delta CPU 为 153%。 -- TiKV 平均 CPU 为 1288%,最大 CPU 1360%。delta CPU 为 126%。TiKV 的平均 IO 吞吐为 130 MB/s,最大 IO 吞吐为 153 MB/s,delta IO 吞吐为 53.7 MB/s。 +- Write traffic (写流量) + - `Client -> TiDB`:从客户端到 TiDB 的入站流量统计 + - `TiDB -> TiKV: general`:前台事务从 TiDB 写入到 TiKV 的速率 + - `TiDB -> TiKV: internal`:内部事务从 TiDB 写入到 TiKV 的速率 + - `TiKV -> Rocksdb`:从 TiKV 到 RocksDB 的写操作流量 + - `RocksDB Compaction`:RocksDB compaction 操作产生的总读写 I/O 流量。如果 `RocksDB Compaction` 明显高于 `TiKV -> Rocksdb`,且你的平均行大小高于 512 字节,你可以通过以下配置来减少 compaction I/O 流量:启用 Titan,将 min-blob-size 设置为 `"512B"` 或 `"1KB"`,将 blob-file-compression 设置为 `"zstd"`。 -由此可以判断,TiKV 的 CPU 消耗更高,因为 TPC-C 是一个写密集场景,这是正常现象,可以考虑扩容 TiKV 节点提升性能。 +```toml +[rocksdb.titan] +enabled = true +[rocksdb.defaultcf.titan] +min-blob-size = "1KB" +blob-file-compression = "zstd" +``` + +**示例 1:TPC-C 负载中的读写流量** + +以下是 TPC-C 负载中读写流量的示例。 + +![TPC-C](/media/performance/tpcc_read_write_traffic.png) + +- 读流量 + - `TiDB -> Client`:14.2 MB/s + - `Rocksdb -> TiKV`:469 MB/s。注意,在提交事务之前,读操作(`SELECT` 语句)和写操作(`INSERT`、`UPDATE` 和 `DELETE` 语句)都需要从 RocksDB 读取数据到 TiKV。 + +- 写流量 + - `Client -> TiDB`:5.05 MB/s + - `TiDB -> TiKV: general`:13.1 MB/s + - `TiDB -> TiKV: internal`:5.07 KB/s + - `TiKV -> Rocksdb`:109 MB/s + - `RocksDB Compaction`:567 MB/s + +![TPC-C](/media/performance/tpcc_read_write_traffic.png) + +**示例 2:启用 Titan 前后的写流量** + +以下示例展示了启用 Titan 前后的性能变化。对于 6 KB 数据量的插入负载,Titan 显著降低了写流量和 compaction I/O,提高了 TiKV 的整体性能和资源利用率。 + +- 启用 Titan 前的写流量 + +![Titan 禁用](/media/performance/titan_disable.png) + + - `Client -> TiDB`:510 MB/s + - `TiDB -> TiKV: general`:187 MB/s + - `TiDB -> TiKV: internal`:3.2 KB/s + - `TiKV -> Rocksdb`:753 MB/s + - `RocksDB Compaction`:10.6 GB/s + +- 启用 Titan 后的写流量 + +![Titan 启用](/media/performance/titan_enable.png) + + - `Client -> TiDB`:586 MB/s + - `TiDB -> TiKV: general`:295 MB/s + - `TiDB -> TiKV: internal`:3.66 KB/s + - `TiKV -> Rocksdb`:1.21 GB/s + - `RocksDB Compaction`:4.68 MB/s + +![Titan Enable](/media/performance/titan_enable.png) ### Query 延迟分解和关键的延迟指标 From 04e283359c2af94df0bb2e6f06e2ebb5888193bb Mon Sep 17 00:00:00 2001 From: qiancai Date: Thu, 23 Jan 2025 13:51:04 +0800 Subject: [PATCH 05/11] Update performance-tuning-methods.md --- performance-tuning-methods.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/performance-tuning-methods.md b/performance-tuning-methods.md index e177af2da029..ab7a6a95e0ea 100644 --- a/performance-tuning-methods.md +++ b/performance-tuning-methods.md @@ -218,7 +218,7 @@ StmtPrepare 每秒执行次数远大于 StmtClose,说明应用程序存在 pre **示例 1:TiKV 资源使用率高** -在以下 TPC-C 负载中,每个 TiDB 和 TiKV 配置了 16 个 CPU,PD 配置了 4 个 CPU。 +在以下 TPC-C 负载中,每个 TiDB 和 TiKV 配置了 16 CPU,PD 配置了 4 CPU。 ![TPC-C](/media/performance/tpcc_cpu_memory.png) From 957e01812b2139111a6658ea1b66e6c76bc4a8a9 Mon Sep 17 00:00:00 2001 From: qiancai Date: Thu, 23 Jan 2025 13:53:13 +0800 Subject: [PATCH 06/11] add images --- media/titan_disable.png | Bin 0 -> 122744 bytes media/titan_enable.png | Bin 0 -> 110860 bytes media/tpcc_cpu_memory.png | Bin 0 -> 561956 bytes media/tpcc_read_write_traffic.png | Bin 0 -> 452874 bytes 4 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 media/titan_disable.png create mode 100644 media/titan_enable.png create mode 100644 media/tpcc_cpu_memory.png create mode 100644 media/tpcc_read_write_traffic.png diff --git a/media/titan_disable.png b/media/titan_disable.png new file mode 100644 index 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U-Z7n};6L-tR-5jc{&x2N0IpUBsQ>@~ literal 0 HcmV?d00001 From 01ad7a95e91453230a6d4c61ab96da9d1eb0eb30 Mon Sep 17 00:00:00 2001 From: qiancai Date: Thu, 23 Jan 2025 14:16:04 +0800 Subject: [PATCH 07/11] format updates --- dashboard/dashboard-monitoring.md | 4 +- performance-tuning-methods.md | 76 +++++++++++++++---------------- 2 files changed, 39 insertions(+), 41 deletions(-) diff --git a/dashboard/dashboard-monitoring.md b/dashboard/dashboard-monitoring.md index 1306b3887dd9..4672adb31e25 100644 --- a/dashboard/dashboard-monitoring.md +++ b/dashboard/dashboard-monitoring.md @@ -23,7 +23,7 @@ Performance Overview 面板按总分结构对 TiDB、TiKV 和 PD 的性能指标 - **总体概览**:数据库时间和 SQL 执行时间概览。通过颜色优化法,你可以快速识别数据库负载特征和性能瓶颈。 - **资源负载**:关键指标和资源利用率,包含数据库 QPS、应用和数据库的连接信息和请求命令类型、数据库内部 TSO 和 KV 请求 OPS、TiDB 和 TiKV 的资源使用概况。 --**自上而下的延迟分解**:Query 延迟和连接空闲时间对比、Query 延迟分解、execute 阶段 TSO 请求和 KV 请求的延迟、TiKV 内部写延迟的分解等。 +- **自上而下的延迟分解**:Query 延迟和连接空闲时间对比、Query 延迟分解、execute 阶段 TSO 请求和 KV 请求的延迟、TiKV 内部写延迟的分解等。 以下为 Performance Overview 面板监控说明: @@ -99,7 +99,7 @@ execute 执行阶段为绿色,其他三个阶段偏红色系,如果非绿色 ### Read Traffic - `TiDB -> Client`:从 TiDB 到客户端的出站流量统计 -- `Rocksdb -> TiKV`:TiKV 在存储层读操作过程中从 RocksDB 获取的数据流量 +- `Rocksdb -> TiKV`:TiKV 在存储层读操作过程中从 RocksDB 读取的数据流量 ### Write Traffic diff --git a/performance-tuning-methods.md b/performance-tuning-methods.md index ab7a6a95e0ea..456873143159 100644 --- a/performance-tuning-methods.md +++ b/performance-tuning-methods.md @@ -211,14 +211,14 @@ StmtPrepare 每秒执行次数远大于 StmtClose,说明应用程序存在 pre #### CPU 和内存使用情况 -在 TiDB、TiKV 和 PD 的 CPU/Memory 面板中,你可以监控它们各自的逻辑 CPU 使用率和内存消耗情况,例如平均 CPU 利用率、最大 CPU 利用率、CPU 利用率差值(最大 CPU 使用率减去最小 CPU 使用率)、CPU 配额以及最大内存使用率。基于这些指标,你可以确定 TiDB、TiKV 和 PD 的整体资源使用情况。 +在 TiDB、TiKV 和 PD 的 CPU/Memory 面板中,你可以监控它们各自的逻辑 CPU 使用率和内存消耗情况,例如平均 CPU 利用率、最大 CPU 利用率、CPU 利用率差值(最大 CPU 使用率减去最小 CPU 使用率)、CPU quota(可以使用的 CPU 核数)以及最大内存使用率。基于这些指标,你可以确定 TiDB、TiKV 和 PD 的整体资源使用情况。 - 根据 `delta` 值,你可以判断 TiDB 或 TiKV 的 CPU 使用是否存在不均衡的情况。对于 TiDB,较高的 `delta` 值通常意味着应用程序的连接在 TiDB 实例之间分布不均衡;对于 TiKV,较高的 `delta` 值通常意味着集群中存在读写热点。 -- 通过 TiDB、TiKV 和 PD 的资源使用概览,你可以快速判断集群是否存在资源瓶颈,以及是否需要对 TiKV、TiDB 或 PD 进行扩容或升级。 +- 通过 TiDB、TiKV 和 PD 的资源使用概览,你可以快速判断集群是否存在资源瓶颈,以及是否需要对 TiKV、TiDB 或 PD 进行扩容或者硬件配置升级。 **示例 1:TiKV 资源使用率高** -在以下 TPC-C 负载中,每个 TiDB 和 TiKV 配置了 16 CPU,PD 配置了 4 CPU。 +在以下 TPC-C 负载中,每个 TiDB 和 TiKV 配置了 16 核 CPU,PD 配置了 4 核 CPU。 ![TPC-C](/media/performance/tpcc_cpu_memory.png) @@ -233,23 +233,23 @@ StmtPrepare 每秒执行次数远大于 StmtClose,说明应用程序存在 pre Read traffic 和 Write traffic 面板可以帮助你深入分析 TiDB 集群内部的流量模式,全面监控从客户端到数据库以及内部组件之间的数据流情况。 - Read traffic (读流量) - - `TiDB -> Client`:从 TiDB 到客户端的出站流量统计 - - `Rocksdb -> TiKV`:TiKV 在存储层读操作期间从 RocksDB 获取的数据流量 + - `TiDB -> Client`:从 TiDB 到客户端的出站流量统计 + - `Rocksdb -> TiKV`:TiKV 在存储层读操作期间从 RocksDB 读取的数据流量 - Write traffic (写流量) - - `Client -> TiDB`:从客户端到 TiDB 的入站流量统计 - - `TiDB -> TiKV: general`:前台事务从 TiDB 写入到 TiKV 的速率 - - `TiDB -> TiKV: internal`:内部事务从 TiDB 写入到 TiKV 的速率 - - `TiKV -> Rocksdb`:从 TiKV 到 RocksDB 的写操作流量 - - `RocksDB Compaction`:RocksDB compaction 操作产生的总读写 I/O 流量。如果 `RocksDB Compaction` 明显高于 `TiKV -> Rocksdb`,且你的平均行大小高于 512 字节,你可以通过以下配置来减少 compaction I/O 流量:启用 Titan,将 min-blob-size 设置为 `"512B"` 或 `"1KB"`,将 blob-file-compression 设置为 `"zstd"`。 - -```toml -[rocksdb.titan] -enabled = true -[rocksdb.defaultcf.titan] -min-blob-size = "1KB" -blob-file-compression = "zstd" -``` + - `Client -> TiDB`:从客户端到 TiDB 的入站流量统计 + - `TiDB -> TiKV: general`:前台事务从 TiDB 写入到 TiKV 的速率 + - `TiDB -> TiKV: internal`:内部事务从 TiDB 写入到 TiKV 的速率 + - `TiKV -> Rocksdb`:从 TiKV 到 RocksDB 的写操作流量 + - `RocksDB Compaction`:RocksDB compaction 操作产生的总读写 I/O 流量。如果 `RocksDB Compaction` 明显高于 `TiKV -> Rocksdb`,且你的平均行大小高于 512 字节,则可以进行以下配置以减少 compaction I/O 流量:启用 Titan,将 min-blob-size 设置为 `"512B"` 或 `"1KB"`,将 blob-file-compression 设置为 `"zstd"`。 + + ```toml + [rocksdb.titan] + enabled = true + [rocksdb.defaultcf.titan] + min-blob-size = "1KB" + blob-file-compression = "zstd" + ``` **示例 1:TPC-C 负载中的读写流量** @@ -258,15 +258,15 @@ blob-file-compression = "zstd" ![TPC-C](/media/performance/tpcc_read_write_traffic.png) - 读流量 - - `TiDB -> Client`:14.2 MB/s - - `Rocksdb -> TiKV`:469 MB/s。注意,在提交事务之前,读操作(`SELECT` 语句)和写操作(`INSERT`、`UPDATE` 和 `DELETE` 语句)都需要从 RocksDB 读取数据到 TiKV。 + - `TiDB -> Client`:14.2 MB/s + - `Rocksdb -> TiKV`:469 MB/s。注意,在提交事务之前,读操作(`SELECT` 语句)和写操作(`INSERT`、`UPDATE` 和 `DELETE` 语句)都需要从 RocksDB 读取数据到 TiKV。 - 写流量 - - `Client -> TiDB`:5.05 MB/s - - `TiDB -> TiKV: general`:13.1 MB/s - - `TiDB -> TiKV: internal`:5.07 KB/s - - `TiKV -> Rocksdb`:109 MB/s - - `RocksDB Compaction`:567 MB/s + - `Client -> TiDB`:5.05 MB/s + - `TiDB -> TiKV: general`:13.1 MB/s + - `TiDB -> TiKV: internal`:5.07 KB/s + - `TiKV -> Rocksdb`:109 MB/s + - `RocksDB Compaction`:567 MB/s ![TPC-C](/media/performance/tpcc_read_write_traffic.png) @@ -276,25 +276,23 @@ blob-file-compression = "zstd" - 启用 Titan 前的写流量 -![Titan 禁用](/media/performance/titan_disable.png) + - `Client -> TiDB`:510 MB/s + - `TiDB -> TiKV: general`:187 MB/s + - `TiDB -> TiKV: internal`:3.2 KB/s + - `TiKV -> Rocksdb`:753 MB/s + - `RocksDB Compaction`:10.6 GB/s - - `Client -> TiDB`:510 MB/s - - `TiDB -> TiKV: general`:187 MB/s - - `TiDB -> TiKV: internal`:3.2 KB/s - - `TiKV -> Rocksdb`:753 MB/s - - `RocksDB Compaction`:10.6 GB/s + ![Titan 禁用](/media/performance/titan_disable.png) - 启用 Titan 后的写流量 -![Titan 启用](/media/performance/titan_enable.png) - - - `Client -> TiDB`:586 MB/s - - `TiDB -> TiKV: general`:295 MB/s - - `TiDB -> TiKV: internal`:3.66 KB/s - - `TiKV -> Rocksdb`:1.21 GB/s - - `RocksDB Compaction`:4.68 MB/s + - `Client -> TiDB`:586 MB/s + - `TiDB -> TiKV: general`:295 MB/s + - `TiDB -> TiKV: internal`:3.66 KB/s + - `TiKV -> Rocksdb`:1.21 GB/s + - `RocksDB Compaction`:4.68 MB/s -![Titan Enable](/media/performance/titan_enable.png) + ![Titan 启用](/media/performance/titan_enable.png) ### Query 延迟分解和关键的延迟指标 From 27f50cdf3989857464f4910e34e8500d304d9659 Mon Sep 17 00:00:00 2001 From: Grace Cai Date: Thu, 23 Jan 2025 14:20:27 +0800 Subject: [PATCH 08/11] Update performance-tuning-methods.md --- performance-tuning-methods.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/performance-tuning-methods.md b/performance-tuning-methods.md index 456873143159..4616a20102c4 100644 --- a/performance-tuning-methods.md +++ b/performance-tuning-methods.md @@ -249,7 +249,7 @@ Read traffic 和 Write traffic 面板可以帮助你深入分析 TiDB 集群内 [rocksdb.defaultcf.titan] min-blob-size = "1KB" blob-file-compression = "zstd" - ``` + ``` **示例 1:TPC-C 负载中的读写流量** From 521f519fba28a99e321f8e775c5ada1bf21a901f Mon Sep 17 00:00:00 2001 From: qiancai Date: Thu, 23 Jan 2025 14:24:58 +0800 Subject: [PATCH 09/11] move images --- media/{ => performance}/titan_disable.png | Bin media/{ => performance}/titan_enable.png | Bin media/{ => performance}/tpcc_cpu_memory.png | Bin media/{ => performance}/tpcc_read_write_traffic.png | Bin 4 files changed, 0 insertions(+), 0 deletions(-) rename media/{ => performance}/titan_disable.png (100%) rename media/{ => performance}/titan_enable.png (100%) rename media/{ => performance}/tpcc_cpu_memory.png (100%) rename media/{ => performance}/tpcc_read_write_traffic.png (100%) diff --git a/media/titan_disable.png b/media/performance/titan_disable.png similarity index 100% rename from media/titan_disable.png rename to media/performance/titan_disable.png diff --git a/media/titan_enable.png b/media/performance/titan_enable.png similarity index 100% rename from media/titan_enable.png rename to media/performance/titan_enable.png diff --git a/media/tpcc_cpu_memory.png b/media/performance/tpcc_cpu_memory.png similarity index 100% rename from media/tpcc_cpu_memory.png rename to media/performance/tpcc_cpu_memory.png diff --git a/media/tpcc_read_write_traffic.png b/media/performance/tpcc_read_write_traffic.png similarity index 100% rename from media/tpcc_read_write_traffic.png rename to media/performance/tpcc_read_write_traffic.png From 5d3252f8294714ff223f73cb170a8cb13c8e3767 Mon Sep 17 00:00:00 2001 From: Grace Cai Date: Thu, 23 Jan 2025 16:01:13 +0800 Subject: [PATCH 10/11] Apply suggestions from code review Co-authored-by: xixirangrang --- dashboard/dashboard-monitoring.md | 8 ++++---- performance-tuning-methods.md | 4 ++-- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/dashboard/dashboard-monitoring.md b/dashboard/dashboard-monitoring.md index 4672adb31e25..a3669040e632 100644 --- a/dashboard/dashboard-monitoring.md +++ b/dashboard/dashboard-monitoring.md @@ -43,7 +43,7 @@ execute 执行阶段为绿色,其他三个阶段偏红色系,如果非绿色 - `execute time`:execute 阶段每秒消耗的数据库时间 - `tso_wait`:execute 阶段每秒同步等待 TSO 的时间 -- `kv request type`:execute 阶段每秒等待每种 KV 请求类型的时间,总的 KV request 等待时间可能超过 execute time,因为 KV request 是并发的。 +- `kv request type`:execute 阶段每秒等待每种 KV 请求类型的时间,总的 KV 请求等待时间可能超过 execute time,因为 KV 请求是并发的。 绿色系标识代表常规的写 KV 请求(例如 Prewrite 和 Commit),蓝色系标识代表常规的读 KV 请求,其他色系标识需要注意的问题。例如,悲观锁加锁请求为红色,TSO 等待为深褐色。如果非蓝色系或者非绿色系占比明显,意味着执行阶段存在异常的瓶颈。例如,当发生严重锁冲突时,红色的悲观锁时间会占比明显;当负载中 TSO 等待的消耗时间过长时,深褐色会占比明显。 @@ -72,7 +72,7 @@ execute 执行阶段为绿色,其他三个阶段偏红色系,如果非绿色 - `total`:所有 TiDB 的连接数 - `active connections`:所有 TiDB 总的活跃连接数 -- 各个 TiDB 的连接数 +- 各个 TiDB 实例的连接数 ### TiDB CPU/Memory @@ -155,8 +155,8 @@ Connection Idle Duration 指空闲连接的持续时间。 ### Storage Async Write Duration、Store Duration 和 Apply Duration - `Storage Async Write Duration`:异步写所花费的时间 -- `Store Duration`:异步写 Store 步骤所花费的时间 -- `Apply Duration`:异步写 Apply 步骤所花费的时间 +- `Store Duration`:异步写入过程中,在存储循环 (store loop) 中所花费的时间 +- `Apply Duration`:异步写入过程中,在应用循环 (apply loop) 中所花费的时间 这三个时间指标都包含所有 TiKV 实例的平均值和 P99 值 diff --git a/performance-tuning-methods.md b/performance-tuning-methods.md index 4616a20102c4..3b66e6581754 100644 --- a/performance-tuning-methods.md +++ b/performance-tuning-methods.md @@ -211,7 +211,7 @@ StmtPrepare 每秒执行次数远大于 StmtClose,说明应用程序存在 pre #### CPU 和内存使用情况 -在 TiDB、TiKV 和 PD 的 CPU/Memory 面板中,你可以监控它们各自的逻辑 CPU 使用率和内存消耗情况,例如平均 CPU 利用率、最大 CPU 利用率、CPU 利用率差值(最大 CPU 使用率减去最小 CPU 使用率)、CPU quota(可以使用的 CPU 核数)以及最大内存使用率。基于这些指标,你可以确定 TiDB、TiKV 和 PD 的整体资源使用情况。 +在 TiDB、TiKV 和 PD 的 CPU/Memory 面板中,你可以监控它们各自的逻辑 CPU 使用率和内存消耗情况,例如平均 CPU 利用率、最大 CPU 利用率、CPU 利用率差值(最大 CPU 使用率减去最小 CPU 使用率)、CPU Quota(可以使用的 CPU 核数)以及最大内存使用率。基于这些指标,你可以确定 TiDB、TiKV 和 PD 的整体资源使用情况。 - 根据 `delta` 值,你可以判断 TiDB 或 TiKV 的 CPU 使用是否存在不均衡的情况。对于 TiDB,较高的 `delta` 值通常意味着应用程序的连接在 TiDB 实例之间分布不均衡;对于 TiKV,较高的 `delta` 值通常意味着集群中存在读写热点。 - 通过 TiDB、TiKV 和 PD 的资源使用概览,你可以快速判断集群是否存在资源瓶颈,以及是否需要对 TiKV、TiDB 或 PD 进行扩容或者硬件配置升级。 @@ -241,7 +241,7 @@ Read traffic 和 Write traffic 面板可以帮助你深入分析 TiDB 集群内 - `TiDB -> TiKV: general`:前台事务从 TiDB 写入到 TiKV 的速率 - `TiDB -> TiKV: internal`:内部事务从 TiDB 写入到 TiKV 的速率 - `TiKV -> Rocksdb`:从 TiKV 到 RocksDB 的写操作流量 - - `RocksDB Compaction`:RocksDB compaction 操作产生的总读写 I/O 流量。如果 `RocksDB Compaction` 明显高于 `TiKV -> Rocksdb`,且你的平均行大小高于 512 字节,则可以进行以下配置以减少 compaction I/O 流量:启用 Titan,将 min-blob-size 设置为 `"512B"` 或 `"1KB"`,将 blob-file-compression 设置为 `"zstd"`。 + - `RocksDB Compaction`:RocksDB compaction 操作产生的总读写 I/O 流量。如果 `RocksDB Compaction` 明显高于 `TiKV -> Rocksdb`,且你的平均行大小高于 512 字节,则可以进行以下配置以减少 compaction I/O 流量:启用 Titan,将 `min-blob-size` 设置为 `"512B"` 或 `"1KB"`,将 `blob-file-compression` 设置为 `"zstd"`。 ```toml [rocksdb.titan] From e2e44229b206fdba79bfa2a3470dc6b50e57c07e Mon Sep 17 00:00:00 2001 From: Grace Cai Date: Thu, 23 Jan 2025 16:01:32 +0800 Subject: [PATCH 11/11] Update performance-tuning-methods.md Co-authored-by: xixirangrang --- performance-tuning-methods.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/performance-tuning-methods.md b/performance-tuning-methods.md index 3b66e6581754..6511790887f0 100644 --- a/performance-tuning-methods.md +++ b/performance-tuning-methods.md @@ -272,7 +272,7 @@ Read traffic 和 Write traffic 面板可以帮助你深入分析 TiDB 集群内 **示例 2:启用 Titan 前后的写流量** -以下示例展示了启用 Titan 前后的性能变化。对于 6 KB 数据量的插入负载,Titan 显著降低了写流量和 compaction I/O,提高了 TiKV 的整体性能和资源利用率。 +以下示例展示了启用 Titan 前后的性能变化。对于 6 KiB 数据量的插入负载,Titan 显著降低了写流量和 compaction I/O,提高了 TiKV 的整体性能和资源利用率。 - 启用 Titan 前的写流量