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zJ2aZ7aY{tLDT9`qG|hH2E!3B^S1_yO&-FuRK%Sd`s4a;>uh5EX+peIYd(0r zbn6S{;6XUqCY>9$>SOE$zox;r9J7Wbcb4@4gAoI=>l8b zQPxB;W*m;dVp%SyWIXF|n;PUp_5UUToxBYrP hzkL(@U;a2dKwGmqyUyar`(T;^4j(`TF!#lL^G|1q8@T`g literal 0 HcmV?d00001 From f8bc74f116e84c5d0905a5055d6b46f4fb665df2 Mon Sep 17 00:00:00 2001 From: "DamonGuo@PingCAP" <50732087+Damon-PingCap@users.noreply.github.com> Date: Sat, 23 May 2020 12:19:43 +0800 Subject: [PATCH 2/8] troubleshoot-hot-spot-issues v1 --- troubleshoot-hot-spot-issues.md | 143 ++++++++++++++++++++++++++++++++ 1 file changed, 143 insertions(+) diff --git a/troubleshoot-hot-spot-issues.md b/troubleshoot-hot-spot-issues.md index e69de29bb2d1..a127938e59c1 100644 --- a/troubleshoot-hot-spot-issues.md +++ b/troubleshoot-hot-spot-issues.md @@ -0,0 +1,143 @@ +# TiDB 热点问题处理 + +## 常见热点场景 + +### TiDB 编码规则 + +TiDB 对每个表分配一个 TableID,每一个索引都会分配一个 IndexID,每一行分配一个 RowID(如果表有整数型的 Primary Key,那么会用 Primary Key 的值当做 RowID),其中 TableID 在整个集群内唯一,IndexID/RowID 在表内唯一,这些 ID 都是 int64 类型。 + +每行数据按照如下规则进行编码成 Key-Value pair: + +```text +Key: tablePrefix{tableID}_recordPrefixSep{rowID} +Value: [col1, col2, col3, col4] +``` + +其中 Key 的 tablePrefix/recordPrefixSep 都是特定的字符串常量,用于在 KV 空间内区分其他数据。 + +对于 Index 数据,会按照如下规则编码成 Key-Value pair: + +```text +Key: tablePrefix{tableID}_indexPrefixSep{indexID}_indexedColumnsValue +Value: rowID +``` + +Index 数据还需要考虑 Unique Index 和非 Unique Index 两种情况,对于 Unique Index,可以按照上述编码规则。但是对于非 Unique Index,通过这种编码并不能构造出唯一的 Key,因为同一个 Index 的 tablePrefix{tableID}_indexPrefixSep{indexID} 都一样,可能有多行数据的 ColumnsValue 是一样的,所以对于非 Unique Index 的编码做了一点调整: + +```text +Key: tablePrefix{tableID}_indexPrefixSep{indexID}_indexedColumnsValue_rowID +Value: null +``` + +### 表热点 + +由 TiDB 编码规则可知,同一个表的数据会在以表 id 开头为前缀的一个 range 中,数据的顺序按照 RowID 的值顺序排列。在表 insert 的过程中如果 RowID 的值是递增的,则插入的行只能在末端追加。当 region 达到一定的大小之后会进行分裂,分裂之后还是只能在 range 范围的末端追加,此时永远只能在一个 region 上进行 insert 操作,形成热点。 + +常见的 increment 类型自增主键就是顺序递增的,在主键为整数型时,会用主键值当做 RowID ,此时 RowID 为顺序递增,在大量 insert 时形成表的写入热点。 + +同时,TiDB 中 RowID 默认也按照自增的方式顺序递增,主键不为整数类型时,同样会遇到写入热点的问题。 + +### 索引热点 + +索引热点与表热点类似,常见的热点场景出现在时间顺序递增的字段,或者插入大量重复值的场景。 + +## 使用 TiDB Dashboard 定位热点表 + +TiDB Dashboard 中的「热点可视化」功能可帮助用户缩小热点排查范围到表级别。以下是一个「热点可视化」功能展示的热力图样例,该图横坐标是时间,纵坐标排列了各个表和索引,颜色越亮代表其流量越大。可在工具栏中切换显示读或写流量。 + +![Dashboard 示例1](/media/troubleshoot-hot-spot-issues-1.png) + +当图中写入流量图出现以下明亮斜线(斜向上或斜向下)时,由于写入只出现在末端,随着表 region 数量变多,呈现出阶梯状。此时说明该表构成了写入热点: + +![Dashboard 示例2](/media/troubleshoot-hot-spot-issues-2.png) + +对于读热点,在热力图中一般表现为一条明亮的横线,通常是有大量访问的小表,如下图所示: + +![Dashboard 示例3](/media/troubleshoot-hot-spot-issues-3.png) + +将鼠标移到亮色块上,即可看到是什么表或索引具有大流量,如下图所示: + +![Dashboard 示例4](/media/troubleshoot-hot-spot-issues-4.png) + +## 使用 SHARD_ROW_ID_BITS 处理热点表 + +对于主键非整数或没有主键的表或者是联合主键,TiDB 会使用一个隐式的自增 RowID,大量 INSERT 时会把数据集中写入单个 Region,造成写入热点。 + +通过设置 SHARD_ROW_ID_BITS,可以把 RowID 打散写入多个不同的 Region,缓解写入热点问题。但是设置的过大会造成 RPC 请求数放大,增加 CPU 和网络开销。 + +SHARD_ROW_ID_BITS = 4 表示 16 个分片\ +SHARD_ROW_ID_BITS = 6 表示 64 个分片\ +SHARD_ROW_ID_BITS = 0 表示默认值 1 个分片 + +语句示例: + +```sql +CREATE TABLE:CREATE TABLE t (c int) SHARD_ROW_ID_BITS = 4; +ALTER TABLE:ALTER TABLE t SHARD_ROW_ID_BITS = 4; +``` + +> SHARD_ROW_ID_BITS 的值可以动态修改,每次修改之后,只对新写入的数据生效。 +> +> TiDB alter-primary-key 参数设置为 false 时,会使用表的整数型主键作为 RowID,因为 SHARD_ROW_ID_BITS 会改变 RowID 生成规则,所以此时无法使用 SHARD_ROW_ID_BITS 选项,在 alter-primary-key 参数设置为 true 时,TiDB 在建表时不再使用整数型主键作为 RowID,此时带有整数型主键的表也可以使用 SHARD_ROW_ID_BITS 特性。 + +以下是两张无主键情况下使用 SHARD_ROW_ID_BITS 打散热点后的流量图,第一张展示了打散前的情况,第二张展示了打散后的情况。 + +![Dashboard 示例5](/media/troubleshoot-hot-spot-issues-5.png) + +![Dashboard 示例6](/media/troubleshoot-hot-spot-issues-6.png) + +由流量图可见,设置 SHARD_ROW_ID_BITS 后,流量热点由之前的只在一个 Region 上变得很分散。 + +## 使用 AUTO_RANDOM 处理自增主键热点表 + +使用 AUTO_RANDOM 处理自增主键热点表,适用于代替自增主键,解决自增主键带来的写入热点。 + +> 该功能目前还是实验性功能,不推荐生产环境使用。可使用以下配置启用: +> +>[experimental]\ +>allow-auto-random = true + +使用该功能后,将由 TiDB 生成随机分布且空间耗尽前不重复的主键,达到离散写入、打散写入热点的目的。 + +>注意,TiDB 生成的主键不再是自增的主键,可使用 LAST_INSERT_ID() 获取上次分配的主键值。 + +将建表语句中的 AUTO_INCREMENT 改为 AUTO_RANDOM 即可使用该功能。\ +示例如下: + +```sql +> CREATE TABLE t (a BIGINT PRIMARY KEY AUTO_RANDOM, b varchar(255)); +> INSERT INTO t (b) VALUES ("foo"); +> SELECT * FROM t; ++------------+---+ +| a | b | ++------------+---+ +| 1073741825 | b | ++------------+---+ + +> SELECT LAST_INSERT_ID(); ++------------------+ +| LAST_INSERT_ID() | ++------------------+ +| 1073741825 | ++------------------+ +``` + +以下是将 AUTO_INCREMENT 表改为 AUTO_RANDOM 打散热点后的流量图,第一张是 AUTO_INCREMENT,第二张是 AUTO_RANDOM。 + +![Dashboard 示例7](/media/troubleshoot-hot-spot-issues-7.png) + +![Dashboard 示例8](/media/troubleshoot-hot-spot-issues-8.png) + +由流量图可见,使用 AUTO_RANDOM 代替 AUTO_INCREMENT 可以很好地打散热点情况。 + +更详细的说明可以阅读 [AUTO_RANDOM](https://pingcap.com/docs-cn/stable/reference/sql/attributes/auto-random/) 文档。 + +## 下推计算结果缓存 + +TiDB 从 4.0 起支持下推计算结果缓存(即 Coprocessor Cache 功能)。开启该功能后,将在 TiDB 实例侧缓存下推给 TiKV 计算的结果,对于小表读热点能起到比较好的效果。 + +更详细的说明可以阅读[下推计算结果缓存](https://pingcap.com/docs-cn/stable/coprocessor-cache/#%E9%85%8D%E7%BD%AE)文档 + +**其他相关资料**\ +[TiDB 高并发写入场景最佳实践](https://pingcap.com/docs-cn/dev/reference/best-practices/high-concurrency/)\ +[Split Region 使用文档](https://pingcap.com/docs-cn/stable/reference/sql/statements/split-region/#split-region-%E4%BD%BF%E7%94%A8%E6%96%87%E6%A1%A3) From e7fbffdf0f0eb3af77ce676f0678e5c01a6b755f Mon Sep 17 00:00:00 2001 From: "DamonGuo@PingCAP" <50732087+Damon-PingCap@users.noreply.github.com> Date: Sat, 23 May 2020 19:13:38 +0800 Subject: [PATCH 3/8] Update troubleshoot-hot-spot-issues.md Co-authored-by: kissmydb --- troubleshoot-hot-spot-issues.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/troubleshoot-hot-spot-issues.md b/troubleshoot-hot-spot-issues.md index a127938e59c1..1d81b517d55e 100644 --- a/troubleshoot-hot-spot-issues.md +++ b/troubleshoot-hot-spot-issues.md @@ -132,7 +132,8 @@ ALTER TABLE:ALTER TABLE t SHARD_ROW_ID_BITS = 4; 更详细的说明可以阅读 [AUTO_RANDOM](https://pingcap.com/docs-cn/stable/reference/sql/attributes/auto-random/) 文档。 -## 下推计算结果缓存 +## 小表热点的优化 + TiDB 从 4.0 起支持下推计算结果缓存(即 Coprocessor Cache 功能)。开启该功能后,将在 TiDB 实例侧缓存下推给 TiKV 计算的结果,对于小表读热点能起到比较好的效果。 From 4edb65a726d78a48fbf4821a176d4400b8825e69 Mon Sep 17 00:00:00 2001 From: "DamonGuo@PingCAP" <50732087+Damon-PingCap@users.noreply.github.com> Date: Sat, 23 May 2020 19:33:12 +0800 Subject: [PATCH 4/8] Update troubleshoot-hot-spot-issues.md --- troubleshoot-hot-spot-issues.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/troubleshoot-hot-spot-issues.md b/troubleshoot-hot-spot-issues.md index 1d81b517d55e..8ede7a7ee612 100644 --- a/troubleshoot-hot-spot-issues.md +++ b/troubleshoot-hot-spot-issues.md @@ -1,3 +1,8 @@ +--- +title: TiDB 热点问题处理 +category: reference +--- + # TiDB 热点问题处理 ## 常见热点场景 From e79fe09ee06c449df5edd4e12cabc16642b16edd Mon Sep 17 00:00:00 2001 From: "DamonGuo@PingCAP" <50732087+Damon-PingCap@users.noreply.github.com> Date: Sat, 23 May 2020 19:37:23 +0800 Subject: [PATCH 5/8] Update troubleshoot-hot-spot-issues.md --- troubleshoot-hot-spot-issues.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/troubleshoot-hot-spot-issues.md b/troubleshoot-hot-spot-issues.md index 8ede7a7ee612..e7dd161cf86a 100644 --- a/troubleshoot-hot-spot-issues.md +++ b/troubleshoot-hot-spot-issues.md @@ -64,6 +64,8 @@ TiDB Dashboard 中的「热点可视化」功能可帮助用户缩小热点排 ![Dashboard 示例4](/media/troubleshoot-hot-spot-issues-4.png) +> [4.0 之前版本热点定位可以参考此文档](https://book.tidb.io/session4/chapter7/hotspot-resolved.html) + ## 使用 SHARD_ROW_ID_BITS 处理热点表 对于主键非整数或没有主键的表或者是联合主键,TiDB 会使用一个隐式的自增 RowID,大量 INSERT 时会把数据集中写入单个 Region,造成写入热点。 From 1cc7b907faec6f6ce77aa3652e39d261b89fc159 Mon Sep 17 00:00:00 2001 From: "DamonGuo@PingCAP" <50732087+Damon-PingCap@users.noreply.github.com> Date: Sat, 23 May 2020 19:51:59 +0800 Subject: [PATCH 6/8] Update troubleshoot-hot-spot-issues.md --- troubleshoot-hot-spot-issues.md | 1 - 1 file changed, 1 deletion(-) diff --git a/troubleshoot-hot-spot-issues.md b/troubleshoot-hot-spot-issues.md index e7dd161cf86a..d5d2df528a24 100644 --- a/troubleshoot-hot-spot-issues.md +++ b/troubleshoot-hot-spot-issues.md @@ -141,7 +141,6 @@ ALTER TABLE:ALTER TABLE t SHARD_ROW_ID_BITS = 4; ## 小表热点的优化 - TiDB 从 4.0 起支持下推计算结果缓存(即 Coprocessor Cache 功能)。开启该功能后,将在 TiDB 实例侧缓存下推给 TiKV 计算的结果,对于小表读热点能起到比较好的效果。 更详细的说明可以阅读[下推计算结果缓存](https://pingcap.com/docs-cn/stable/coprocessor-cache/#%E9%85%8D%E7%BD%AE)文档 From 263201dfe39e3a5a442aeacb5d4d9eb27b9b4fb4 Mon Sep 17 00:00:00 2001 From: kissmydb Date: Tue, 26 May 2020 12:00:44 +0800 Subject: [PATCH 7/8] Update troubleshoot-hot-spot-issues.md --- troubleshoot-hot-spot-issues.md | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/troubleshoot-hot-spot-issues.md b/troubleshoot-hot-spot-issues.md index d5d2df528a24..5c2ab559380b 100644 --- a/troubleshoot-hot-spot-issues.md +++ b/troubleshoot-hot-spot-issues.md @@ -5,9 +5,15 @@ category: reference # TiDB 热点问题处理 +本文适用于 TiDB 4.0 版本,介绍了如何定位和解决读写热点问题。 + +TiDB 作为分布式数据库,自身拥有一些负载均衡机制,尽可能将业务负载均匀地分布到不同计算或存储节点上,更好地利用上整体系统资源。然而,机制不是万能的,在一些场景下仍会有部分业务负载不能被很好地分散,影响性能,形成单点的过高负载,也称为热点。 + +TiDB 提供了完整的方案用于排查、解决或规避这类热点。通过均衡负载热点,可以提升整体性能,包括提高 QPS 和降低延迟等。 + ## 常见热点场景 -### TiDB 编码规则 +### TiDB 编码规则介绍 TiDB 对每个表分配一个 TableID,每一个索引都会分配一个 IndexID,每一行分配一个 RowID(如果表有整数型的 Primary Key,那么会用 Primary Key 的值当做 RowID),其中 TableID 在整个集群内唯一,IndexID/RowID 在表内唯一,这些 ID 都是 int64 类型。 @@ -46,6 +52,14 @@ Value: null 索引热点与表热点类似,常见的热点场景出现在时间顺序递增的字段,或者插入大量重复值的场景。 +## 确定存在热点问题 + +性能问题不一定是热点造成的,也有可能有多个因素共同影响,在排查前需要先确认是否与热点相关。 + +- 判断写热点依据:打开监控面板 TiKV-Trouble-Shooting 中 Hot Write 面板(如下图所示),观察 Raftstore CPU 监控是否存在个别 TiKV 节点的指标明显高于其他节点的现象。 + +- 判断读热点依据:打开监控面板 TIKV-Details 中 Thread_CPU,查看 coprocessor cpu 有没有明显的某个 tikv 特别高。 + ## 使用 TiDB Dashboard 定位热点表 TiDB Dashboard 中的「热点可视化」功能可帮助用户缩小热点排查范围到表级别。以下是一个「热点可视化」功能展示的热力图样例,该图横坐标是时间,纵坐标排列了各个表和索引,颜色越亮代表其流量越大。可在工具栏中切换显示读或写流量。 From 986f336a062591d00ae057bc5592d3a1a909f701 Mon Sep 17 00:00:00 2001 From: pepezzzz <35323945+pepezzzz@users.noreply.github.com> Date: Tue, 26 May 2020 12:15:02 +0800 Subject: [PATCH 8/8] a little fix --- troubleshoot-hot-spot-issues.md | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/troubleshoot-hot-spot-issues.md b/troubleshoot-hot-spot-issues.md index 5c2ab559380b..5c0b80106303 100644 --- a/troubleshoot-hot-spot-issues.md +++ b/troubleshoot-hot-spot-issues.md @@ -5,17 +5,17 @@ category: reference # TiDB 热点问题处理 -本文适用于 TiDB 4.0 版本,介绍了如何定位和解决读写热点问题。 +本文适用于 TiDB 4.0 版本,介绍如何定位和解决读写热点问题。 -TiDB 作为分布式数据库,自身拥有一些负载均衡机制,尽可能将业务负载均匀地分布到不同计算或存储节点上,更好地利用上整体系统资源。然而,机制不是万能的,在一些场景下仍会有部分业务负载不能被很好地分散,影响性能,形成单点的过高负载,也称为热点。 +TiDB 作为分布式数据库,内建负载均衡机制,尽可能将业务负载均匀地分布到不同计算或存储节点上,更好地利用上整体系统资源。然而,机制不是万能的,在一些场景下仍会有部分业务负载不能被很好地分散,影响性能,形成单点的过高负载,也称为热点。 TiDB 提供了完整的方案用于排查、解决或规避这类热点。通过均衡负载热点,可以提升整体性能,包括提高 QPS 和降低延迟等。 ## 常见热点场景 -### TiDB 编码规则介绍 +### TiDB 编码规则回顾 -TiDB 对每个表分配一个 TableID,每一个索引都会分配一个 IndexID,每一行分配一个 RowID(如果表有整数型的 Primary Key,那么会用 Primary Key 的值当做 RowID),其中 TableID 在整个集群内唯一,IndexID/RowID 在表内唯一,这些 ID 都是 int64 类型。 +TiDB 对每个表分配一个 TableID,每一个索引都会分配一个 IndexID,每一行分配一个 RowID(默认情况下,如果表使用整数型的 Primary Key,那么会用 Primary Key 的值当做 RowID)。其中 TableID 在整个集群内唯一,IndexID/RowID 在表内唯一,这些 ID 都是 int64 类型。 每行数据按照如下规则进行编码成 Key-Value pair: @@ -42,19 +42,19 @@ Value: null ### 表热点 -由 TiDB 编码规则可知,同一个表的数据会在以表 id 开头为前缀的一个 range 中,数据的顺序按照 RowID 的值顺序排列。在表 insert 的过程中如果 RowID 的值是递增的,则插入的行只能在末端追加。当 region 达到一定的大小之后会进行分裂,分裂之后还是只能在 range 范围的末端追加,此时永远只能在一个 region 上进行 insert 操作,形成热点。 +从 TiDB 编码规则可知,同一个表的数据会在以表 id 开头为前缀的一个 range 中,数据的顺序按照 RowID 的值顺序排列。在表 insert 的过程中如果 RowID 的值是递增的,则插入的行只能在末端追加。当 region 达到一定的大小之后会进行分裂,分裂之后还是只能在 range 范围的末端追加,永远只能在一个 region 上进行 insert 操作,形成热点。 -常见的 increment 类型自增主键就是顺序递增的,在主键为整数型时,会用主键值当做 RowID ,此时 RowID 为顺序递增,在大量 insert 时形成表的写入热点。 +常见的 increment 类型自增主键就是顺序递增的,默认情况下,在主键为整数型时,会用主键值当做 RowID ,此时 RowID 为顺序递增,在大量 insert 时形成表的写入热点。 同时,TiDB 中 RowID 默认也按照自增的方式顺序递增,主键不为整数类型时,同样会遇到写入热点的问题。 ### 索引热点 -索引热点与表热点类似,常见的热点场景出现在时间顺序递增的字段,或者插入大量重复值的场景。 +索引热点与表热点类似,常见的热点场景出现在时间顺序单调递增的字段,或者插入大量重复值的场景。 ## 确定存在热点问题 -性能问题不一定是热点造成的,也有可能有多个因素共同影响,在排查前需要先确认是否与热点相关。 +性能问题不一定是热点造成的,也可能存在多个因素共同影响,在排查前需要先确认是否与热点相关。 - 判断写热点依据:打开监控面板 TiKV-Trouble-Shooting 中 Hot Write 面板(如下图所示),观察 Raftstore CPU 监控是否存在个别 TiKV 节点的指标明显高于其他节点的现象。 @@ -99,7 +99,7 @@ ALTER TABLE:ALTER TABLE t SHARD_ROW_ID_BITS = 4; > SHARD_ROW_ID_BITS 的值可以动态修改,每次修改之后,只对新写入的数据生效。 > -> TiDB alter-primary-key 参数设置为 false 时,会使用表的整数型主键作为 RowID,因为 SHARD_ROW_ID_BITS 会改变 RowID 生成规则,所以此时无法使用 SHARD_ROW_ID_BITS 选项,在 alter-primary-key 参数设置为 true 时,TiDB 在建表时不再使用整数型主键作为 RowID,此时带有整数型主键的表也可以使用 SHARD_ROW_ID_BITS 特性。 +> TiDB alter-primary-key 参数设置为 false 时,会使用表的整数型主键作为 RowID,因为 SHARD_ROW_ID_BITS 会改变 RowID 生成规则,所以此时无法使用 SHARD_ROW_ID_BITS 选项。在 alter-primary-key 参数设置为 true 时,TiDB 在建表时不再使用整数型主键作为 RowID,此时带有整数型主键的表也可以使用 SHARD_ROW_ID_BITS 特性。 以下是两张无主键情况下使用 SHARD_ROW_ID_BITS 打散热点后的流量图,第一张展示了打散前的情况,第二张展示了打散后的情况。 @@ -107,7 +107,7 @@ ALTER TABLE:ALTER TABLE t SHARD_ROW_ID_BITS = 4; ![Dashboard 示例6](/media/troubleshoot-hot-spot-issues-6.png) -由流量图可见,设置 SHARD_ROW_ID_BITS 后,流量热点由之前的只在一个 Region 上变得很分散。 +从流量图可见,设置 SHARD_ROW_ID_BITS 后,流量热点由之前的只在一个 Region 上变得很分散。 ## 使用 AUTO_RANDOM 处理自增主键热点表 @@ -122,7 +122,7 @@ ALTER TABLE:ALTER TABLE t SHARD_ROW_ID_BITS = 4; >注意,TiDB 生成的主键不再是自增的主键,可使用 LAST_INSERT_ID() 获取上次分配的主键值。 -将建表语句中的 AUTO_INCREMENT 改为 AUTO_RANDOM 即可使用该功能。\ +将建表语句中的 AUTO_INCREMENT 改为 AUTO_RANDOM 即可使用该功能,适用于主键只需要保证唯一,不包含业务意义的场景。\ 示例如下: ```sql @@ -149,7 +149,7 @@ ALTER TABLE:ALTER TABLE t SHARD_ROW_ID_BITS = 4; ![Dashboard 示例8](/media/troubleshoot-hot-spot-issues-8.png) -由流量图可见,使用 AUTO_RANDOM 代替 AUTO_INCREMENT 可以很好地打散热点情况。 +由流量图可见,使用 AUTO_RANDOM 代替 AUTO_INCREMENT 能很好地打散热点。 更详细的说明可以阅读 [AUTO_RANDOM](https://pingcap.com/docs-cn/stable/reference/sql/attributes/auto-random/) 文档。