From 859e9abe8e370bbba1d5bbf53a5d8ea7e5955048 Mon Sep 17 00:00:00 2001 From: Ti Chi Robot Date: Fri, 20 Oct 2023 15:20:00 +0800 Subject: [PATCH] tiflash: add mpp glossary and diagram (#15076) (#15279) --- glossary.md | 6 +++ media/tiflash/tiflash-mpp.png | Bin 0 -> 318392 bytes schedule-replicas-by-topology-labels.md | 62 ++++++++++++------------ tiflash/use-tiflash-mpp-mode.md | 6 ++- 4 files changed, 43 insertions(+), 31 deletions(-) create mode 100644 media/tiflash/tiflash-mpp.png diff --git a/glossary.md b/glossary.md index f98605bee569..c030bad43515 100644 --- a/glossary.md +++ b/glossary.md @@ -75,6 +75,12 @@ Coalesce Partition 是一种减少 Hash 分区表或 Key 分区表中分区数 它们分别对应 [Peer](#regionpeerraft-group) 的三种角色。其中 Leader 负责响应客户端的读写请求;Follower 被动地从 Leader 同步数据,当 Leader 失效时会进行选举产生新的 Leader;Learner 是一种特殊的角色,它只参与同步 raft log 而不参与投票,在目前的实现中只短暂存在于添加副本的中间步骤。 +## M + +### MPP + +从 v5.0 起,TiDB 通过 TiFlash 节点引入了 Massively Parallel Processing (MPP) 架构。这使得大型表连接类查询可以由不同 TiFlash 节点共同分担完成。当 MPP 模式开启后,TiDB 将会根据代价决定是否应该交由 MPP 框架进行计算。MPP 模式下,表连接将通过对 JOIN Key 进行数据计算时重分布(Exchange 操作)的方式把计算压力分摊到各个 TiFlash 执行节点,从而达到加速计算的目的。更多信息请参见 [使用 MPP 模式](/tiflash/use-tiflash-mpp-mode.md)。 + ## O ### Old value diff --git a/media/tiflash/tiflash-mpp.png b/media/tiflash/tiflash-mpp.png new file mode 100644 index 0000000000000000000000000000000000000000..2342f1ffe89cc2ddfb85384109dfa3ca7b629213 GIT binary patch literal 318392 zcmYhiWmKC>_cxs2E`=5^P>K|a6xZTV+}+*XH8>QCTX87v?h>@P7k77eNqBiq&$<8a zm#`Kq*UV(Dy=V6R$#;2KadZ?y6aWB#F7Zu75dc6s1pwfJkYHZ_qiQEg`uYdxq$n-~ zs2C$Y0077U5+Z`i?&-%XZa;BVW)audnpI}_Qv87*kx{}w;?RVDd<%rlhA|Zt8Obu3 zJ3jms!LWNwI7>Vm<_E_@Mn?M~oD8Yx+gML$Q08e#%idFN$=3D9xS*@AyiC{1D=jW( zCm#FU=}zBM$b+zikX}DpkvDkrORvX7{r(23k_HNKFQPd`LPCK0Oi6QZ z=~+{zH4D9!`u}@E==jsNUd2BT|KEophiF_PD#tc3rW zF$^4HY=ZoE$*x-U=!`Sh_lI$cv=(L@OULGjOHZdo4GlJMt~*VG#Q%IP%qQ;u_dpyX z#lOGyiF$r`}oK9lzMxRT4JjrA;EQ$sb@YB)UEX)9Kn* zrds_oZ*_ER+2_A22*NTP&jlqkDt^6s3{`GmwyH8L<(ts5f4izjm=_;idQcyCupLypPj?J~!Dm=6;9>DSn>;%6 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