From 02916dd9d6efab76ffdf1137d7a667dd80859bb8 Mon Sep 17 00:00:00 2001 From: Xiaojian Zheng Date: Wed, 24 Apr 2024 00:15:12 +0800 Subject: [PATCH] add PACELC-theory --- docs/posts/PACELC-theory.md | 29 +++++++++++++++++++++++++++++ docs/posts/images/redis-doc1.png | Bin 0 -> 79567 bytes docs/posts/images/redis-doc2.png | Bin 0 -> 80688 bytes 3 files changed, 29 insertions(+) create mode 100644 docs/posts/PACELC-theory.md create mode 100644 docs/posts/images/redis-doc1.png create mode 100644 docs/posts/images/redis-doc2.png diff --git a/docs/posts/PACELC-theory.md b/docs/posts/PACELC-theory.md new file mode 100644 index 0000000..c4c26b6 --- /dev/null +++ b/docs/posts/PACELC-theory.md @@ -0,0 +1,29 @@ +--- +category: + - 分布式 +tag: + - PACELC + - CAP +date: 2024-04-24 +star: true +--- + +# PACELC理论 + +如果有网络分区partition (P),系统就必须在可用性availability和一致性consistency (A and C)之间取得平衡; 否则else (E) 当系统运行在无分区情况下,系统需要在 延迟latency (L) 和 consistency (C)之间取得平衡。 + +PACELC定理是CAP定理的扩展。 + +## MongoDB + +MongoDB(默认配置)下是PA/EC系统,mongo读写都在主节点上,它只需在主节点上写入成功就返回(不像raft需要多数复制成功),当主节点和备节点分区时,可能会丢失数据,所以说PA,在无分区的情况下,由于读写都在主节点,肯定能读到最新写入的数据,所以是EC。另外Mongo可以配置为写入大多数节点读主节点,这样就是PC/EC系统了。 + +## Redis + +在分析Redis Cluster的一致性模型之前,我们先来看看Redis Cluster数据分片策略,它并没有使用常见的一致性哈希算法,而是使用哈希槽(Hash Slot),总共有2^14个槽,把这些槽分配到主节点,使用CRC-16(key) % 2^14确定该key属于哪个节点。新增或删除节点,需要手动分配槽(一致性哈希算法按照顺时针重新分布节点,不需要手动调整)。 + +在默认配置下,redis cluster读写都在主节点上,使用gossip协议复制数据到副本,实现的是最终一致性。存在分区的情况下,主节点宕机,副本未复制到最新的数据,出现掉数据的情况。所以是PA。无分区情况下,读写都在主节点,一定能读到最新写入的数据,所以是EC。其次,redis cluster可以配置读写分离,在主节点写,在从节点读,这样就是EL。 +![redis-doc1.png](images/redis-doc1.png) + +其次,redis cluster 提供了WAIT命令同步复制副本数据,但依然不能实现强一致性。大概原因是,redis cluster同步复制没有二阶段提交协议(2PC),也就是说,它是尽最大努力复制,如果有的副本节点复制失败,也不会撤销已经复制成功的节点。假设出现分区,主节点出现在少数区,集群检测到分区需要一定的时间窗口(这个可以配置多少),在这个时间窗口内主节点仍可接受客户端的写入,在多数区的某一个节点成功当选主节点,这样在这个时间窗口内写入原主节点的数据就丢失了。 +![redis-doc2.png](images/redis-doc2.png) \ No newline at end of file diff --git a/docs/posts/images/redis-doc1.png b/docs/posts/images/redis-doc1.png new file mode 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