From 443e0d043aa7b8b1ac8534f68b5b8cfc37e40b60 Mon Sep 17 00:00:00 2001
From: Zhang Jian <zjsariel@gmail.com>
Date: Wed, 1 Jul 2020 17:38:24 +0800
Subject: [PATCH 1/4] add tikv overview

---
 TOC.md              |   2 ++
 media/tikv-arch.png | Bin 0 -> 43653 bytes
 tikv-overview.md    |  37 +++++++++++++++++++++++++++++++++++++
 3 files changed, 39 insertions(+)
 create mode 100644 media/tikv-arch.png
 create mode 100644 tikv-overview.md

diff --git a/TOC.md b/TOC.md
index d06064b0dbab1..879dfad943355 100644
--- a/TOC.md
+++ b/TOC.md
@@ -403,6 +403,8 @@
     + [MySQL System Variables](/system-variables.md)
     + [TiDB Specific System Variables](/tidb-specific-system-variables.md)
   + Storage Engines
+    + TiKV
+      + [TiKV Overview](/tikv-overview.md)
     + TiFlash
       + [Overview](/tiflash/tiflash-overview.md)
       + [Use TiFlash](/tiflash/use-tiflash.md)
diff --git a/media/tikv-arch.png b/media/tikv-arch.png
new file mode 100644
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diff --git a/tikv-overview.md b/tikv-overview.md
new file mode 100644
index 0000000000000..7bd3b7b93c1c1
--- /dev/null
+++ b/tikv-overview.md
@@ -0,0 +1,37 @@
+---
+title: TiKV Overview
+category: reference
+---
+
+# TiKV Overview
+
+TiKV is a distributed and transactional key-value database, which provides transactional APIs with ACID compliance. With the implementation of the [Raft consensus algorithm](https://raft.github.io/raft.pdf) and consensus state stored in RocksDB, TiKV guarantees data consistency between multiple replicas and high availability. As the storage layer of the TiDB distributed database, it provides the read and write service, and persist the written data from applications. It also stores the statistic data of the TiDB cluster.
+
+## Architecture Overview
+
+TiKV is a distributed Key-Value database which is based on the design of Google Spanner. TiKV implements the multiple raft-group replica mechanism. Region is the basic unit of Key-Value data movement and corresponds to a data range in a Store. Each Region is replicated to multiple nodes. These multiple replicas form a Raft group. A replica of a Region is called a Peer. Typically there are 3 peers in a Region. One of them is the leader, which provides the read and write services. Region is the basic data movement unit, the PD balances all the Regions automatically to guarantee that the read and write throughput is balanced among all the nodes in the TiKV cluster. With PD and carefully designed Raft groups, TiKV excels in horizontal scalability and can easily scale to 100+ TBs of data.
+
+![TiKV Architecture](/media/tikv-arch.png)
+
+### Region and RocksDB
+
+There is a RocksDB database within each store and it stores data into the local disk. All the Region data are stored in the same RocksDB in each store. All the logs used for the Raft consensus algorithm is stored in another RocksDB in each store. This is because the performance of sequential I/O is
+better than random I/O. With different RocksDB for raftlog and Region data, TiKV can combine all the data write operation of raft log and TiKV regions into one I/O operation to improve the performance.
+
+### Region and Raft Consensus Algorithm
+
+Data consistency between replicas of a Region is guaranteed by the Raft Consensus Algorithm. Only the leader of the Region can provid the write service, only when the data is written to the majority replicated of a Region, the write operation is succeed.
+
+When the size of a certain Region exceed a threshold, which is 144 MB by default, TiKV splits it to two of more Regions. This operation guarantees the size of all the Regions in the cluster are nearly the same. It helps the PD to balance Regions among nodes in a TiKV cluster. When the size of a certain Region is smaller than a threshold, TiKV merges the two smaller adjacent Regins into one Region.
+
+When PD moves a replica from one TiKV to another, it firstly adds a Learner replica on the destination node, after the data in Follower replica is nearly the same with the Leader replica, PD changes it to the Follower replica and removes the replica on the source node.
+
+Moving Leader replica from one node to another follows nearly the same mechanism, the difference is, after the Learner replica becomes the Follower replica, there is operation to transfer Leader from the source node to the destination node. Finanly the new Leader removes the old replica in the source node.
+
+## Distributed Transaction
+
+TiKV supports distributed transaction. Users can write multiple key-value pairs without worrying about whether they belong to the same Region. TiKV uses two phase commit to achive the ACID constraints, see [TiDB Optimistic Transaction Model](/optimistic-transaction.md) for details.
+
+## TiKV Coprocessor
+
+TiDB pushes some data computation logic to TiKV Coprocessor. TiKV Coprocessor processes the computation for each Region. Each request send to TiKV Coprocessor only involves the data of one Region.

From e10216f3179536dea1475414d01112909a82d84e Mon Sep 17 00:00:00 2001
From: Zhang Jian <zjsariel@gmail.com>
Date: Mon, 6 Jul 2020 23:13:54 +0800
Subject: [PATCH 2/4] Update tikv-overview.md

---
 tikv-overview.md | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/tikv-overview.md b/tikv-overview.md
index 7bd3b7b93c1c1..b10e93323ffef 100644
--- a/tikv-overview.md
+++ b/tikv-overview.md
@@ -9,28 +9,28 @@ TiKV is a distributed and transactional key-value database, which provides trans
 
 ## Architecture Overview
 
-TiKV is a distributed Key-Value database which is based on the design of Google Spanner. TiKV implements the multiple raft-group replica mechanism. Region is the basic unit of Key-Value data movement and corresponds to a data range in a Store. Each Region is replicated to multiple nodes. These multiple replicas form a Raft group. A replica of a Region is called a Peer. Typically there are 3 peers in a Region. One of them is the leader, which provides the read and write services. Region is the basic data movement unit, the PD balances all the Regions automatically to guarantee that the read and write throughput is balanced among all the nodes in the TiKV cluster. With PD and carefully designed Raft groups, TiKV excels in horizontal scalability and can easily scale to 100+ TBs of data.
+TiKV is a distributed Key-Value database which is based on the design of Google Spanner. TiKV implements the multi-raft-group replica mechanism. The Region is the basic unit of the Key-Value data movement and corresponds to a data range in a Store. Each Region is replicated to multiple nodes. These multiple replicas form a Raft group. A replica of a Region is called a Peer. Typically there are 3 peers in a Region. One of them is the leader, which provides the read and write services. The Region is the basic data movement unit, the PD balances all the Regions automatically to guarantee that the read and write throughput is balanced among all the nodes in the TiKV cluster. With PD and carefully designed Raft groups, TiKV excels in horizontal scalability and can easily scale to 100+ TBs of data.
 
 ![TiKV Architecture](/media/tikv-arch.png)
 
 ### Region and RocksDB
 
 There is a RocksDB database within each store and it stores data into the local disk. All the Region data are stored in the same RocksDB in each store. All the logs used for the Raft consensus algorithm is stored in another RocksDB in each store. This is because the performance of sequential I/O is
-better than random I/O. With different RocksDB for raftlog and Region data, TiKV can combine all the data write operation of raft log and TiKV regions into one I/O operation to improve the performance.
+better than random I/O. With different RocksDB for raft log and Region data, TiKV can combine all the data write operation of raft log and TiKV regions into one I/O operation to improve the performance.
 
 ### Region and Raft Consensus Algorithm
 
-Data consistency between replicas of a Region is guaranteed by the Raft Consensus Algorithm. Only the leader of the Region can provid the write service, only when the data is written to the majority replicated of a Region, the write operation is succeed.
+Data consistency between replicas of a Region is guaranteed by the Raft Consensus Algorithm. Only the leader of the Region can provide the writing service, only when the data is written to the majority replicated of a Region, the write operation succeeds.
 
-When the size of a certain Region exceed a threshold, which is 144 MB by default, TiKV splits it to two of more Regions. This operation guarantees the size of all the Regions in the cluster are nearly the same. It helps the PD to balance Regions among nodes in a TiKV cluster. When the size of a certain Region is smaller than a threshold, TiKV merges the two smaller adjacent Regins into one Region.
+When the size of a certain Region exceeds a threshold, which is 144 MB by default, TiKV splits it to two or more Regions. This operation guarantees the size of all the Regions in the cluster is nearly the same. It helps the PD to balance Regions among nodes in a TiKV cluster. When the size of a certain Region is smaller than a threshold, TiKV merges the two smaller adjacent Regions into one Region.
 
 When PD moves a replica from one TiKV to another, it firstly adds a Learner replica on the destination node, after the data in Follower replica is nearly the same with the Leader replica, PD changes it to the Follower replica and removes the replica on the source node.
 
-Moving Leader replica from one node to another follows nearly the same mechanism, the difference is, after the Learner replica becomes the Follower replica, there is operation to transfer Leader from the source node to the destination node. Finanly the new Leader removes the old replica in the source node.
+Moving Leader replica from one node to another follows nearly the same mechanism, the difference is, after the Learner replica becomes the Follower replica, there is an operation to transfer Leader from the source node to the destination node. Finally, the new Leader removes the old replica in the source node.
 
 ## Distributed Transaction
 
-TiKV supports distributed transaction. Users can write multiple key-value pairs without worrying about whether they belong to the same Region. TiKV uses two phase commit to achive the ACID constraints, see [TiDB Optimistic Transaction Model](/optimistic-transaction.md) for details.
+TiKV supports distributed transactions. Users can write multiple key-value pairs without worrying about whether they belong to the same Region. TiKV uses two-phase commit to achieve the ACID constraints, see [TiDB Optimistic Transaction Model](/optimistic-transaction.md) for details.
 
 ## TiKV Coprocessor
 

From c17ff1cfa572dbb5d8e4e4aecc2fb89a448bb8f7 Mon Sep 17 00:00:00 2001
From: Zhang Jian <zjsariel@gmail.com>
Date: Mon, 13 Jul 2020 17:41:49 +0800
Subject: [PATCH 3/4] Apply suggestions from code review

Co-authored-by: Keke Yi <40977455+yikeke@users.noreply.github.com>
---
 tikv-overview.md | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/tikv-overview.md b/tikv-overview.md
index b10e93323ffef..69e0174215143 100644
--- a/tikv-overview.md
+++ b/tikv-overview.md
@@ -5,33 +5,33 @@ category: reference
 
 # TiKV Overview
 
-TiKV is a distributed and transactional key-value database, which provides transactional APIs with ACID compliance. With the implementation of the [Raft consensus algorithm](https://raft.github.io/raft.pdf) and consensus state stored in RocksDB, TiKV guarantees data consistency between multiple replicas and high availability. As the storage layer of the TiDB distributed database, it provides the read and write service, and persist the written data from applications. It also stores the statistic data of the TiDB cluster.
+TiKV is a distributed and transactional key-value database, which provides transactional APIs with ACID compliance. With the implementation of the [Raft consensus algorithm](https://raft.github.io/raft.pdf) and consensus state stored in RocksDB, TiKV guarantees data consistency between multiple replicas and high availability. As the storage layer of the TiDB distributed database, TiKV provides the read and write service, and persist the written data from applications. It also stores the statistics data of the TiDB cluster.
 
 ## Architecture Overview
 
-TiKV is a distributed Key-Value database which is based on the design of Google Spanner. TiKV implements the multi-raft-group replica mechanism. The Region is the basic unit of the Key-Value data movement and corresponds to a data range in a Store. Each Region is replicated to multiple nodes. These multiple replicas form a Raft group. A replica of a Region is called a Peer. Typically there are 3 peers in a Region. One of them is the leader, which provides the read and write services. The Region is the basic data movement unit, the PD balances all the Regions automatically to guarantee that the read and write throughput is balanced among all the nodes in the TiKV cluster. With PD and carefully designed Raft groups, TiKV excels in horizontal scalability and can easily scale to 100+ TBs of data.
+TiKV implements the multi-raft-group replica mechanism based on the design of Google Spanner. A Region is a basic unit of the key-value data movement and refers to a data range in a Store. Each Region is replicated to multiple nodes. These multiple replicas form a Raft group. A replica of a Region is called a Peer. Typically there are 3 peers in a Region. One of them is the leader, which provides the read and write services. The PD component balances all the Regions automatically to guarantee that the read and write throughput is balanced among all the nodes in the TiKV cluster. With PD and carefully designed Raft groups, TiKV excels in horizontal scalability and can easily scale to store more than 100 TBs of data.
 
 ![TiKV Architecture](/media/tikv-arch.png)
 
 ### Region and RocksDB
 
-There is a RocksDB database within each store and it stores data into the local disk. All the Region data are stored in the same RocksDB in each store. All the logs used for the Raft consensus algorithm is stored in another RocksDB in each store. This is because the performance of sequential I/O is
-better than random I/O. With different RocksDB for raft log and Region data, TiKV can combine all the data write operation of raft log and TiKV regions into one I/O operation to improve the performance.
+There is a RocksDB database within each Store and it stores data into the local disk. All the Region data are stored in the same RocksDB instance in each Store. All the logs used for the Raft consensus algorithm is stored in another RocksDB instance in each Store. This is because the performance of sequential I/O is
+better than random I/O. With different RocksDB instances storing raft logs and Region data, TiKV combines all the data write operations of raft logs and TiKV Regions into one I/O operation to improve the performance.
 
 ### Region and Raft Consensus Algorithm
 
-Data consistency between replicas of a Region is guaranteed by the Raft Consensus Algorithm. Only the leader of the Region can provide the writing service, only when the data is written to the majority replicated of a Region, the write operation succeeds.
+Data consistency between replicas of a Region is guaranteed by the Raft Consensus Algorithm. Only the leader of the Region can provide the writing service, and only when the data is written to the majority of replicas of a Region, the write operation succeeds.
 
-When the size of a certain Region exceeds a threshold, which is 144 MB by default, TiKV splits it to two or more Regions. This operation guarantees the size of all the Regions in the cluster is nearly the same. It helps the PD to balance Regions among nodes in a TiKV cluster. When the size of a certain Region is smaller than a threshold, TiKV merges the two smaller adjacent Regions into one Region.
+When the size of a Region exceeds a threshold, which is 144 MB by default, TiKV splits it to two or more Regions. This operation guarantees the size of all the Regions in the cluster is nearly the same, which helps the PD component to balance Regions among nodes in a TiKV cluster. When the size of a Region is smaller than the threshold, TiKV merges the two smaller adjacent Regions into one Region.
 
-When PD moves a replica from one TiKV to another, it firstly adds a Learner replica on the destination node, after the data in Follower replica is nearly the same with the Leader replica, PD changes it to the Follower replica and removes the replica on the source node.
+When PD moves a replica from one TiKV node to another, it firstly adds a Learner replica on the target node, after the data in the Learner replica is nearly the same as that in the Leader replica, PD changes it to a Follower replica and removes the Follower replica on the source node.
 
-Moving Leader replica from one node to another follows nearly the same mechanism, the difference is, after the Learner replica becomes the Follower replica, there is an operation to transfer Leader from the source node to the destination node. Finally, the new Leader removes the old replica in the source node.
+Moving Leader replica from one node to another has a similar mechanism. The difference is that after the Learner replica becomes the Follower replica, there is a "Leader Transfer" operation in which the Follower replica actively proposes an election to elect itself as the Leader. Finally, the new Leader removes the old Leader replica in the source node.
 
 ## Distributed Transaction
 
-TiKV supports distributed transactions. Users can write multiple key-value pairs without worrying about whether they belong to the same Region. TiKV uses two-phase commit to achieve the ACID constraints, see [TiDB Optimistic Transaction Model](/optimistic-transaction.md) for details.
+TiKV supports distributed transactions. Users (or TiDB) can write multiple key-value pairs without worrying about whether they belong to the same Region. TiKV uses two-phase commit to achieve ACID constraints. See [TiDB Optimistic Transaction Model](/optimistic-transaction.md) for details.
 
 ## TiKV Coprocessor
 
-TiDB pushes some data computation logic to TiKV Coprocessor. TiKV Coprocessor processes the computation for each Region. Each request send to TiKV Coprocessor only involves the data of one Region.
+TiDB pushes some data computation logic to TiKV Coprocessor. TiKV Coprocessor processes the computation for each Region. Each request sent to TiKV Coprocessor only involves the data of one Region.

From 3cb811a2164c38a612e22beb88b4c81c8b2287e6 Mon Sep 17 00:00:00 2001
From: Keke Yi <40977455+yikeke@users.noreply.github.com>
Date: Mon, 13 Jul 2020 17:52:04 +0800
Subject: [PATCH 4/4] remove category meta

---
 tikv-overview.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tikv-overview.md b/tikv-overview.md
index 69e0174215143..df672d12aed81 100644
--- a/tikv-overview.md
+++ b/tikv-overview.md
@@ -1,6 +1,6 @@
 ---
 title: TiKV Overview
-category: reference
+summary: An overview of the TiKV storage engine.
 ---
 
 # TiKV Overview