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+# Node.js
 node_modules/
 package-lock.json
+
+# Others
+.DS_Store
\ No newline at end of file
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+# Improve the Scalability of TSO Service
+
+- RFC PR: https://github.com/tikv/rfcs/pull/78
+- Tracking Issue: https://github.com/tikv/pd/issues/3149
+
+## Summary
+
+As the size of the cluster grows, some users encountered a situation that is
+extremely challenging for TSO performance. In this kind of cluster that may
+have many TiDB instances, a certain number of PD clients will request TSO to
+the PD leader concurrently, and this puts a lot of CPU pressure on the PD leader
+because of the Go Runtime scheduling caused by the gRPC connection switch. With
+the high CPU pressure, TSO requests will suffer from increasing average latency
+and long-tail latency, which will hurt TiDB's QPS performance. To improve the
+scalability of the TSO Service, we will propose two kinds of enhancement to both TSO
+client and server in this RFC to reduce the PD CPU usage and improve QPS performance.
+
+## Motivation
+
+As mentioned before, improvement is needed in the cluster that has a certain number
+of TiDB instances, i.e PD clients, to reduce the CPU pressure of PD leader. With
+better TSO handling performance, in this case, TSO service won't be the potential
+bottleneck of a big cluster easily and have better scalability.
+
+## Detailed design
+
+### Current TSO processing flow
+
+Before proposing specific improvements, let me give a brief overview of the current
+PD client and TSO processing flow first.
+
+For the PD client, every time it receive a TSO request from the upper level, it won't
+send the TSO gRPC request to the PD leader immediately. Instead, it will collect as
+many TSO requests as it can from a channel and batch them as a single request to
+send to reduce the gRPC request number it actually sent. For example, at a certain
+moment, PD client may receive 10 TSO requests at once, it will send just one TSO gRPC
+request to the PD leader with an argument `count` inside the gRPC request body.
+
+![TSO Client Batch - Old](../media/tso-client-batch-old.png)
+
+For the PD server, it just takes the request and returns an incremental and unique TSO
+request with 4 counts and return it to the client. After the PD client receives the
+response, it will split the single TSO request into 10 different TSOs and return it to
+the upper requester.
+
+During the whole process flow, every PD client will maintain a gRPC stream with the PD
+leader to send and receive the TSO request efficiently.
+
+### Enhancement #1: Improve the batch effect
+
+An intuitive improvement is to improve the batch effect of TSO, i.e. to reduce the number
+of TSO gRPC requests by increasing the size of each batch with the same number of TSO requests.
+With fewer TSO gRPC requests, the CPU pressure on the PD leader can be reduced directly.
+
+We can introduce different batch strategies such as waiting for a while to fetch more TSO requests
+in a same interval or even more complicated one like a dynamic smallest batch size.
+
+![TSO Client Batch - New](../media/tso-client-batch-new.png)
+
+As the figure above shows, we can introduce a session variable like `@@tidb_tso_client_batch_max_wait_time`
+to control the max wait time the PD client is willing to wait for more TSO requests, which could make the
+batch size bigger without hurting the latency.
+
+Predicting strategy is also a useful way to improve the batch effect. For example, the PD Client
+could collect as much information as it needs such as latency and batch size in the last few minutes,
+then base on these information, the PD client could calculate a suitable expected batch size to predict
+the incoming TSO number, which make the batch waiting more effective.
+
+### Enhancement #2: Use proxy to reduce the stream number
+
+However, as mentioned before, according to our pprof result, the main reason of high PD leader
+CPU usage is the Go Runtime scheduling caused by the gRPC connection switch. Batch effect
+improvement does not alleviate this part at the root. To reduce the connection switch,
+fewer gRPC stream number is necessary. We can introduce the TSO Follower Proxy feature
+to achieve this.
+
+Every TSO request will be sent to different TSO servers (including both the PD leader and follower)
+randomly by the PD client, and multiple TSO requests sent to the same TSO follower will be
+batched again with the same logic as a PD client before being forwarded to the PD leader.
+With this implementation, the gRPC pressure is distributed to each PD server, and for the
+PD leader, if we have 50 TiDB instances and 5 PD instances, it only needs to maintain 4
+stream connections with each PD follower rather than 50 stream connections with all the TiDB
+servers.
+
+![TSO Follower Proxy](../media/tso-follower-proxy.png)
+
+Also, this could be configured in a TiDB cluster by enabling a single session variable like `tidb_enable_tso_follower_proxy` globally.
+
+## Drawbacks
+
+- Increase the TSO latency if the QPS is not high enough.
+- Increase the CPU usage of the PD followers.
+- Increase code complexity.