From 14f766929cd6476a15c72f1f2e806a9eab0b445c Mon Sep 17 00:00:00 2001 From: raylchen Date: Tue, 17 Oct 2023 17:40:52 +0800 Subject: [PATCH] Docs: Add overload control for flow control --- docs/README.md | 3 +- docs/README.zh_CN.md | 3 +- ...r.md => overload_control_fiber_limiter.md} | 2 +- docs/en/overload_control_flow_limiter.md | 172 +++++++++++++++++ docs/en/plugin_management.md | 3 +- docs/en/server_guide.md | 3 +- docs/images/flow_control_limiter.png | Bin 0 -> 98221 bytes docs/images/flow_control_limiter_second_1.png | Bin 0 -> 231909 bytes docs/images/flow_control_limiter_second_2.png | Bin 0 -> 228416 bytes docs/images/flow_control_limiter_smooth.png | Bin 0 -> 304517 bytes .../overload_control_concurrency_limiter.md | 4 +- ...r.md => overload_control_fiber_limiter.md} | 2 +- docs/zh/overload_control_flow_limiter.md | 175 ++++++++++++++++++ docs/zh/plugin_management.md | 3 +- docs/zh/server_guide.md | 3 +- .../flow_controller_server_filter.cc | 8 +- .../flow_control/seconds_limiter.cc | 1 + .../flow_control/smooth_limiter.cc | 1 + 18 files changed, 369 insertions(+), 14 deletions(-) rename docs/en/{overload_control_filter_limiter.md => overload_control_fiber_limiter.md} (99%) create mode 100644 docs/en/overload_control_flow_limiter.md create mode 100644 docs/images/flow_control_limiter.png create mode 100644 docs/images/flow_control_limiter_second_1.png create mode 100644 docs/images/flow_control_limiter_second_2.png create mode 100644 docs/images/flow_control_limiter_smooth.png rename docs/zh/{overload_control_filter_limiter.md => overload_control_fiber_limiter.md} (99%) create mode 100644 docs/zh/overload_control_flow_limiter.md diff --git a/docs/README.md b/docs/README.md index a48c2127..1f364442 100644 --- a/docs/README.md +++ b/docs/README.md @@ -44,7 +44,8 @@ English | [中文](README.zh_CN.md) * [custom filter](./en/filter.md) * Flow-Control & Overload-Protect * [concurrency requests limiter plugin](./en/overload_control_concurrency_limiter.md) - * [concurrency fibers limiter plugin](./en/overload_control_filter_limiter.md) + * [concurrency fibers limiter plugin](./en/overload_control_fiber_limiter.md) + * [flow control limiter plugin](./en/overload_control_flow_limiter.md) * Naming * [custom naming plugin](./en/custom_naming.md) * [mesh-polaris](https://github.com/trpc-ecosystem/cpp-naming-polarismesh/blob/main/README.md) diff --git a/docs/README.zh_CN.md b/docs/README.zh_CN.md index 513d94cf..07d68c32 100644 --- a/docs/README.zh_CN.md +++ b/docs/README.zh_CN.md @@ -43,7 +43,8 @@ * [开发自定义拦截器](./zh/filter.md) * 流控和过载保护 * [基于并发请求的过载保护插件](./zh/overload_control_concurrency_limiter.md) - * [基于并发 Fiber 个数的过载保护插件](./zh/overload_control_filter_limiter.md) + * [基于并发 Fiber 个数的过载保护插件](./zh/overload_control_fiber_limiter.md) + * [基于流量控制的过载保护插件](./zh/overload_control_flow_limiter.md) * Naming插件 * [开发自定义naming插件](./zh/custom_naming.md) * [mesh-polaris](https://github.com/trpc-ecosystem/cpp-naming-polarismesh/blob/main/README.zh_CN.md) diff --git a/docs/en/overload_control_filter_limiter.md b/docs/en/overload_control_fiber_limiter.md similarity index 99% rename from docs/en/overload_control_filter_limiter.md rename to docs/en/overload_control_fiber_limiter.md index 0defd8fd..89a805ed 100644 --- a/docs/en/overload_control_filter_limiter.md +++ b/docs/en/overload_control_fiber_limiter.md @@ -1,4 +1,4 @@ -[中文](../zh/overload_control_filter_limiter.md) +[中文](../zh/overload_control_fiber_limiter.md) # Overview diff --git a/docs/en/overload_control_flow_limiter.md b/docs/en/overload_control_flow_limiter.md new file mode 100644 index 00000000..03685e07 --- /dev/null +++ b/docs/en/overload_control_flow_limiter.md @@ -0,0 +1,172 @@ +[中文](../zh/overload_control_flow_limiter.md) + +# Overview + +The capacity of a single node to handle requests is limited. In order to ensure high availability of the service, we must impose some restrictions on the number of requests. The need for flow control arises in this context. The current tRPC-Cpp framework supports flow control configuration at two levels: service and function. The measurement dimension is QPS. + +- Two flow control algorithms are used: + - Fixed window (counting method), corresponding to the flow control controller: `seconds` (fixed window), also known as `default`. + - Sliding window, corresponding to the flow control controller: `smooth` (sliding window). +- Throttling trigger conditions + + First, the service flow limit is checked. If the service flow limit is exceeded, a flow control error is returned. Then, the interface flow limit is checked. If it exceeds the limit, a flow control error is returned. + +*Note: The algorithm principles behind flow control are quite complex. A dedicated section will be provided to explain them in detail.* + +# Principle + +## Principle diagram of overload protection based on flow control + +![flow_control_limiter](../images/flow_control_limiter.png) +The core point in the diagram is the `FlowControlLimiter`, which is primarily responsible for calculating the current QPS (requests per second) using traffic control algorithms. It compares the number of requests (`reqs_counter`) within a 1-second time window to the maximum number of requests configured in the window (`win_limit`) to determine whether to reject the new incoming request (`curr_req`). The logic is straightforward. + +## Implementation code + +The overload protection implementation of the framework is based on [filters](./filter.md), in order to ensure flow control protection as early as possible. This filter is placed before the request is enqueued, and the specific implementation of the filter placement is as follows: + +```cpp +std::vector FlowControlServerFilter::GetFilterPoint() { + return { + FilterPoint::SERVER_PRE_SCHED_RECV_MSG, + // ... + }; +} +``` + + Source code: [flow_control_server_filter](../../trpc/overload_control/flow_control/flow_controller_server_filter.cc) + +# Usage example + +The overload protection filter based on flow control can currently **only be applied to the server-side, and client-side support is not available at the moment**. Users can use it without modifying any code by simply enabling compilation and adding configurations, making it very convenient. + +## Compilation options + +Add the following line to the `.bazelrc` file. + +```sh +build --define trpc_include_overload_control=true +``` + +## Configuration file + +The server-side flow control configuration is as follows (for detailed configuration, refer to [flow_test.yaml](../../trpc/overload_control/flow_control/flow_test.yaml)): + +```yaml +#Server configuration +server: + app: test #Business name, such as: COS, CDB. + server: helloworld #Module name of the business + admin_port: 21111 # Admin port + admin_ip: 0.0.0.0 # Admin ip + service: #Business service, can have multiple. + - name: trpc.test.helloworld.Greeter #Service name, needs to be filled in according to the format, the first field is default to trpc, the second and third fields are the app and server configurations above, and the fourth field is the user-defined service_name. + network: tcp #Network listening type: for example: TCP, UDP. + ip: 0.0.0.0 #Listen ip + port: 10001 #Listen port + protocol: trpc #Service application layer protocol, for example: trpc, http. + accept_thread_num: 1 #Number of threads for binding ports. + filter: + - flow_control + +#Plugin configuration. +plugins: +# metrics: +# prometheus: + # ... + overload_control: + flow_control: + - service_name: trpc.test.helloworld.Greeter #service name. + is_report: true # Whether to report monitoring data. + service_limiter: default(100000) # Service-level flow control limiter, standard format: name (maximum limit per second), empty for no limit. + func_limiter: #Interface-level flow control. + - name: SayHello ##Method name + limiter: seconds(50000) #Interface-level flow control limiter, standard format: name (maximum limit per second), empty for no limit. + - name: Route #Method name + limiter: smooth(80000) #Interface-level flow control limiter, standard format: name (maximum limit per second), empty for no limit. +``` + +The key points of the configuration are as follows: + +- flow_control: The name of the flow control overload protector +- service_name: The name of the service associated with flow control. +- service_limiter: Specifies the service-level flow control algorithm for the service name `service_name`. Here, the configuration `default(100000)` is explained as follows: + - `default` (equivalent to `seconds`): Indicates that the fixed window flow control algorithm is selected. + - `100000`: Represents the maximum number of requests per second, i.e., the maximum QPS is 100000. +- func_limiter: Specifies the interface-level flow control strategy for the service name `service_name`. Each service can have multiple interfaces, and each interface can choose a different flow control algorithm. The details are as follows: + - `name`: The name of the interface, such as `SayHello` and `Route`. + - `limiter`: Specifies the flow control algorithm for the interface. For example, `Route` is configured with the sliding window (smooth) algorithm, with a maximum QPS of 80000. +- is_report: Specifies whether to report monitoring data to the monitoring plugin. **Note that this configuration must be used together with a monitoring plugin (e.g., configuration: plugins->metrics->prometheus), otherwise, this option is meaningless**. The monitoring data for different flow control algorithms is as follows: + - seconds: + - `SecondsLimiter`: The name of the flow control algorithm used to check if the configuration matches the one executed in the program. + - `/{callee_name}/{method}`: The format of the monitoring name, composed of the callee service (callee_name) and the method name (method). For example: `/trpc.test.helloworld.Greeter/SayHello`. + - `current_qps`: The current concurrent QPS value. + - `max_qps`: The configured maximum QPS, used to check if the maximum QPS in the configuration matches the one executed in the program. + - `window_size`: The number of sampling windows. Users may not need to pay attention to this. + - `Pass`: The pass status of a single request, where 0 means intercepted and 1 means passed. + - `Limited`: The interception status of a single request, where 1 means intercepted and 0 means passed. This is the opposite of the `Pass` monitoring attribute mentioned above. + - smooth: + - `SmoothLimiter`: The name of the flow control algorithm used to check if the configuration matches the one executed in the program. + - `/{callee_name}/{method}`: The format of the monitoring name, composed of the callee service (callee_name) and the method name (method). For example: `/trpc.test.helloworld.Greeter/SayHello`. + - `active_sum`: The sum of all requests in the hit time slots, representing the QPS value at the moment after excluding the current request. If it exceeds the maximum QPS, the `hit_num` below will be 0. + - `hit_num`: The QPS value after adding one request to the hit time slot. + - `max_qps`: The configured maximum QPS, used to check if the maximum QPS in the configuration matches the one executed in the program. + - `window_size`: The number of sampling windows. Users may not need to pay attention to this. + - `Pass`: The pass status of a single request, where 0 means intercepted and 1 means passed. + - `Limited`: The interception status of a single request, where 1 means intercepted and 0 means passed. This is the opposite of the `Pass` monitoring attribute mentioned above. + +## Implementing flow control using code + +In addition to configuring flow control, flow control functionality can also be implemented directly through code (note the difference between service-level and interface-level flow control code). The registration methods for service-level and interface-level flow controllers for business users are as follows: + +```cpp +class HelloWorldServer : public ::trpc::TrpcApp { + public: + // ... + int RegisterPlugins() { + + // ... + + // Registering a service-level flow controller. + trpc::FlowControllerPtr service_controller(new trpc::SmoothLimter(200000, true, 100)); + trpc::FlowControllerFactory::GetInstance()->Register( "trpc.test.helloworld.Greeter", service_controller); + + // Registering an interface-level flow controller. + trpc::FlowControllerPtr say_hello_controller(new trpc::SecondsLimiter(10000, true, 100)); + trpc::FlowControllerFactory::GetInstance()->Register( "/trpc.test.helloworld.Greeter/SayHello", say_hello_controller); + return 0; + } + +}; +``` + +The registration logic for the flow controller must be executed in the `RegisterPlugins` function within the `trpc::TrpcApp` interface. + +- For detailed information about the `trpc::SmoothLimiter` class, refer to: [SmoothLimiter](../../trpc/overload_control/flow_control/smooth_limiter.h). +- For detailed information about the `trpc::SecondsLimiter` class, refer to: [SecondsLimiter](../../trpc/overload_control/flow_control/seconds_limiter.h). + +# Principles of flow control algorithms + +Below is a brief explanation of the implementation algorithms for fixed window traffic control and sliding window traffic control. + +## Fixed window traffic control algorithm + +The fixed window algorithm, also known as the fixed window counter algorithm, divides time into fixed-sized windows along the timeline. It limits the maximum number of requests allowed within each time window to a predefined threshold. At any given moment, the system operates within a specific time window. When a new request arrives within the current time window, the counter for that window is atomically incremented. Additionally, each new request checks the total number of requests allowed within the current time window against the threshold. If the counter exceeds the threshold, the remaining requests are rejected. It is important to note that as time progresses and the time window shifts, the counter within each window is reset to 0. + +![flow_control_limiter_second_1](../images/flow_control_limiter_second_1.png) + +The fixed window algorithm is the simplest traffic control algorithm in terms of principles and implementation. It typically involves setting a global counter to track the number of requests allowed within the current time window and making decisions for incoming requests. Additionally, the counter is reset whenever the time reaches the start of a new time window. The specific steps are as follows: + +- Divide time into multiple windows. +- Increment the counter for each request within the window. +- If the counter exceeds the limit, reject the remaining requests within the current time window. Reset the counter when the time reaches the next window. ![flow_control_limiter_second_2](../images/flow_control_limiter_second_2.png) However, the fixed window algorithm also has a **boundary problem** due to the fixed position of the windows. This means that there can be situations where the actual number of requests passing through exceeds the limit at the boundary positions of the windows. While the number of requests allowed within each individual time window is below the threshold, the combination of two windows at the boundary position may result in a window size that still satisfies the 1-second setting, but allows twice the number of requests as the threshold. + +## Sliding window traffic control algorithm + +To address the limitations of the fixed window algorithm described above, researchers have developed the sliding window counter algorithm. Instead of using fixed windows, this algorithm uses **sliding** windows that move with time. This ensures that within each sliding window, the condition `counter <= limit` is always satisfied. The sliding windows overlap with each other due to the sliding algorithm, eliminating the occurrence of boundary effects. The specific steps of the sliding window algorithm are as follows: + +- Divide time into multiple intervals. +- Within each time interval, divide time into smaller slices. The sliding window moves one slice at a time according to the time rules. +- Increment the counter for each request within each window. +- Check the total count within the latest sliding window against the threshold to decide whether to accept or reject the service. Services that exceed the threshold are rejected. +- When the sliding window moves, the counts from the slices that move out of the sliding window are discarded, and the counts within the new slices are reset to zero. +![flow_control_limiter_smooth](../images/flow_control_limiter_smooth.png) The sliding window algorithm is an upgraded version of the fixed window algorithm. By subdividing the windows and **sliding** them according to time, it improves accuracy and eliminates **boundary effects**. However, this improvement comes at the cost of increased computational overhead. diff --git a/docs/en/plugin_management.md b/docs/en/plugin_management.md index 329712d9..58c0312f 100644 --- a/docs/en/plugin_management.md +++ b/docs/en/plugin_management.md @@ -56,7 +56,8 @@ The framework takes inspiration from Java's Aspect-Oriented Programming (AOP) pa It provides the ability for flow controlling and overload protecting. For more details, please refer to the **documentation of customizing Flow-Control & Overload-Protect plugin**. * [Concurrent requests limiter](./overload_control_concurrency_limiter.md) - * [Concurrent fibers limiter](./overload_control_filter_limiter.md) + * [Concurrent fibers limiter](./overload_control_fiber_limiter.md) + * [Flow control limiter plugin](./overload_control_flow_limiter.md) ## Other features diff --git a/docs/en/server_guide.md b/docs/en/server_guide.md index 31fddc1f..8d1a0b7e 100644 --- a/docs/en/server_guide.md +++ b/docs/en/server_guide.md @@ -240,4 +240,5 @@ See [Transparent proxy](transparent_service.md). ### Flow-Control & Overload-Protect * See [Concurrent requests limiter](./overload_control_concurrency_limiter.md) -* See [Concurrent fibers limiter](./overload_control_filter_limiter.md) +* See [Concurrent fibers limiter](./overload_control_fiber_limiter.md) +* See [Flow control limiter plugin](./overload_control_flow_limiter.md) diff --git 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z&7(>O`G$BtlG)Ka9_iP&A(`MfM0ik?Lv!NUU85%B7qnZ{QErq?7nti{f2!9ScpJ9{ zdDGeSuu9@+K@ALw6}I<@p&ZLw2(Qu+Guc$6fL?guz`hAa8HFs{B4aEAgBH%o?92}W zNvF5cmOhpJ&1SR7Wa%0*Vw%Fs={o7C$M)sMZ2=41QP?@-2yy|2D0|;gd=-RooR%;t zf2S@hj3sbVpL5Y%OYcN5V81>b%amYz;aa`ocFh5n0zxWHZaA%7xw6`YD}^~jraA9z zZQ|Ha5YUEXx3Y+OAS#MG&eah~Q0*hR0K0qNNNY044;U~Y#ww=n;?p&(Yq4q+s8OIs zff@z6NP(K--bF&~`)JnDt0ztu*i)85`9KwGY1LY9G&4T%7d2K+-F6XS*L4?P_P`$$ zO{W5xWmFl+>W`(D`&x2X7K3Cw=4V2$uXzMF^|H@b($ z2AUJIH?;O_E}l%0T}!$UjmOe0IW%_~ptXl6hb4*1PH~UOB2eGpH8fdc;@K7ivpZH2hs00000NkvXXu0mjf^h%3! literal 0 HcmV?d00001 diff --git a/docs/zh/overload_control_concurrency_limiter.md b/docs/zh/overload_control_concurrency_limiter.md index e6ecc4df..8fa3b30c 100644 --- a/docs/zh/overload_control_concurrency_limiter.md +++ b/docs/zh/overload_control_concurrency_limiter.md @@ -75,8 +75,8 @@ plugins: - concurrency_limiter:并发请求过载保护器的名称 - max_concurrency:为用户配置的最大并发请求数,当当前并发请求大于等于该值的时候,会拦截请求 - is_report:是否上报监控数据到监控插件,**注意,该配置必须与监控插件一起使用(例如配置:plugins->metrics->prometheus,则会上报到 prometheus 上),如果没有配置监控插件,该选项无意义**,被监控数据有: - - `max_concurrency`: 上报配置的最大并发请求数,属于固定值,用于检查配置的最大请求并发数是否在程序中生效 - - `current_concurrency`: 上报当前并发请求数,属于动态值 + - `max_concurrency`:上报配置的最大并发请求数,属于固定值,用于检查配置的最大请求并发数是否在程序中生效 + - `current_concurrency`:上报当前并发请求数,属于动态值 - `/{callee_name}/{method}`: 上报监控的 RPC 方法名,属于固定值;由被调服务(callee_name)和方法名(method)组成,例如:`/trpc.test.helloworld.Greeter/SayHello`。 - `Pass`:单个请求的通过状态,0:拦截;1:通过 - `Limited`:单个请求的拦截状态,1:拦截;0:通过。与上面的 `Pass` 监控属性是相反的 diff --git a/docs/zh/overload_control_filter_limiter.md b/docs/zh/overload_control_fiber_limiter.md similarity index 99% rename from docs/zh/overload_control_filter_limiter.md rename to docs/zh/overload_control_fiber_limiter.md index 20019bcc..7453a733 100644 --- a/docs/zh/overload_control_filter_limiter.md +++ b/docs/zh/overload_control_fiber_limiter.md @@ -1,4 +1,4 @@ -[English](../en/overload_control_filter_limiter.md) +[English](../en/overload_control_fiber_limiter.md) # 前言 diff --git a/docs/zh/overload_control_flow_limiter.md b/docs/zh/overload_control_flow_limiter.md new file mode 100644 index 00000000..db0ef303 --- /dev/null +++ b/docs/zh/overload_control_flow_limiter.md @@ -0,0 +1,175 @@ +[English](../en/overload_control_flow_limiter.md) + +# 前言 + +单个节点对请求的承载能力是有限的,为了保证服务的高可用性,我们必须对请求数做一些限制;流量控制需求就是在这个背景下产生的。当前 tRPC-Cpp 框架支持对服务(service)及函数(function)两个维度的流量控制配置,考察维度为 QPS(每秒最大限制数)。 + +- 分别使用了两种流量控制算法: + - 固定窗口(计数法),对应的流量控制控制器:`seconds`(即固定窗口),也称为 `default` + - 滑动窗口,对应的流量控制控制器:`smooth`(滑动窗口) +- 限流触发条件 + + 首先判断服务流量限制,当服务流量限制超过后,返回流控错误;然后判断接口流量限制,超过限制则返回流控错误 + +*注意:关于流量控制的算法原理比较复杂,最后专门用一小节讲解。* + +# 原理 + +## 基于流量控制的过载保护原理图 + +![flow_control_limiter](../images/flow_control_limiter.png) +图中核心点就是`FlowControlLimiter` ,它的主要作用是通过流量控制算法计算当前的 QPS,也即 1s 时间中的请求数(`reqs_counter`)与窗口中配置的最大请求数(`win_limit`)进行比较来判断是否拒绝当前接收的新请求(`curr_req`),逻辑很简单。 + +## 实现代码 + +框架的过载保护实现方式是基于[过滤器](./filter.md),为了保证尽可能早进行限流保护;该过滤器会埋点在请求入队前,具体埋点实现如下: + +```cpp +std::vector FlowControlServerFilter::GetFilterPoint() { + return { + FilterPoint::SERVER_PRE_SCHED_RECV_MSG, + // ... + }; +} +``` + +源码参考:[flow_control_server_filter](../../trpc/overload_control/flow_control/flow_controller_server_filter.cc) + +# 使用示例 + +基于流量控制的过载保护过滤器,**当前只能应用于服务端,客户端暂时不支持**,用户使用无需修改任何代码,只需开启编译和增加配置即可,非常方便。 + +## 编译选项 + +编译选项:在`.bazelrc` 文件中加入下面一行 + +```sh +build --define trpc_include_overload_control=true +``` + +## 配置文件 + +服务端流量控制配置如下(详细配置参考:[flow_test.yaml](../../trpc/overload_control/flow_control/flow_test.yaml)): + +```yaml +#Server configuration +server: + app: test #Business name, such as: COS, CDB. + server: helloworld #Module name of the business + admin_port: 21111 # Admin port + admin_ip: 0.0.0.0 # Admin ip + service: #Business service, can have multiple. + - name: trpc.test.helloworld.Greeter #Service name, needs to be filled in according to the format, the first field is default to trpc, the second and third fields are the app and server configurations above, and the fourth field is the user-defined service_name. + network: tcp #Network listening type: for example: TCP, UDP. + ip: 0.0.0.0 #Listen ip + port: 10001 #Listen port + protocol: trpc #Service application layer protocol, for example: trpc, http. + accept_thread_num: 1 #Number of threads for binding ports. + filter: + - flow_control + +#Plugin configuration. +plugins: +# metrics: +# prometheus: + # ... + overload_control: + flow_control: + - service_name: trpc.test.helloworld.Greeter #service name. + is_report: true # Whether to report monitoring data. + service_limiter: default(100000) # Service-level flow control limiter, standard format: name (maximum limit per second), empty for no limit. + func_limiter: #Interface-level flow control. + - name: SayHello ##Method name + limiter: seconds(50000) #Interface-level flow control limiter, standard format: name (maximum limit per second), empty for no limit. + - name: Route #Method name + limiter: smooth(80000) #Interface-level flow control limiter, standard format: name (maximum limit per second), empty for no limit. +``` + +配置关键点如下: + +- flow_control:流量控制过载保护器的名称 +- service_name:流量控制对应的服务名称 +- service_limiter:指定服务名 `service_name` 下的服务级流控算法;这里配置 `default(100000)` 介绍如下: + - `default`(等同 `seconds`):表示此处选择了固定窗口流量控制算法 + - `100000`:表示每秒最大的请求数,也即最大 QPS 是 100000 +- func_limiter:指定服务名 `service_name` 下的接口级流控策略;每个服务可以存在多个接口,每个接口可以选择不同的流量控制算法,介绍如下: + - `name`:接口名称,如:`SayHello` 和 `Route` + - `limiter`:指定接口流控算法,例如:`Route` 配置了滑动窗口(smooth)算法,最大 QPS 是 80000 +- is_report:是否上报监控数据到监控插件,**注意,该配置必须与监控插件一起使用(例如配置:plugins->metrics->prometheus,则会上报到 prometheus 上),如果没有配置监控插件,该选项无意义**,不同流量控制算法监控数据分别如下: + - seconds: + - `SecondsLimiter`:流控算法名称,用于检查配置和程序中执行的流量控制算法是否一致 + - `/{callee_name}/{method}`:监控名称格式,由被调服务(callee_name)和方法名(method)组成,例如:`/trpc.test.helloworld.Greeter/SayHello` + - `current_qps`:当前并发 QPS 值 + - `max_qps`: 配置的最大 QPS,用于检查配置和程序中执行的流量控制最大 QPS 是否一致 + - `window_size`:采样窗口个数,用户可不关注 + - `Pass`:单个请求的通过状态,0:拦截;1:通过 + - `Limited`:单个请求的拦截状态,1:拦截;0:通过。与上面的 `Pass` 监控属性是相反的 + - smooth: + - `SmoothLimiter`:流控算法名称,用于检查配置和程序中执行的流量控制算法是否一致 + - `/{callee_name}/{method}`: 监控名称格式,由被调服务(callee_name)和方法名(method)组成,例如:`/trpc.test.helloworld.Greeter/SayHello` + - `active_sum`:所有命中的时间片中的请求总和,表示除去当前请求后此刻的 QPS 值,若超过最大 QPS,下面的 `hit_num` 则为 0 + - `hit_num`:当前命中时间片增加一个请求后的的 QPS 值 + - `max_qps`:配置的最大 QPS,用于检查配置和程序中执行的流量控制最大 QPS 是否一致 + - `window_size`:采样窗口个数,用户可不关注 + - `Pass`:单个请求的通过状态,0:拦截;1:通过 + - `Limited`:单个请求的拦截状态,1:拦截;0:通过。与上面的 `Pass` 监控属性是相反的 + +## 代码方式采用流量控制 + +除了通过配置流量控制之外,还可以直接通过代码实现流量控制功能(**注意服务流量控制和接口流量控制的代码区别**)。业务使用者注册服务级和接口级流量控制器方式如下: + +```cpp +class HelloWorldServer : public ::trpc::TrpcApp { + public: + // ... + int RegisterPlugins() { + + // ... + + // 注册服务级流量控制器 + trpc::FlowControllerPtr service_controller(new trpc::SmoothLimter(200000, true, 100)); + trpc::FlowControllerFactory::GetInstance()->Register( "trpc.test.helloworld.Greeter", service_controller); + + // 注册接口级流量控制器 + trpc::FlowControllerPtr say_hello_controller(new trpc::SecondsLimiter(10000, true, 100)); + trpc::FlowControllerFactory::GetInstance()->Register( "/trpc.test.helloworld.Greeter/SayHello", say_hello_controller); + return 0; + } + +}; +``` + +流量控制器的注册逻辑必须在 `trpc::TrpcApp` 注册接口中 `RegisterPlugins` 中执行,其中: + +- `trpc::SmoothLimter` 类的详细介绍参考:[SmoothLimter](../../trpc/overload_control/flow_control/smooth_limiter.h) +- `trpc::SecondsLimiter` 类的详细介绍参考:[SecondsLimiter](../../trpc/overload_control/flow_control/seconds_limiter.h) + +# 流量控制算法原理 + +下面分别就固定窗口流量控制实现算法和滑动窗口流量控制实现算法做一个简单说明。 + +## 固定窗口流量控制算法 + +固定窗口法又称为固定窗口计数器法,其在时间线性维度上将时间划分为固定大小的窗口,同时限定每个时间窗口内允许通过的请求数上限为设定的阈值。每一时刻都处于一个固定的时间窗口内,而当前时间窗口每接收一个新的请求,时间窗口内的计数器就会原子的自增;同时每一个新的请求到达时都会判断当前时间窗口内通过的请求个数总和与阈值的大小,若计数器超过了限制阈值,则会拒绝剩余的请求。注意随着时间的流逝,每当时间窗口变换时窗口内的计数器都会重置为 0。 + +![flow_control_limiter_second_1](../images/flow_control_limiter_second_1.png) + +固定窗口法是原理最简单的流量控制算法,同时其实现也最为简单,一般设定一个全局的 counter 记录当前时间窗口内允许的请求,同时对新进入的请求进行判断;同时每当时间到达新的时间窗口点时就对 counter 进行重置。具体措施为: + +- 将时间划分为多个窗口 +- 在每个窗口内每有一次请求就将计数器加一 +- 如果计数器超过了限制数量,则拒绝当前时间窗口内剩余请求。当时间到达下一个窗口时,计数器重置 + ![flow_control_limiter_second_2](../images/flow_control_limiter_second_2.png) + 但同时,固定时间窗口法也由于其固定窗口的位置导致**边界问题**。即在窗口的边界位置易发生实际通过请求数高于限制阈值的情况。两个时间窗口内允许的请求数量都满足小于阈值,但由于两个窗口内请求都在边界位置,故对于两个窗口边界位置组成的窗口处,其窗口大小依然满足设定的1s,但该窗口内允许通过的请求数却是阈值的两倍。 + +## 滑动窗口流量控制算法 + +为了解决以上所描述的固定窗口算法的不足,人们研究出了滑动窗口计数器法。即将原本固定的窗口改为随时间而**滑动**的窗口,这样在每一个滑动窗口内都满足 `counter <= limit`,且窗口与窗口之间由于**滑动**算法,相互有重叠,保证了不会出现**边界效应**。滑动窗口法的具体措施为为: + +- 将时间划分为多个区间 +- 在每个时间区间内,将时间分片,滑动窗口每次根据时间规则滑动一个分片 +- 在每个窗口内每有一次请求就将计数器加一 +- 每次判断最新滑动窗口内的总计数与阈值的大小选择是否接受服务,超出阈值的服务都将被拒绝 +- 每次滑动窗口移动时,移出滑动窗口的分片内计数都将被抛弃,划入时间分片内的计数都将置零 + ![flow_control_limiter_smooth](../images/flow_control_limiter_smooth.png) + 滑动窗口法即固定窗口法的升级版。其通过将窗口再进行细分,且按照时间**滑动**,提升了精度,避免了**边界效应**;但同时也由此提升了计算的性能消耗。 diff --git a/docs/zh/plugin_management.md b/docs/zh/plugin_management.md index 717626b9..81ef50d9 100644 --- a/docs/zh/plugin_management.md +++ b/docs/zh/plugin_management.md @@ -56,7 +56,8 @@ tRPC-Cpp 框架基于接口编程的思想,把框架功能抽象成一系列 提供了流量控制和过载保护的能力。详细介绍请参考 * [基于并发请求的过载保护插件](./overload_control_concurrency_limiter)。 - * [基于并发 Fiber 个数的过载保护插件](./overload_control_filter_limiter)。 + * [基于并发 Fiber 个数的过载保护插件](./overload_control_fiber_limiter)。 + * [基于流量控制的过载保护插件](./overload_control_flow_limiter.md) ## 其他特性 diff --git a/docs/zh/server_guide.md b/docs/zh/server_guide.md index ccee2222..4ec799a9 100644 --- a/docs/zh/server_guide.md +++ b/docs/zh/server_guide.md @@ -249,4 +249,5 @@ tRPC-Cpp 是多线程的框架,只支持一种 fork 用法:fork with exec, ### 流控和过载保护 * [基于并发请求的过载保护插件](./overload_control_concurrency_limiter.md) -* [基于并发 Fiber 个数的过载保护插件](./overload_control_filter_limiter) +* [基于并发 Fiber 个数的过载保护插件](./overload_control_fiber_limiter) +* [基于流量控制的过载保护插件](./overload_control_flow_limiter.md) diff --git a/trpc/overload_control/flow_control/flow_controller_server_filter.cc b/trpc/overload_control/flow_control/flow_controller_server_filter.cc index 89445a7f..f342ed64 100644 --- a/trpc/overload_control/flow_control/flow_controller_server_filter.cc +++ b/trpc/overload_control/flow_control/flow_controller_server_filter.cc @@ -35,15 +35,15 @@ int FlowControlServerFilter::Init() { std::vector FlowControlServerFilter::GetFilterPoint() { return { - FilterPoint::SERVER_POST_RECV_MSG, - // This tracking point is not used, but tracking points must be paired, so it is added here. - FilterPoint::SERVER_PRE_SEND_MSG, + FilterPoint::SERVER_PRE_SCHED_RECV_MSG, + // This tracking point is not being used, but tracking points must be paired, so it is added here. + FilterPoint::SERVER_POST_SCHED_RECV_MSG, }; } void FlowControlServerFilter::operator()(FilterStatus& status, FilterPoint point, const ServerContextPtr& context) { switch (point) { - case FilterPoint::SERVER_POST_RECV_MSG: { + case FilterPoint::SERVER_PRE_SCHED_RECV_MSG: { OnRequest(status, context); break; } diff --git a/trpc/overload_control/flow_control/seconds_limiter.cc b/trpc/overload_control/flow_control/seconds_limiter.cc index d7684902..2d1a1484 100644 --- a/trpc/overload_control/flow_control/seconds_limiter.cc +++ b/trpc/overload_control/flow_control/seconds_limiter.cc @@ -57,6 +57,7 @@ bool SecondsLimiter::CheckLimit(const ServerContextPtr& context) { infos.report_name = context->GetFuncName(); infos.tags["current_qps"] = result + 1; infos.tags["max_qps"] = limit_; + infos.tags["window_size"] = window_size_; infos.tags[kOverloadctrlPass] = (ret ? 0 : 1); infos.tags[kOverloadctrlLimited] = (ret ? 1 : 0); Report::GetInstance()->ReportOverloadInfo(infos); diff --git a/trpc/overload_control/flow_control/smooth_limiter.cc b/trpc/overload_control/flow_control/smooth_limiter.cc index f52713cc..a0fbf536 100644 --- a/trpc/overload_control/flow_control/smooth_limiter.cc +++ b/trpc/overload_control/flow_control/smooth_limiter.cc @@ -55,6 +55,7 @@ bool SmoothLimiter::CheckLimit(const ServerContextPtr& context) { infos.tags["active_sum"] = active_sum; infos.tags["hit_num"] = hit_num; infos.tags["max_qps"] = limit_; + infos.tags["window_size"] = window_size_; infos.tags[kOverloadctrlPass] = (ret ? 0 : 1); infos.tags[kOverloadctrlLimited] = (ret ? 1 : 0); Report::GetInstance()->ReportOverloadInfo(infos);