Android性能优化系列-腾讯matrix IO优化之IOCanaryPlugin源码分析-六虎

这是功能优化系列之matrix结构的第2篇文章，我将在功能优化专栏中对matrix apm结构做一个全面的代码剖析，功能优化是Android高级工程师必知必会的点，也是面试过程中的高频题目，对功能优化感兴趣的小伙伴能够去我主页查看一切关于matrix的分享。

前语

matrix 对io的监控包含四个方面

监控在主线程履行 IO 操作的问题
监控缓冲区过小的问题
监控重复读同一文件
监控内存走漏问题

IOCanaryPlugin，内部由IOCanaryCore完结真正的操作。

start办法

依据配置进行hook的装置

//io流hook
if (ioConfig.isDetectFileIOInMainThread() || ioConfig.isDetectFileIOBufferTooSmall() || ioConfig.isDetectFileIORepeatReadSameFile()) {
    IOCanaryJniBridge.install(ioConfig, this);
}
//内存走漏hook
if (ioConfig.isDetectIOClosableLeak()) {
    this.mCloseGuardHooker = new CloseGuardHooker(this);
    this.mCloseGuardHooker.hook();
}

stop办法

取消hook

if (this.mCloseGuardHooker != null) {
    this.mCloseGuardHooker.unHook();
}
IOCanaryJniBridge.uninstall();

IOCanaryJniBridge.install()

底层hook装置包函几个步骤，加载so，设置hook内容，分别对应了下面几个办法

loadJni

System.loadLibrary("io-canary")

履行了System.loadLibrary(“io-canary”)，此时会进入io_canary_jni.cc中的JNI_OnLoad办法，在这个办法中有两项要害操作，1.获取到java层的一些信息，2.设置一个回调接口，用于上传监控信息.

InitJniEnv()

static bool InitJniEnv(JavaVM *vm) {
    ....
    jclass temp_cls = env->FindClass("com/tencent/matrix/iocanary/core/IOCanaryJniBridge");
    ....
}

SetIssuedCallback()

iocanary::IOCanary::Get().SetIssuedCallback(OnIssuePublish)

其间OnIssuePublish是在拿到信息之后将信息组装成java层的目标IOIssue，然后放入List中，经过调用java层IOCanaryJniBridge类的onIssuePublish实现信息的抛出。

com/tencent/matrix/iocanary/core/IOIssue

com/tencent/matrix/iocanary/core/IOCanaryJniBridge

enableDetector

经过传入定义好的type类型到底层，实现此类型的io监控，代码如下

iocanary::IOCanary::Get().RegisterDetector(static_cast<DetectorType>(detector_type));

能够看到终究是往detectors_这个vector集合中存入了对应的Detector，每个Detector都FileIODetector的子类。

FileIOMainThreadDetector
FileIORepeatReadDetector
FileIOSmallBufferDetector

void IOCanary::RegisterDetector(DetectorType type) {
    switch (type) {
        case DetectorType::kDetectorMainThreadIO:
            detectors_.push_back(new FileIOMainThreadDetector());
            break;
        case DetectorType::kDetectorSmallBuffer:
            detectors_.push_back(new FileIOSmallBufferDetector());
            break;
        case DetectorType::kDetectorRepeatRead:
            detectors_.push_back(new FileIORepeatReadDetector());
            break;
        default:
            break;
    }
}

setConfig

给对应的io监控设置监控阈值，存入configs_数组，配置和对应的默认值如下，超过阈值则触发监控

kMainThreadThreshold = 500 毫秒
kSmallBufferThreshold = 4096 kb
kRepeatReadThreshold = 20 次

iocanary::IOCanary::Get().SetConfig(static_cast(key), val);

void IOCanaryEnv::SetConfig(IOCanaryConfigKey key, long val) {
    if (key >= IOCanaryConfigKey::kConfigKeysLen) {
        return;
    }
    configs_[key] = val;
}

dohook

dohook是核心办法，前边配置信息准备好后，这儿开始进行对应办法的hook。被hook的so文件为

const static char* TARGET_MODULES[] = {
    "libopenjdkjvm.so",
    "libjavacore.so",
    "libopenjdk.so"
};

关于GOT hook,能够查看爱奇艺的开源结构XHook，这儿不再描述细节。github.com/iqiyi/xHook…

被hook的办法如下
open、open64、close、android_fdsan_close_with_tag，
假如so是libjavacore.so，会测验hook它内部的这几个办法
read、__read_chk、write、__write_chk

open

当一个文件被翻开时，回调到设置好的办法ProxyOpen中，在这儿会检测是否是主线程操作，如不是则不做处理，如是主线程，则履行DoProxyOpenLogic逻辑。

int ProxyOpen(const char *pathname, int flags, mode_t mode) {
    if(!IsMainThread()) {
        return original_open(pathname, flags, mode);
    }
    int ret = original_open(pathname, flags, mode);
    if (ret != -1) {
        DoProxyOpenLogic(pathname, flags, mode, ret);
    }
    return ret;
}

在DoProxyOpenLogic办法中会获取到当时仓库信息

static void DoProxyOpenLogic(const char *pathname, int flags, mode_t mode, int ret) {
    ....
    //kJavaBridgeClass = com/tencent/matrix/iocanary/core/IOCanaryJniBridge
    //kMethodIDGetJavaContext = getJavaContext() 得到的是一个JavaContext，
    //是一个内部类，这个类上有一个变量stack，在java Context 创立的时候，
    //就会获取到仓库信息，保存在stack变量上
    jobject java_context_obj = env->CallStaticObjectMethod(kJavaBridgeClass, kMethodIDGetJavaContext);
    if (NULL == java_context_obj) {
        return;
    }
    //仓库信息
    jstring j_stack = (jstring) env->GetObjectField(java_context_obj, kFieldIDStack);
    jstring j_thread_name = (jstring) env->GetObjectField(java_context_obj, kFieldIDThreadName);
    //当时线程名
    char* thread_name = jstringToChars(env, j_thread_name);
    char* stack = jstringToChars(env, j_stack);
    JavaContext java_context(GetCurrentThreadId(), thread_name == NULL ? "" : thread_name, stack == NULL ? "" : stack);
    ....
    //pathname是被翻开的文件名，java_context中包含了仓库和线程名
    //flags和mode都是系统open办法调用传过来的值，ret是open履行的结果
    //这儿进入了IOCanary OnOpen办法
    iocanary::IOCanary::Get().OnOpen(pathname, flags, mode, ret, java_context);
    ....
}

open64

同open()

close

检测是主线程，进入IOCanary OnClose办法

int ProxyClose(int fd) {
    if(!IsMainThread()) {
        return original_close(fd);
    }
    int ret = original_close(fd);
    iocanary::IOCanary::Get().OnClose(fd, ret);
    return ret;
}

android_fdsan_close_with_tag

同close()

read

主要是获取到read耗费的时长，然后携带信息进入IOCanary OnRead

ssize_t ProxyRead(int fd, void *buf, size_t size) {
    if(!IsMainThread()) {
        return original_read(fd, buf, size);
    }
    //获取到当时时刻
    int64_t start = GetTickCountMicros();
    //履行原read办法
    size_t ret = original_read(fd, buf, size);
    //记载read时刻距离
    long read_cost_us = GetTickCountMicros() - start;
    //将信息传入IOCanary OnRead
    iocanary::IOCanary::Get().OnRead(fd, buf, size, ret, read_cost_us);
    return ret;
}

__read_chk

同read

write

ssize_t ProxyWrite(int fd, const void *buf, size_t size) {
    if(!IsMainThread()) {
        return original_write(fd, buf, size);
    }
    //获取到当时时刻
    int64_t start = GetTickCountMicros();
    //履行write
    size_t ret = original_write(fd, buf, size);
    //记载时刻距离
    long write_cost_us = GetTickCountMicros() - start;
    //将信息传入IOCanary OnRead
    iocanary::IOCanary::Get().OnWrite(fd, buf, size, ret, write_cost_us);
    return ret;
}

__write_chk

同write

IOCanary

从上边open close read write办法的流向可知，终究都仍是聚集到了IOCanary这个C++类中，进入对应的办法可知，IOCanary内部又调用了IOInfoCollector这个类。
。

OnOpen

void IOCanary::OnOpen(const char *pathname, int flags, mode_t mode,
                      int open_ret, const JavaContext& java_context) {
    collector_.OnOpen(pathname, flags, mode, open_ret, java_context);
}

办法内部逻辑也很明晰，直接将文件名和相关信息组装成info,然后以文件描述符为key,info为value存入了c++的info_map_(一个std::unordered_map)中，信息存起来肯定是要用的，咱们后边会看到。文件翻开之后，下一步便是或读或写，继续去看read办法。

void IOInfoCollector::OnOpen(const char *pathname, int flags, mode_t mode
        , int open_ret, const JavaContext& java_context) {
    if (open_ret == -1) {
        return;
    }
    //open_ret参数指的是open办法调用后的结果，也便是当时被翻开的文件的文件描述符，
    //假如已存在，则回来
    if (info_map_.find(open_ret) != info_map_.end()) {
        return;
    }
    std::shared_ptr<IOInfo> info = std::make_shared<IOInfo>(pathname, java_context);
    info_map_.insert(std::make_pair(open_ret, info));
}

OnRead

void IOCanary::OnRead(int fd, const void *buf, size_t size,
                      ssize_t read_ret, long read_cost) {
    collector_.OnRead(fd, buf, size, read_ret, read_cost);
}

看起来要害内容在CountRWInfo中，从办法名上能够看出，读和写都与此办法有关，所以咱们先不看CountRWInfo办法内容，看完write后再去深入CountRWInfo办法。

void IOInfoCollector::OnRead(int fd, const void *buf, size_t size,
                             ssize_t read_ret, long read_cost) {
    if (read_ret == -1 || read_cost < 0) {
        return;
    }
    if (info_map_.find(fd) == info_map_.end()) {
        return;
    }
    CountRWInfo(fd, FileOpType::kRead, size, read_cost);
}

OnWrite

void IOCanary::OnWrite(int fd, const void *buf, size_t size,
                       ssize_t write_ret, long write_cost) {
    collector_.OnWrite(fd, buf, size, write_ret, write_cost);
}

和read相同，进入了CountRWInfo办法

void IOInfoCollector::OnWrite(int fd, const void *buf, size_t size,
                              ssize_t write_ret, long write_cost) {
    if (write_ret == -1 || write_cost < 0) {
        return;
    }
    if (info_map_.find(fd) == info_map_.end()) {
        return;
    }
    CountRWInfo(fd, FileOpType::kWrite, size, write_cost);
}

CountRWInfo

CountRWInfo将每个文件对应的信息封装到IOInfo这个类中，封装的信息包函：

读(写)次数
文件巨细
读(写)耗费的时长
单次读(写)最大时长
读(写)距离小于8000奇妙的总时长
缓存区巨细
读写类型，读仍是写

在一个文件被读写过程中，这个办法会不断的被调用，并更新对应的信息，读写完结之后，得到终究的信息，履行close办法。

void IOInfoCollector::CountRWInfo(int fd, const FileOpType &fileOpType, long op_size, long rw_cost) {
    if (info_map_.find(fd) == info_map_.end()) {
        return;
    }
    const int64_t now = GetSysTimeMicros();
    //读写次数
    info_map_[fd]->op_cnt_ ++;
    //文件巨细
    info_map_[fd]->op_size_ += op_size;
    //读写耗费的时长
    info_map_[fd]->rw_cost_us_ += rw_cost;
    //单次读写最大时长
    if (rw_cost > info_map_[fd]->max_once_rw_cost_time_s_) {
        info_map_[fd]->max_once_rw_cost_time_s_ = rw_cost;
    }
    //读写距离小于8000奇妙的总时长
    if (info_map_[fd]->last_rw_time_s_ > 0 && (now - info_map_[fd]->last_rw_time_s_) < kContinualThreshold) {
        info_map_[fd]->current_continual_rw_time_s_ += rw_cost;
    } else {
        info_map_[fd]->current_continual_rw_time_s_ = rw_cost;
    }
    if (info_map_[fd]->current_continual_rw_time_s_ > info_map_[fd]->max_continual_rw_cost_time_s_) {
        info_map_[fd]->max_continual_rw_cost_time_s_ = info_map_[fd]->current_continual_rw_time_s_;
    }
    info_map_[fd]->last_rw_time_s_ = now;
    //缓存区巨细
    if (info_map_[fd]->buffer_size_ < op_size) {
        info_map_[fd]->buffer_size_ = op_size;
    }
    //读写类型，读仍是写
    if (info_map_[fd]->op_type_ == FileOpType::kInit) {
        info_map_[fd]->op_type_ = fileOpType;
    }
}

OnClose

void IOCanary::OnClose(int fd, int close_ret) {
    std::shared_ptr<IOInfo> info = collector_.OnClose(fd, close_ret);
    if (info == nullptr) {
        return;
    }
    OfferFileIOInfo(info);
}

close时记载总时长，文件巨细，然后回来，回来后进入OfferFileIOInfo办法

std::shared_ptr<IOInfo> IOInfoCollector::OnClose(int fd, int close_ret) {
    if (info_map_.find(fd) == info_map_.end()) {
        return nullptr;
    }
    //从翻开到封闭的总时长
    info_map_[fd]->total_cost_s_ = GetSysTimeMicros() - info_map_[fd]->start_time_s_;
    //获取到文件巨细
    info_map_[fd]->file_size_ = GetFileSize(info_map_[fd]->path_.c_str());
    std::shared_ptr<IOInfo> info = info_map_[fd];
    //从map中移除
    info_map_.erase(fd);
    //回来信息
    return info;
}

OfferFileIOInfo将info放入队列，并调用notify_one办法告诉顾客消费，这儿用到了生产消费形式，生产者将生产果实放在队列中，顾客从队列取出进行消费，咱们找下顾客在哪。

void IOCanary::OfferFileIOInfo(std::shared_ptr<IOInfo> file_io_info) {
    std::unique_lock<std::mutex> lock(queue_mutex_);
    queue_.push_back(file_io_info);
    queue_cv_.notify_one();
    lock.unlock();
}

能够看到，IOCanary在创立的时候，启动了一个线程

IOCanary::IOCanary() {
    exit_ = false;
    std::thread detect_thread(&IOCanary::Detect, this);
    detect_thread.detach();
}

线程中有一个无限循环，它担任不断的从队列中拿info，假如队列为空则挂起线程等待。

前边咱们看到了拿到一条info之后，将info放入到队列中，然后告诉顾客消费，此时顾客线程会从TakeFileIOInfo办法中被唤醒，并拿到一条info，交给各个detector去检测。

检测完结之后，满意条件的信息会被放入published_issues中，然后issued_callback_将信息回调出去。前边说到有三个detector接下来详细看下他们的内部逻辑。

void IOCanary::Detect() {
    std::vector<Issue> published_issues;
    std::shared_ptr<IOInfo> file_io_info;
    while (true) {
        published_issues.clear();
        int ret = TakeFileIOInfo(file_io_info);
        if (ret != 0) {
            break;
        }
        for (auto detector : detectors_) {
            detector->Detect(env_, *file_io_info, published_issues);
        }
        if (issued_callback_ && !published_issues.empty()) {
            issued_callback_(published_issues);
        }
        file_io_info = nullptr;
    }
}

FileIOMainThreadDetector

检测主线程io

void FileIOMainThreadDetector::Detect(const IOCanaryEnv &env, const IOInfo &file_io_info,
                                      std::vector<Issue>& issues) {
    //有必要是主线程才会履行
    if (GetMainThreadId() == file_io_info.java_context_.thread_id_) {
        int type = 0;
        //单次io时长超过13毫秒，要记载
        //constexpr static const int kPossibleNegativeThreshold = 13*1000;
        if (file_io_info.max_once_rw_cost_time_s_ > IOCanaryEnv::kPossibleNegativeThreshold) {
            type = 1;
        }
        //最大连续读写时长超过env.GetMainThreadThreshold()=500
        if(file_io_info.max_continual_rw_cost_time_s_ > env.GetMainThreadThreshold()) {
            type |= 2;
        }
        if (type != 0) {
            Issue issue(kType, file_io_info);
            issue.repeat_read_cnt_ = type; 
            //存入
            PublishIssue(issue, issues);
        }
    }
}

FileIORepeatReadDetector

监听重复读取同一文件


void FileIORepeatReadDetector::Detect(const IOCanaryEnv &env,
                                      const IOInfo &file_io_info,
                                      std::vector<Issue>& issues) {
    const std::string& path = file_io_info.path_;
    if (observing_map_.find(path) == observing_map_.end()) {
        if (file_io_info.max_continual_rw_cost_time_s_ < env.kPossibleNegativeThreshold) {
            return;
        }
        observing_map_.insert(std::make_pair(path, std::vector<RepeatReadInfo>()));
    }
    std::vector<RepeatReadInfo>& repeat_infos = observing_map_[path];
    if (file_io_info.op_type_ == FileOpType::kWrite) {
        repeat_infos.clear();
        return;
    }
    RepeatReadInfo repeat_read_info(file_io_info.path_, file_io_info.java_context_.stack_, file_io_info.java_context_.thread_id_,
                                  file_io_info.op_size_, file_io_info.file_size_);
    if (repeat_infos.size() == 0) {
        repeat_infos.push_back(repeat_read_info);
        return;
    }
    if((GetTickCount() - repeat_infos[repeat_infos.size() - 1].op_timems) > 17) {   //17ms todo astrozhou add to params
        repeat_infos.clear();
    }
    bool found = false;
    int repeatCnt;
    for (auto& info : repeat_infos) {
        if (info == repeat_read_info) {
            found = true;
            info.IncRepeatReadCount();
            repeatCnt = info.GetRepeatReadCount();
            break;
        }
    }
    if (!found) {
        repeat_infos.push_back(repeat_read_info);
        return;
    }
    if (repeatCnt >= env.GetRepeatReadThreshold()) {
        Issue issue(kType, file_io_info);
        issue.repeat_read_cnt_ = repeatCnt;
        issue.stack = repeat_read_info.GetStack();
        PublishIssue(issue, issues);
    }
}

FileIOSmallBufferDetector

监听缓存区过小

void FileIOSmallBufferDetector::Detect(const IOCanaryEnv &env, const IOInfo &file_io_info,
                                       std::vector<Issue>& issues) {
    if (file_io_info.op_cnt_ > env.kSmallBufferOpTimesThreshold && (file_io_info.op_size_ / file_io_info.op_cnt_) < env.GetSmallBufferThreshold()
            && file_io_info.max_continual_rw_cost_time_s_ >= env.kPossibleNegativeThreshold) {
        PublishIssue(Issue(kType, file_io_info), issues);
    }
}

OnIssuePublish

一切信息都拿到之后就开始要回调了，也就回到了咱们最开始开到的
iocanary::IOCanary::Get().SetIssuedCallback(OnIssuePublish)

void OnIssuePublish(const std::vector<Issue>& published_issues) {
    ....
    //这儿new了一个Java层的List
    jobject j_issues = env->NewObject(kListClass, kMethodIDListConstruct);
    //遍历一切的info，拿到信息，每一条信息创立一个Java层的IOIssue目标，封装到这个目标中
    for (const auto& issue : published_issues) {
        jint type = issue.type_;
        jstring path = env->NewStringUTF(issue.file_io_info_.path_.c_str());
        jlong file_size = issue.file_io_info_.file_size_;
        jint op_cnt = issue.file_io_info_.op_cnt_;
        jlong buffer_size = issue.file_io_info_.buffer_size_;
        jlong op_cost_time = issue.file_io_info_.rw_cost_us_/1000;
        jint op_type = issue.file_io_info_.op_type_;
        jlong op_size = issue.file_io_info_.op_size_;
        jstring thread_name = env->NewStringUTF(issue.file_io_info_.java_context_.thread_name_.c_str());
        jstring stack = env->NewStringUTF(issue.stack.c_str());
        jint repeat_read_cnt = issue.repeat_read_cnt_;
        jobject issue_obj = env->NewObject(kIssueClass, kMethodIDIssueConstruct, type, path, file_size, op_cnt, buffer_size,
                                           op_cost_time, op_type, op_size, thread_name, stack, repeat_read_cnt);
        //讲IOIssue目标add到List中
        env->CallBooleanMethod(j_issues, kMethodIDListAdd, issue_obj);
        ....
    }
    //回调到Java层的IOCanaryJniBridge类中的静态办法onIssuePublish中
    env->CallStaticVoidMethod(kJavaBridgeClass, kMethodIDOnIssuePublish, j_issues);
    ....
}

后边在Java层onIssuePublish中就开始拼接信息转为json打印到控制台或上传服务器，流程至此就算完毕了。

总结

IOCanaryPlugin经过hook底层io办法open、read、write、close来实现对io操作的拦截，所以一切的io操作都会被监控到，这样就能够在每一个io操作的过程中记载操作的信息，并剖析io操作是否超过设定阈值，如满意条件则进行上报。

Android性能优化系列-腾讯matrix IO优化之IOCanaryPlugin源码分析

前语

start办法

stop办法

IOCanaryJniBridge.install()

loadJni

enableDetector

setConfig

dohook

open

open64

close

android_fdsan_close_with_tag

read

__read_chk

write

__write_chk

IOCanary

OnOpen

OnRead

OnWrite

CountRWInfo

OnClose

FileIOMainThreadDetector

FileIORepeatReadDetector

FileIOSmallBufferDetector

OnIssuePublish

总结

作者信息

推广

Android性能优化系列-腾讯matrix IO优化之IOCanaryPlugin源码分析

前语

start办法

stop办法

IOCanaryJniBridge.install()

loadJni

enableDetector

setConfig

dohook

open

open64

close

android_fdsan_close_with_tag

read

__read_chk

write

__write_chk

IOCanary

OnOpen

OnRead

OnWrite

CountRWInfo

OnClose

FileIOMainThreadDetector

FileIORepeatReadDetector

FileIOSmallBufferDetector

OnIssuePublish

总结

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