年初分享过[聊聊 Go failpoint 使用] ,感兴趣的可以看看看这篇文章
Failpoints
是一个允许在运行时注入错误或是其它行为的工具,主要用于测试目的,包括 ut 单测,集成压测等等。测试的内容包括状态机错误,磁盘错误,网络 IO 延迟
可以注入的行为有:panic
, early returns
, sleeping
等等,注入的行为可以通过环境变量或代码进行控制。一般推荐用 http 或集成公司的配置平台,触发规则可以是次数,概率或是两种的结合
首先配置依赖,Cargo.toml
[dependencies]
fail = "0.4"
我们依赖 0.4 版本
use fail::{fail_point, FailScenario};
fn do_fallible_work() {
fail_point!("read-dir");
println!("mock working now");
}
fn main() {
let scenario = FailScenario::setup();
do_fallible_work();
scenario.teardown();
println!("done");
}
do_fallible_work
函数只做两件事情,执行 read-dir 注入点,打印消息用于模拟函数处理请求
$ FAILPOINTS=read-dir="panic" cargo run
mock working now
done
通过环境变量注入 panic 语句,条件编译默认没有开启,所以正常输出
$ FAILPOINTS=read-dir="panic" cargo run --features fail/failpoints
mock working now
thread 'main' panicked at 'failpoint read-dir panic', /Users/zerun.dong/.cargo/registry/src/github.com-1ecc6299db9ec823/fail-0.4.0/src/lib.rs:488:25
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
cargo 指定 --features fail/failpoints
, 发生 Panic 符合预期
FAILPOINTS=read-dir="sleep(2000)" cargo run --features fail/failpoints
当然我们也可以指定其它行为,比如 sleep(2000)
休眠 2 秒
use fail::{fail_point, FailScenario};
use std::io;
fn do_fallible_work() -> io::Result<()>{
println!("mock working now");
fail_point!("read-dir", |_| {
Err(io::Error::new(io::ErrorKind::PermissionDenied, "error"))
});
Ok(())
}
fn main() -> io::Result<()> {
let scenario = FailScenario::setup();
do_fallible_work()?;
do_fallible_work()?;
scenario.teardown();
println!("done");
Ok(())
}
这是测试提前返回 early return 的案例,需要使用闭包来封装 error
$ FAILPOINTS=read-dir=return cargo run --features fail/failpoints
mock working now
Error: Custom { kind: PermissionDenied, error: "error" }
上面是普通用法,也可以指定多个 action
$ FAILPOINTS=read-dir="1*sleep(2000)->return" cargo run --features fail/failpoints
mock working now
mock working now
Error: Custom { kind: PermissionDenied, error: "error" }
"1*sleep(2000)->return"
表示第一次休眠 2 秒,然后第二次时提前返回。关于更多高级用法,请参考官网 https://docs.rs/fail
最重要的要求是:集成 Failpoint
的代码,在线上正式环境运行时,要做到零性能消耗
func test() {
failpoint.Inject("testValue", func(v failpoint.Value) {
fmt.Println(v)
})
}
这是 go 测试代码,failpoint.Inject
是 marker
函数,参数是名称和闭包
// failpoint.Inject("fail-point-name", func(_ failpoint.Value) (...){}
func Inject(fpname string, fpbody interface{}) {}
由于 Inject
是空函数体,编译时会被优化掉,所以运行时零性能消耗。当线下测试时,需要执行 failpoint-ctl
将所有 marker 函数转化成注入函数
func test() {
if v, _err_ := failpoint.Eval(_curpkg_("testValue")); _err_ == nil {
fmt.Println(v)
}
}
上面是转换后的代码,原理不难,解析 AST 替换语法树。那么 rust 如何实现呢?答案是 macro 宏 + 条件编译
/// Define a fail point (disabled, see `failpoints` feature).
#[macro_export]
#[cfg(not(feature = "failpoints"))]
macro_rules! fail_point {
($name:expr, $e:expr) => {{}};
($name:expr) => {{}};
($name:expr, $cond:expr, $e:expr) => {{}};
}
当 cargo build 编译时未指定 failpints
feature, fail_point
宏对应空实现
#[cfg(feature = "failpoints")]
macro_rules! fail_point {
($name:expr) => {{
$crate::eval($name, |_| {
panic!("Return is not supported for the fail point \"{}\"", $name);
});
}};
($name:expr, $e:expr) => {{
if let Some(res) = $crate::eval($name, $e) {
return res;
}
}};
($name:expr, $cond:expr, $e:expr) => {{
if $cond {
fail_point!($name, $e);
}
}};
}
指定 feature 时,对应上面的宏实现,编译期展开成相应的逻辑代码。fail_point
宏有三种形式,模式匹配到不同的参数表达式 (designators) 对应不同代码块
/// Registry with failpoints configuration.
type Registry = HashMap<String, Arc<FailPoint>>;
#[derive(Debug, Default)]
struct FailPointRegistry {
// TODO: remove rwlock or store *mut FailPoint
registry: RwLock<Registry>,
}
lazy_static::lazy_static! {
static ref REGISTRY: FailPointRegistry = FailPointRegistry::default();
static ref SCENARIO: Mutex<&'static FailPointRegistry> = Mutex::new(®ISTRY);
}
注册中心 Registry
是 HashMap 类型,key 是上面测试例子的 name
, value 是 Arc<Failpoint>
类型,[Arc 用于并发环境下共享所有权]
struct FailPoint {
pause: Mutex<bool>,
pause_notifier: Condvar,
actions: RwLock<Vec<Action>>,
actions_str: RwLock<String>,
}
pause
表示是否暂停,pause_notifier
用于暂停通知,actions
是一个数组,因为一个 fail_point 注入可以有多个动作,actions_str
是表示任务的字符串,通过 from_str
转化成 action
结构体
FailScenario::setup()
通过获取 FAILPOINTS
环境变量来初始化注入动作,暂时不支持通过 http 方式
解析后通过 set
函数将多个注入动作解析,注册到上文提到的 Registry
fn set(
registry: &mut HashMap<String, Arc<FailPoint>>,
name: String,
actions: &str,
) -> Result<(), String> {
let actions_str = actions;
// `actions` are in the format of `failpoint[->failpoint...]`.
let actions = actions
.split("->")
.map(Action::from_str)
.collect::<Result<_, _>>()?;
// Please note that we can't figure out whether there is a failpoint named `name`,
// so we may insert a failpoint that doesn't exist at all.
let p = registry
.entry(name)
.or_insert_with(|| Arc::new(FailPoint::new()));
p.set_actions(actions_str, actions);
Ok(())
}
这里面用 Action::from_str
将字符串解析成 Action
#[derive(Clone, Debug, PartialEq)]
enum Task {
/// Do nothing.
Off,
/// Return the value.
Return(Option<String>),
/// Sleep for some milliseconds.
Sleep(u64),
/// Panic with the message.
Panic(Option<String>),
/// Print the message.
Print(Option<String>),
/// Sleep until other action is set.
Pause,
/// Yield the CPU.
Yield,
/// Busy waiting for some milliseconds.
Delay(u64),
/// Call callback function.
Callback(SyncCallback),
}
#[derive(Debug)]
struct Action {
task: Task,
freq: f32,
count: Option<AtomicUsize>,
}
Action
类型都不一样,freq
控制频率,count
控制触发次数
大前提肯定是条件编译打开了 failpoint, 直接看 macro 实现
pub fn eval<R, F: FnOnce(Option<String>) -> R>(name: &str, f: F) -> Option<R> {
let p = {
let registry = REGISTRY.registry.read().unwrap();
match registry.get(name) {
None => return None,
Some(p) => p.clone(),
}
};
p.eval(name).map(f)
}
逻辑比较简单,从 Registry
注册中心 map 找到对应 failpoint
, 然后调用 failpoint.eval
函数,并且针对所有返回值执行闭包 f (如果有值)
#[cfg_attr(feature = "cargo-clippy", allow(clippy::option_option))]
fn eval(&self, name: &str) -> Option<Option<String>> {
let task = {
let actions = self.actions.read().unwrap();
match actions.iter().filter_map(Action::get_task).next() {
Some(Task::Pause) => {
let mut guard = self.pause.lock().unwrap();
*guard = true;
loop {
guard = self.pause_notifier.wait(guard).unwrap();
if !*guard {
break;
}
}
return None;
}
Some(t) => t,
None => return None,
}
};
match task {
Task::Off => {}
Task::Return(s) => return Some(s),
Task::Sleep(t) => thread::sleep(Duration::from_millis(t)),
Task::Panic(msg) => match msg {
Some(ref msg) => panic!("{}", msg),
None => panic!("failpoint {} panic", name),
},
Task::Print(msg) => match msg {
Some(ref msg) => log::info!("{}", msg),
None => log::info!("failpoint {} executed.", name),
},
Task::Pause => unreachable!(),
Task::Yield => thread::yield_now(),
Task::Delay(t) => {
let timer = Instant::now();
let timeout = Duration::from_millis(t);
while timer.elapsed() < timeout {}
}
Task::Callback(f) => {
f.run();
}
}
None
}
eval
函数不难,首先调用 get_task
获取要执行的 Action
, 这里 Pause
动作单独处理,其它的通过 match 模式匹配。同时也能看到,如果 Return 不指定闭包 f, 那么返回值是 Some(""), 触发 macro 的默认 panic 闭包
fn get_task(&self) -> Option<Task> {
use rand::Rng;
if let Some(ref cnt) = self.count {
let c = cnt.load(Ordering::Acquire);
if c == 0 {
return None;
}
}
if self.freq < 1f32 && !rand::thread_rng().gen_bool(f64::from(self.freq)) {
return None;
}
if let Some(ref ref_cnt) = self.count {
let mut cnt = ref_cnt.load(Ordering::Acquire);
loop {
if cnt == 0 {
return None;
}
let new_cnt = cnt - 1;
match ref_cnt.compare_exchange_weak(
cnt,
new_cnt,
Ordering::AcqRel,
Ordering::Acquire,
) {
Ok(_) => break,
Err(c) => cnt = c,
}
}
}
Some(self.task.clone())
}
get_task
先判断执行次数,如果为 0 返回空。然后判断频率,如果没有触发返回空,最后再判断一次计数,并 cas 更新。这里 count
计数字段类型是 Option<AtomicUsize>
, 如果不指定次数默认无限制
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