I have an existing debouncer utility using DispatchQueue. It accepts a closure and executes it before the time threshold is met. It can be used like this:
let limiter = Debouncer(limit: 5)
var value = ""
func sendToServer() {
limiter.execute {
print("\(Date.now.timeIntervalSince1970): Fire! \(value)")
}
}
value.append("h")
sendToServer() // Waits until 5 seconds
value.append("e")
sendToServer() // Waits until 5 seconds
value.append("l")
sendToServer() // Waits until 5 seconds
value.append("l")
sendToServer() // Waits until 5 seconds
value.append("o")
sendToServer() // Waits until 5 seconds
print("\(Date.now.timeIntervalSince1970): Last operation called")
// 1635691696.482115: Last operation called
// 1635691701.859087: Fire! hello
Notice it is not calling Fire! multiple times, but just 5 seconds after the last time with the value from the last task. The Debouncer instance is configured to hold the last task in queue for 5 seconds no matter how many times it is called. The closure is passed into the execute(block:) method:
final class Debouncer {
private let limit: TimeInterval
private let queue: DispatchQueue
private var workItem: DispatchWorkItem?
private let syncQueue = DispatchQueue(label: "Debouncer", attributes: [])
init(limit: TimeInterval, queue: DispatchQueue = .main) {
self.limit = limit
self.queue = queue
}
#objc func execute(block: #escaping () -> Void) {
syncQueue.async { [weak self] in
if let workItem = self?.workItem {
workItem.cancel()
self?.workItem = nil
}
guard let queue = self?.queue, let limit = self?.limit else { return }
let workItem = DispatchWorkItem(block: block)
queue.asyncAfter(deadline: .now() + limit, execute: workItem)
self?.workItem = workItem
}
}
}
How can I convert this into a concurrent operation so it can be called like below:
let limit = Debouncer(limit: 5)
func sendToServer() {
await limiter.waitUntilFinished
print("\(Date.now.timeIntervalSince1970): Fire! \(value)")
}
sendToServer()
sendToServer()
sendToServer()
However, this wouldn't debounce the tasks but suspend them until the next one gets called. Instead it should cancel the previous task and hold the current task until the debounce time. Can this be done with Swift Concurrency or is there a better approach to do this?
Tasks have the ability to use isCancelled or checkCancellation, but for the sake of a debounce routine, where you want to wait for a period of time, you might just use the throwing rendition of Task.sleep(nanoseconds:), whose documentation says:
If the task is canceled before the time ends, this function throws CancellationError.
Thus, this effectively debounces for 2 seconds.
var task: Task<(), Never>?
func debounced(_ string: String) {
task?.cancel()
task = Task {
do {
try await Task.sleep(nanoseconds: 2_000_000_000)
logger.log("result \(string)")
} catch {
logger.log("canceled \(string)")
}
}
}
Note, Apple’s swift-async-algorithms has a debounce for asynchronous sequences.
Based on #Rob's great answer, here's a sample using an actor and Task:
actor Limiter {
enum Policy {
case throttle
case debounce
}
private let policy: Policy
private let duration: TimeInterval
private var task: Task<Void, Never>?
init(policy: Policy, duration: TimeInterval) {
self.policy = policy
self.duration = duration
}
nonisolated func callAsFunction(task: #escaping () async -> Void) {
Task {
switch policy {
case .throttle:
await throttle(task: task)
case .debounce:
await debounce(task: task)
}
}
}
private func throttle(task: #escaping () async -> Void) {
guard self.task?.isCancelled ?? true else { return }
Task {
await task()
}
self.task = Task {
try? await sleep()
self.task?.cancel()
self.task = nil
}
}
private func debounce(task: #escaping () async -> Void) {
self.task?.cancel()
self.task = Task {
do {
try await sleep()
guard !Task.isCancelled else { return }
await task()
} catch {
return
}
}
}
private func sleep() async throws {
try await Task.sleep(nanoseconds: UInt64(duration * 1_000_000_000))
}
}
The tests are inconsistent in passing so I think my assumption on the order of the tasks firing is incorrect, but the sample is a good start I think:
final class LimiterTests: XCTestCase {
func testThrottler() async throws {
// Given
let promise = expectation(description: "Ensure first task fired")
let throttler = Limiter(policy: .throttle, duration: 1)
var value = ""
var fulfillmentCount = 0
promise.expectedFulfillmentCount = 2
func sendToServer(_ input: String) {
throttler {
value += input
// Then
switch fulfillmentCount {
case 0:
XCTAssertEqual(value, "h")
case 1:
XCTAssertEqual(value, "hwor")
default:
XCTFail()
}
promise.fulfill()
fulfillmentCount += 1
}
}
// When
sendToServer("h")
sendToServer("e")
sendToServer("l")
sendToServer("l")
sendToServer("o")
await sleep(2)
sendToServer("wor")
sendToServer("ld")
wait(for: [promise], timeout: 10)
}
func testDebouncer() async throws {
// Given
let promise = expectation(description: "Ensure last task fired")
let limiter = Limiter(policy: .debounce, duration: 1)
var value = ""
var fulfillmentCount = 0
promise.expectedFulfillmentCount = 2
func sendToServer(_ input: String) {
limiter {
value += input
// Then
switch fulfillmentCount {
case 0:
XCTAssertEqual(value, "o")
case 1:
XCTAssertEqual(value, "old")
default:
XCTFail()
}
promise.fulfill()
fulfillmentCount += 1
}
}
// When
sendToServer("h")
sendToServer("e")
sendToServer("l")
sendToServer("l")
sendToServer("o")
await sleep(2)
sendToServer("wor")
sendToServer("ld")
wait(for: [promise], timeout: 10)
}
func testThrottler2() async throws {
// Given
let promise = expectation(description: "Ensure throttle before duration")
let throttler = Limiter(policy: .throttle, duration: 1)
var end = Date.now + 1
promise.expectedFulfillmentCount = 2
func test() {
// Then
XCTAssertLessThan(.now, end)
promise.fulfill()
}
// When
throttler(task: test)
throttler(task: test)
throttler(task: test)
throttler(task: test)
throttler(task: test)
await sleep(2)
end = .now + 1
throttler(task: test)
throttler(task: test)
throttler(task: test)
await sleep(2)
wait(for: [promise], timeout: 10)
}
func testDebouncer2() async throws {
// Given
let promise = expectation(description: "Ensure debounce after duration")
let debouncer = Limiter(policy: .debounce, duration: 1)
var end = Date.now + 1
promise.expectedFulfillmentCount = 2
func test() {
// Then
XCTAssertGreaterThan(.now, end)
promise.fulfill()
}
// When
debouncer(task: test)
debouncer(task: test)
debouncer(task: test)
debouncer(task: test)
debouncer(task: test)
await sleep(2)
end = .now + 1
debouncer(task: test)
debouncer(task: test)
debouncer(task: test)
await sleep(2)
wait(for: [promise], timeout: 10)
}
private func sleep(_ duration: TimeInterval) async {
await Task.sleep(UInt64(duration * 1_000_000_000))
}
}
Related
I have an actor that is processing values and is then publishing the values with a Combine Publisher.
I have problems understanding actors, I thought when using actors in an async context, it would automatically be serialised. However, the numbers get processed in different orders and not in the expected order (see class tests for comparison).
I understand that if I would wrap Task around the for loop that then this would be returned serialised, but my understanding is, that I could call a function of an actor and this would then be automatically serialised.
How can I make my actor thread safe so it publishes the values in the expected order even if it is called from a different thread?
import XCTest
import Combine
import CryptoKit
actor AddNumbersActor {
private let _numberPublisher: PassthroughSubject<(Int,String), Never> = .init()
nonisolated lazy var numberPublisher = _numberPublisher.eraseToAnyPublisher()
func process(_ number: Int) {
let string = SHA512.hash(data: Data(String(number).utf8))
.description
_numberPublisher.send((number, string))
}
}
class AddNumbersClass {
private let _numberPublisher: PassthroughSubject<(Int,String), Never> = .init()
lazy var numberPublisher = _numberPublisher.eraseToAnyPublisher()
func process(_ number: Int) {
let string = SHA512.hash(data: Data(String(number).utf8))
.description
_numberPublisher.send((number, string))
}
}
final class TestActorWithPublisher: XCTestCase {
var subscription: AnyCancellable?
override func tearDownWithError() throws {
subscription = nil
}
func testActor() throws {
let addNumbers = AddNumbersActor()
var numbersResults = [(int: Int, string: String)]()
let expectation = expectation(description: "numberOfExpectedResults")
let numberCount = 1000
subscription = addNumbers.numberPublisher
.sink { results in
print(results)
numbersResults.append(results)
if numberCount == numbersResults.count {
expectation.fulfill()
}
}
for number in 1...numberCount {
Task {
await addNumbers.process(number)
}
}
wait(for: [expectation], timeout: 5)
print(numbersResults.count)
XCTAssertEqual(numbersResults[10].0, 11)
XCTAssertEqual(numbersResults[100].0, 101)
XCTAssertEqual(numbersResults[500].0, 501)
}
func testClass() throws {
let addNumbers = AddNumbersClass()
var numbersResults = [(int: Int, string: String)]()
let expectation = expectation(description: "numberOfExpectedResults")
let numberCount = 1000
subscription = addNumbers.numberPublisher
.sink { results in
print(results)
numbersResults.append(results)
if numberCount == numbersResults.count {
expectation.fulfill()
}
}
for number in 1...numberCount {
addNumbers.process(number)
}
wait(for: [expectation], timeout: 5)
print(numbersResults.count)
XCTAssertEqual(numbersResults[10].0, 11)
XCTAssertEqual(numbersResults[100].0, 101)
XCTAssertEqual(numbersResults[500].0, 501)
}
}
``
Using actor does indeed serialize access.
The issue you're running into is that the tests aren't testing whether calls to process() are serialized, they are testing the execution order of the calls. And the execution order of the Task calls is not guaranteed.
Try changing your AddNumbers objects so that instead of the output order reflecting the order in which the calls were made, they will succeed if calls are serialized but will fail if concurrent calls are made. You can do this by keeping a count variable, incrementing it, sleeping a bit, then publishing the count. Concurrent calls will fail, since count will be incremented multiple times before its returned.
If you make that change, the test using an Actor will pass. The test using a class will fail if it calls process() concurrently:
DispatchQueue.global(qos: .default).async {
addNumbers.process()
}
It will also help to understand that Task's scheduling depends on a bunch of stuff. GCD will spin up tons of threads, whereas Swift concurrency will only use 1 worker thread per available core (I think!). So in some execution environments, just wrapping your work in Task { } might be enough to serialize it for you. I've been finding that iOS simulators act as if they have a single core, so task execution ends up being serialized. Also, otherwise unsafe code will work if you ensure the task runs on the main actor, since it guarantees serial execution:
Task { #MainActor in
// ...
}
Here are modified tests showing all this:
class TestActorWithPublisher: XCTestCase {
actor AddNumbersActor {
private let _numberPublisher: PassthroughSubject<Int, Never> = .init()
nonisolated lazy var numberPublisher = _numberPublisher.eraseToAnyPublisher()
var count = 0
func process() {
// Increment the count here
count += 1
// Wait a bit...
Thread.sleep(forTimeInterval: TimeInterval.random(in: 0...0.010))
// Send it back. If other calls to process() were made concurrently, count may have been incremented again before being sent:
_numberPublisher.send(count)
}
}
class AddNumbersClass {
private let _numberPublisher: PassthroughSubject<Int, Never> = .init()
lazy var numberPublisher = _numberPublisher.eraseToAnyPublisher()
var count = 0
func process() {
count += 1
Thread.sleep(forTimeInterval: TimeInterval.random(in: 0...0.010))
_numberPublisher.send(count)
}
}
var subscription: AnyCancellable?
override func tearDownWithError() throws {
subscription = nil
}
func testActor() throws {
let addNumbers = AddNumbersActor()
var numbersResults = [Int]()
let expectation = expectation(description: "numberOfExpectedResults")
let numberCount = 1000
subscription = addNumbers.numberPublisher
.sink { results in
numbersResults.append(results)
if numberCount == numbersResults.count {
expectation.fulfill()
}
}
for _ in 1...numberCount {
Task.detached(priority: .high) {
await addNumbers.process()
}
}
wait(for: [expectation], timeout: 10)
XCTAssertEqual(numbersResults, Array(1...numberCount))
}
func testClass() throws {
let addNumbers = AddNumbersClass()
var numbersResults = [Int]()
let expectation = expectation(description: "numberOfExpectedResults")
let numberCount = 1000
subscription = addNumbers.numberPublisher
.sink { results in
numbersResults.append(results)
if numberCount == numbersResults.count {
expectation.fulfill()
}
}
for _ in 1...numberCount {
DispatchQueue.global(qos: .default).async {
addNumbers.process()
}
}
wait(for: [expectation], timeout: 5)
XCTAssertEqual(numbersResults, Array(1...numberCount))
}
}
With Swift concurrency, is it possible to have something almost like an 'unnamed' async let?
Here is an example. You have the following actor:
actor MyActor {
private var foo: Int = 0
private var bar: Int = 0
func setFoo(to value: Int) async {
foo = value
}
func setBar(to value: Int) async {
bar = value
}
func printResult() {
print("foo =", foo)
print("bar =", bar)
}
}
Now I want to set foo and bar using the given methods. Simple usage would look like the following:
let myActor = MyActor()
await myActor.setFoo(to: 5)
await myActor.setBar(to: 10)
await myActor.printResult()
However this code is sequentially run. For all intents and purposes, assume setFoo(to:) and setBar(to:) may be a long running task. You can also assume the methods are mutually exclusive (don't share variables & won't affect each other).
To make this code current, async let can be used. However, this just starts the tasks until they are awaited later on. In my example you'll notice I don't need the return value from these methods. All I need is that before printResult() is called, the previous tasks have completed.
I could come up with the following:
let myActor = MyActor()
async let tempFoo: Void = myActor.setFoo(to: 5)
async let tempBar: Void = myActor.setBar(to: 10)
let _ = await [tempFoo, tempBar]
await myActor.printResult()
Explicitly creating these tasks and then awaiting an array of them seems incorrect. Is this really the best way?
This can be achieved with a task group using withTaskGroup(of:returning:body:). The method calls are individual tasks, and then we await waitForAll() which continues when all tasks have completed.
Code:
await withTaskGroup(of: Void.self) { group in
let myActor = MyActor()
group.addTask {
await myActor.setFoo(to: 5)
}
group.addTask {
await myActor.setBar(to: 10)
}
await group.waitForAll()
await myActor.printResult()
}
I made your actor a class to allow concurrent execution of the two methods.
import Foundation
final class Jeep {
private var foo: Int = 0
private var bar: Int = 0
func setFoo(to value: Int) {
print("begin foo")
foo = value
sleep(1)
print("end foo \(value)")
}
func setBar(to value: Int) {
print("begin bar")
bar = value
sleep(2)
print("end bar \(bar)")
}
func printResult() {
print("printResult foo:\(foo), bar:\(bar)")
}
}
let jeep = Jeep()
let blocks = [
{ jeep.setFoo(to: 1) },
{ jeep.setBar(to: 2) },
]
// ...WORK
RunLoop.current.run(mode: RunLoop.Mode.default, before: NSDate(timeIntervalSinceNow: 5) as Date)
Replace WORK with one of these:
// no concurrency, ordered execution
for block in blocks {
block()
}
jeep.printResult()
// concurrency, unordered execution, tasks created upfront programmatically
Task {
async let foo: Void = blocks[0]()
async let bar: Void = blocks[1]()
await [foo, bar]
jeep.printResult()
}
// concurrency, unordered execution, tasks created upfront, but started by the system (I think)
Task {
await withTaskGroup(of: Void.self) { group in
for block in blocks {
group.addTask { block() }
}
}
// when the initialization closure exits, all child tasks are awaited implicitly
jeep.printResult()
}
// concurrency, unordered execution, awaited in order
Task {
let tasks = blocks.map { block in
Task { block() }
}
for task in tasks {
await task.value
}
jeep.printResult()
}
// tasks created upfront, all tasks start concurrently, produce result as soon as they finish
let stream = AsyncStream<Void> { continuation in
Task {
let tasks = blocks.map { block in
Task { block() }
}
for task in tasks {
continuation.yield(await task.value)
}
continuation.finish()
}
}
Task {
// now waiting for all values, bad use of a stream, I know
for await value in stream {
print(value as Any)
}
jeep.printResult()
}
I I have a loop with a firestore query in it that is repeated 10 times. I need to call the (completion: block) after all the 10 queries completed; Here I have my code so that it performs the (completion: block) per query but this would be too heavy on the server and the user's phone. How can I change below to accomplish what I just described?
static func getSearchedProducts(fetchingNumberToStart: Int, sortedProducts: [Int : [String : Int]], handler: #escaping (_ products: [Product], _ lastFetchedNumber: Int?) -> Void) {
var lastFetchedNumber:Int = 0
var searchedProducts:[Product] = []
let db = Firestore.firestore()
let block : FIRQuerySnapshotBlock = ({ (snap, error) in
guard error == nil, let snapshot = snap else {
debugPrint(error?.localizedDescription)
return
}
var products = snapshot.documents.map { Product(data: $0.data()) }
if !UserService.current.isGuest {
db.collection(DatabaseRef.Users).document(Auth.auth().currentUser?.uid ?? "").collection(DatabaseRef.Cart).getDocuments { (cartSnapshot, error) in
guard error == nil, let cartSnapshot = cartSnapshot else {
return
}
cartSnapshot.documents.forEach { document in
var product = Product(data: document.data())
guard let index = products.firstIndex(of: product) else { return }
let cartCount: Int = document.exists ? document.get(DatabaseRef.cartCount) as? Int ?? 0 : 0
product.cartCount = cartCount
products[index] = product
}
handler(products, lastFetchedNumber)
}
}
else {
handler(products, lastFetchedNumber)
}
})
if lastFetchedNumber == fetchingNumberToStart {
for _ in 0 ..< 10 {
//change the fetching number each time in the loop
lastFetchedNumber = lastFetchedNumber + 1
let productId = sortedProducts[lastFetchedNumber]?.keys.first ?? ""
if productId != "" {
db.collection(DatabaseRef.products).whereField(DatabaseRef.id, isEqualTo: productId).getDocuments(completion: block)
}
}
}
}
as you can see at the very end I am looping 10 times for this query because of for _ in 0 ..< 10 :
if productId != "" {
db.collection(DatabaseRef.products).whereField(DatabaseRef.id, isEqualTo: productId).getDocuments(completion: block)
}
So I need to make the completion: block handler to be called only once instead of 10 times here.
Use a DispatchGroup. You can enter the dispatch group each time you call the async code and then leave each time it's done. Then when everything is finished it will call the notify block and you can call your handler. Here's a quick example of what that would look like:
let dispatchGroup = DispatchGroup()
let array = []
for i in array {
dispatchGroup.enter()
somethingAsync() {
dispatchGroup.leave()
}
}
dispatchGroup.notify(queue: .main) {
handler()
}
I have a, b, c, d, e time consuming task functions with completion handler.
There are constraints between them:
Both b & c wait for a to finish
The last task e waits for b & c & d to finish
if there is no task d, I could write code in swift like this (not tested yet)
let group = DispatchGroup()
group.enter()
a() { group.leave() }
group.wait()
group.enter()
b() { group.leave() }
group.enter()
c() { group.leave() }
group.notify(queue: .main) {
e()
}
How to add task d without waiting a to complete?
Edited on 4/30 10:00 (+8)
Code Different said
the easiest approach is to make the download function synchronous and add a warning to its documentation that it should never be called from the main thread.
So I made a version based on it. This way cannot handle the return values from concurrent calls. But it looks really like async/await. So I'm satisfied now. Thank you guys.
the async/await like part is
myQueue.async {
downloadSync("A")
downloadSync("B", isConcurrent: true)
downloadSync("C", isConcurrent: true)
downloadSync("D", 4, isConcurrent: true)
waitConcurrentJobs()
downloadSync("E")
}
And the full code is below.
let myGroup = DispatchGroup()
let myQueue = DispatchQueue(label: "for Sync/Blocking version of async functions")
func waitConcurrentJobs() {
myGroup.wait()
}
// original function (async version, no source code)
func download(_ something: String, _ seconds: UInt32 = 1, completionHandler: #escaping ()->Void = {}) {
print("Downloading \(something)")
DispatchQueue.global().async {
sleep(seconds)
print("\(something) is downloaded")
completionHandler()
}
}
// wrapped function (synced version)
// Warning:
// It blocks current thead !!!
// Do not call it on main thread
func downloadSync(
_ something: String,
_ seconds: UInt32 = 1,
isConcurrent: Bool = false
){
myGroup.enter()
download(something, seconds) { myGroup.leave() }
if !isConcurrent {
myGroup.wait()
}
}
// Now it really looks like ES8 async/await
myQueue.async {
downloadSync("A")
downloadSync("B", isConcurrent: true)
downloadSync("C", isConcurrent: true)
downloadSync("D", 4, isConcurrent: true)
waitConcurrentJobs()
downloadSync("E")
}
results
Edit: the easiest approach is to make the download function synchronous and add a warning to its documentation that it should never be called from the main thread. The pyramid of doom for async function is the reason why coroutines were proposed, by no other than Chris Lattner, Swift's creator. As of April 2018, it's not yet a formal proposal waiting for review so chances are that you won't see it in Swift 5.
An synchronous download function:
// Never call this from main thread
func download(_ something: String, _ seconds: UInt32 = 1, completionHandler: #escaping ()->Void = {}) {
let group = DispatchGroup()
print("Downloading \(something)")
group.enter()
DispatchQueue.global().async {
sleep(seconds)
print("\(something) is downloaded")
completionHandler()
group.leave()
}
group.wait()
}
And NSOperation / NSOperationQueue setup:
let opA = BlockOperation() {
self.download("A")
}
let opB = BlockOperation() {
self.download("B")
}
let opC = BlockOperation() {
self.download("C")
}
let opD = BlockOperation() {
self.download("D", 4)
}
let opE = BlockOperation() {
self.download("E")
}
opB.addDependency(opA)
opC.addDependency(opA)
opE.addDependency(opB)
opE.addDependency(opC)
opE.addDependency(opD)
let operationQueue = OperationQueue()
operationQueue.addOperations([opA, opB, opC, opD, opE], waitUntilFinished: false)
Your original effort seems very close to me. You could make a minor adjustment: make B, C, and D be the group that finishes to trigger E.
A could be another group, but since it's one task, I don't see the point. Trigger B and C when it's done.
Note that unlike some of the example code in your question and other answers, in the code below, D and A can both start right away and run in parallel.
let q = DispatchQueue(label: "my-queue", attributes: .concurrent)
let g = DispatchGroup()
func taskA() { print("A") }
func taskB() { print("B"); g.leave() }
func taskC() { print("C"); g.leave() }
func taskD() { print("D"); g.leave() }
func taskE() { print("E") }
g.enter()
g.enter()
g.enter()
q.async {
taskA()
q.async(execute: taskB)
q.async(execute: taskC)
}
q.async(execute: taskD)
g.notify(queue: q, execute: taskE)
You can use this framework to implement async/await pattern - https://github.com/belozierov/SwiftCoroutine
When you call await it doesn’t block the thread but only suspends coroutine, so you can use it in the main thread as well.
func awaitAPICall(_ url: URL) throws -> String? {
let future = URLSession.shared.dataTaskFuture(for: url)
let data = try future.await().data
return String(data: data, encoding: .utf8)
}
func load(url: URL) {
DispatchQueue.main.startCoroutine {
let result1 = try self.awaitAPICall(url)
let result2 = try self.awaitAPICall2(result1)
let result3 = try self.awaitAPICall3(result2)
print(result3)
}
}
I would like to show an alternative solution using Scala like futures:
let result = funcA().flatMap { resultA in
return [funcB(param: resultA.0),
funcC(param: resultA.1),
funcD()]
.fold(initial: [String]()) { (combined, element) in
return combined + [element]
}
}.flatMap { result in
return funcE(param: result)
}.map { result in
print(result)
}
That's it basically. It handles errors (implicitly) and is thread-safe. No Operation subclasses ;)
Note, that funcD will be called only when A completes successfully. Since funcA() can fail it would make no sense to call it. But the code can be easily adapted to make this possible as well, iff required.
Please compare this to function foo() from my other solution which uses Dispatch Groups and Dispatch Queues.
Below an example of the definitions of the async functions which each passing their result to the next one:
func funcA() -> Future<(String, String)> {
print("Start A")
let promise = Promise<(String, String)>()
DispatchQueue.global().asyncAfter(deadline: .now() + 3) {
print("Complete A")
promise.complete(("A1", "A2"))
}
return promise.future
}
func funcB(param: String) -> Future<String> {
print("Start B")
let promise = Promise<String>()
DispatchQueue.global().asyncAfter(deadline: .now() + 1) {
print("Complete B")
promise.complete("\(param) -> B")
}
return promise.future
}
func funcC(param: String) -> Future<String> {
print("Start C")
let promise = Promise<String>()
DispatchQueue.global().asyncAfter(deadline: .now() + 2) {
print("Complete C")
promise.complete("\(param) -> C")
}
return promise.future
}
func funcD() -> Future<String> {
print("Start D")
let promise = Promise<String>()
DispatchQueue.global().asyncAfter(deadline: .now() + 4) {
print("Complete D")
promise.complete("D")
}
return promise.future
}
func funcE(param: [String]) -> Future<String> {
print("Start E")
let promise = Promise<String>()
DispatchQueue.global().asyncAfter(deadline: .now() + 4) {
print("Complete E")
promise.complete("\(param) -> E")
}
return promise.future
}
Which prints this to the console:
Start A
Complete A
Start B
Start C
Start D
Complete B
Complete C
Complete D
Start E
Complete E
["A1 -> B", "A2 -> C", "D"] -> E
Hint: there are a couple of Future and Promise libraries available.
I am trying to implement a read/write lock in Swift with the pthread API's and I have come across a strange issue.
My implementation is largely based on the following with the addition of a timeout for attempted read locks.
http://swiftweb.johnholdsworth.com/Deferred/html/ReadWriteLock.html
Here is my implementation:
public final class ReadWriteLock {
private var lock = pthread_rwlock_t()
public init() {
let status = pthread_rwlock_init(&lock, nil)
assert(status == 0)
}
deinit {
let status = pthread_rwlock_destroy(&lock)
assert(status == 0)
}
#discardableResult
public func withReadLock<Result>(_ body: () throws -> Result) rethrows -> Result {
pthread_rwlock_rdlock(&lock)
defer { pthread_rwlock_unlock(&lock) }
return try body()
}
#discardableResult
public func withAttemptedReadLock<Result>(_ body: () throws -> Result) rethrows -> Result? {
guard pthread_rwlock_tryrdlock(&lock) == 0 else { return nil }
defer { pthread_rwlock_unlock(&lock) }
return try body()
}
#discardableResult
public func withAttemptedReadLock<Result>(_ timeout: Timeout = .now, body: () throws -> Result) rethrows -> Result? {
guard timeout != .now else { return try withAttemptedReadLock(body) }
let expiry = DispatchTime.now().uptimeNanoseconds + timeout.rawValue.uptimeNanoseconds
var ts = Timeout.interval(1).timespec
var result: Int32
repeat {
result = pthread_rwlock_tryrdlock(&lock)
guard result != 0 else { break }
nanosleep(&ts, nil)
} while DispatchTime.now().uptimeNanoseconds < expiry
// If the lock was not acquired
if result != 0 {
// Try to grab the lock once more
result = pthread_rwlock_tryrdlock(&lock)
}
guard result == 0 else { return nil }
defer { pthread_rwlock_unlock(&lock) }
return try body()
}
#discardableResult
public func withWriteLock<Return>(_ body: () throws -> Return) rethrows -> Return {
pthread_rwlock_wrlock(&lock)
defer { pthread_rwlock_unlock(&lock) }
return try body()
}
}
/// An amount of time to wait for an event.
public enum Timeout {
/// Do not wait at all.
case now
/// Wait indefinitely.
case forever
/// Wait for a given number of seconds.
case interval(UInt64)
}
public extension Timeout {
public var timespec: timespec {
let nano = rawValue.uptimeNanoseconds
return Darwin.timespec(tv_sec: Int(nano / NSEC_PER_SEC), tv_nsec: Int(nano % NSEC_PER_SEC))
}
public var rawValue: DispatchTime {
switch self {
case .now:
return DispatchTime.now()
case .forever:
return DispatchTime.distantFuture
case .interval(let milliseconds):
return DispatchTime(uptimeNanoseconds: milliseconds * NSEC_PER_MSEC)
}
}
}
extension Timeout : Equatable { }
public func ==(lhs: Timeout, rhs: Timeout) -> Bool {
switch (lhs, rhs) {
case (.now, .now):
return true
case (.forever, .forever):
return true
case (let .interval(ms1), let .interval(ms2)):
return ms1 == ms2
default:
return false
}
}
Here is my unit test:
func testReadWrite() {
let rwLock = PThreadReadWriteLock()
let queue = OperationQueue()
queue.maxConcurrentOperationCount = 2
queue.qualityOfService = .userInteractive
queue.isSuspended = true
var enterWrite: Double = 0
var exitWrite: Double = 0
let writeWait: UInt64 = 500
// Get write lock
queue.addOperation {
enterWrite = Double(Timeout.now.rawValue.uptimeNanoseconds) / Double(NSEC_PER_MSEC)
rwLock.withWriteLock {
// Sleep for 1 second
var ts = Timeout.interval(writeWait).timespec
var result: Int32
repeat { result = nanosleep(&ts, &ts) } while result == -1
}
exitWrite = Double(Timeout.now.rawValue.uptimeNanoseconds) / Double(NSEC_PER_MSEC)
}
var entered = false
var enterRead: Double = 0
var exitRead: Double = 0
let readWait = writeWait + 50
// Get read lock
queue.addOperation {
enterRead = Double(Timeout.now.rawValue.uptimeNanoseconds) / Double(NSEC_PER_MSEC)
rwLock.withAttemptedReadLock(.interval(readWait)) {
print("**** Entered! ****")
entered = true
}
exitRead = Double(Timeout.now.rawValue.uptimeNanoseconds) / Double(NSEC_PER_MSEC)
}
queue.isSuspended = false
queue.waitUntilAllOperationsAreFinished()
let startDifference = abs(enterWrite - enterRead)
let totalWriteTime = abs(exitWrite - enterWrite)
let totalReadTime = abs(exitRead - enterRead)
print("Start Difference: \(startDifference)")
print("Total Write Time: \(totalWriteTime)")
print("Total Read Time: \(totalReadTime)")
XCTAssert(totalWriteTime >= Double(writeWait))
XCTAssert(totalReadTime >= Double(readWait))
XCTAssert(totalReadTime >= totalWriteTime)
XCTAssert(entered)
}
Finally, the output of my unit test is the following:
Start Difference: 0.00136399269104004
Total Write Time: 571.76081609726
Total Read Time: 554.105705976486
Of course, the test is failing because the write lock is not released in time. Given that my wait time is only half a second (500ms), why is it taking roughly 570ms for the write lock to execute and release?
I have tried executing with optimizations both on and off to no avail.
I was under the impression that nanosleep is high resolution sleep timer I would expect to have a resolution of at least 5-10 milliseconds here for the lock timeout.
Can anyone shed some light here?
Turns out foundation was performing some kind of optimization with the OperationQueue due to the long sleep in my unit test.
Replacing the sleep function with usleep and iterating with a 1ms sleep until the total time is exceed seems to have fixed the problem.
// Get write lock
queue.addOperation {
enterWrite = Double(Timeout.now.rawValue.uptimeNanoseconds) / Double(NSEC_PER_MSEC)
rwLock.withWriteLock {
let expiry = DispatchTime.now().uptimeNanoseconds + Timeout.interval(writeWait).rawValue.uptimeNanoseconds
let interval = Timeout.interval(1)
repeat {
interval.sleep()
} while DispatchTime.now().uptimeNanoseconds < expiry
}
exitWrite = Double(Timeout.now.rawValue.uptimeNanoseconds) / Double(NSEC_PER_MSEC)
}