我正在使用firebase-queue
来处理一些服务器端的工作。当用户注册时,服务器将处理三个任务
var customSpecs = {
'queue': {
'specs': {
'save_user_to_firebase': {
'in_progress_state': 'save_user_to_firebase_in_progress',
'finished_state': 'save_user_to_firebase_finished',
'retries': 3
},
'fetch_from_third_party_API': {
'start_state': 'save_user_to_firebase_finished',
'in_progress_state': 'fetch_from_third_party_API_in_progress',
'finished_state': 'fetch_from_third_party_API_finished',
'retries': 3
},
'save_to_google_datastore':{
'start_state': 'fetch_from_third_party_API_finished',
'in_progress_state': 'save_to_google_datastore_finished',
'retries': 3
}
}
}
}
我编写了没有功能的测试代码。为了测试firebase-queue的性能,我记录了save_user_to_firebase
任务为每个用户启动的时间。
第一个队列
var options = {
'specId': 'save_user_to_firebase',
'numWorkers': 100
}
var saveUserQueue = new Queue({ tasksRef: taskRef, specsRef: specsObjectRef }, options, function (data, progress, resolve, reject) {
var t0 = process.hrtime();
var testUser = data.test_user;
var now = new Date();
console.log("started %s %d:%d:%d:%d", testUser, + now.getHours(), now.getMinutes(), now.getSeconds(), now.getMilliseconds());
var t1 = process.hrtime(t0);
console.log("save_user_to_firebase completed in %s %ds %dms", testUser, t1[0], t1[1]/1000000 );
resolve(data);
}
第二个队列
var options = {
'specId': 'fetch_from_third_party_API',
'numWorkers': 100
};
var fetchFromAPI = new Queue({ tasksRef: taskRef, specsRef: specsObjectRef }, options, function(data, progress, resolve, reject) {
var testUser = data.test_user;
var t0 = process.hrtime();
//Add code for fetching from API
var t1 = process.hrtime(t0);
console.log("fetchFromAPI completed in %s %ds %dms", testUser, t1[0], t1[1]/1000000 );
resolve(data);
});
第三个队列
var options = {
'specId': 'save_to_google_datastore',
'numWorkers': 100
};
var save_to_google_datastoreQueue = new Queue({ tasksRef: taskRef, specsRef: specsObjectRef }, options, function(data, progress, resolve, reject) {
var testUser = data.test_user;
var t0 = process.hrtime();
var now = new Date();
var t1 = process.hrtime(t0);
console.log("datastoreInsertActivitiesQueue completed %s %ds %dms",testUser, t1[0], t1[1]/1000000);
resolve(data);
})
我通过一次更新调用推送了40个任务。我为每个队列使用100名工人。我看到save_user_to_firebase tasks
有明显的延迟。我在队列中没有任何功能。结果由上面的代码产生。
我衡量每个用户save_user_to_firebase
与队列中第一个用户的时间之间的时间差。
started user1 at 13:5:13:575
……
started user40 at 13:5:34:545
我编写了一个脚本来解析日志并计算每个用户的延迟。以下是输出:
user1 delay = 0:0
user3 delay = 0:0
user4 delay = 0:0
user5 delay = 0:1
user6 delay = 0:2
user7 delay = 0:2
user2 delay = 0:2
user9 delay = 0:3
user10 delay = 0:4
user11 delay = 0:4
user12 delay = 0:5
user13 delay = 0:5
user14 delay = 0:6
user8 delay = 0:7
user16 delay = 0:7
user15 delay = 0:8
user18 delay = 0:9
user19 delay = 0:10
user20 delay = 0:10
user21 delay = 0:11
user22 delay = 0:12
user17 delay = 0:12
user24 delay = 0:13
user23 delay = 0:13
user26 delay = 0:14
user27 delay = 0:14
user28 delay = 0:14
user29 delay = 0:15
user30 delay = 0:16
user25 delay = 0:16
user32 delay = 0:17
user31 delay = 0:17
user34 delay = 0:18
user35 delay = 0:18
user36 delay = 0:18
user37 delay = 0:19
user38 delay = 0:20
user33 delay = 0:21
user40 delay = 0:20
user39 delay = 0:21
这是正常的表现率吗?
答案 0 :(得分:0)
Firebase队列库使用Firebase数据库事务来确保只有一个工作进程可以获取任务。这意味着最大吞吐量在很大程度上取决于任务的大小。您拥有的工作人员越多,任务越短,队列中的争用就越高。对于简短的任务,我们建议不要使用超过六名工人。之后,您将看到吞吐量增加水平,甚至可能会降低。