I am trying to understand how "heartbeat threads" work (at conceptual level, to begin with).
How is it possible that "Thread-A" checks status of "Thread-B" (in Java), and accordingly update status to some server (which expects Thread-B to be alive). What mechanism would Thread-A do to get status for Thread-B?
In general, one thread can only test whether another is alive, by calling isAlive().
However, many threads can be "alive" but in a state where they aren't doing anything useful. To detect that, you need to have the thread publish regular updates about its activity. Then a monitoring thread can detect whether the expected activity is no longer occurring.
For example, a batch process might update a shared counter each time it processes a record. Another thread can read this counter, and if it doesn't increase for some time, assume that the process is hung.
In production systems, the conventional solution is to instrument your process with calls to a metrics library. The library would make this information available to a time series database collector. Notification and visualization systems would use data from the time series database to send alerts or display graphs.
Software recommendations are off-topic, but one instantiation of this stack would be Micrometer to collect metrics, Prometheus to collect and store them, and Grafana to display them.
Related
I am building a fitness app which continually logs activity on the device. I need to log quite often, but I also don't want to unnecessarily drain the battery of my users which is why I am thinking about batching network calls together and transmitting them all at once as soon as the radio is active, the device is connected to a WiFi or it is charging.
I am using a filesystem based approach to implement that. I persist the data first to a File - eventually I might use Tape from Square to do that - but here is where I encounter the first issues.
I am continually writing new log data to the File, but I also need to periodically send all the logged data to my backend. When that happens I delete the contents of the File. The problem now is how can I prevent both of those operations from happening at the same time? Of course it will cause problems if I try to write log data to the File at the same time as some other process is reading from the File and trying to delete its contents.
I am thinking about using an IntentService essentially act as a queue for all those operations. And since - at least I have read as much - an IntentServices handles Intents sequentially in single worker Thread it shouldn't be possible for two of those operations to happen at the same time, right?
Currently I want to schedule a PeriodicTask with the GcmNetworkManager which would take care of sending the data to the server. Is there any better way to do all this?
1) You are overthinking this whole thing!
Your approach is way more complicated than it has to be! And for some reason none of the other answers point this out, but GcmNetworkManager already does everything you are trying to implement! You don't need to implement anything yourself.
2) Optimal way to implement what you are trying to do.
You don't seem to be aware that GcmNetworkManager already batches calls in the most battery efficient way with automatic retries etc and it also persists the tasks across device boots and can ensure their execution as soon as is battery efficient and required by your app.
Just whenever you have data to save schedule a OneOffTask like this:
final OneoffTask task = new OneoffTask.Builder()
// The Service which executes the task.
.setService(MyTaskService.class)
// A tag which identifies the task
.setTag(TASK_TAG)
// Sets a time frame for the execution of this task in seconds.
// This specifically means that the task can either be
// executed right now, or must have executed at the lastest in one hour.
.setExecutionWindow(0L, 3600L)
// Task is persisted on the disk, even across boots
.setPersisted(true)
// Unmetered connection required for task
.setRequiredNetwork(Task.NETWORK_STATE_UNMETERED)
// Attach data to the task in the form of a Bundle
.setExtras(dataBundle)
// If you set this to true and this task already exists
// (just depends on the tag set above) then the old task
// will be overwritten with this one.
.setUpdateCurrent(true)
// Sets if this task should only be executed when the device is charging
.setRequiresCharging(false)
.build();
mGcmNetworkManager.schedule(task);
This will do everything you want:
The Task will be persisted on the disk
The Task will be executed in a batched and battery efficient way, preferably over Wifi
You will have configurable automatic retries with a battery efficient backoff pattern
The Task will be executed within a time window you can specify.
I suggest for starters you read this to learn more about the GcmNetworkManager.
So to summarize:
All you really need to do is implement your network calls in a Service extending GcmTaskService and later whenever you need to perform such a network call you schedule a OneOffTask and everything else will be taken care of for you!
Of course you don't need to call each and every setter of the OneOffTask.Builder like I do above - I just did that to show you all the options you have. In most cases scheduling a task would just look like this:
mGcmNetworkManager.schedule(new OneoffTask.Builder()
.setService(MyTaskService.class)
.setTag(TASK_TAG)
.setExecutionWindow(0L, 300L)
.setPersisted(true)
.setExtras(bundle)
.build());
And if you put that in a helper method or even better create factory methods for all the different tasks you need to do than everything you were trying to do should just boil down to a few lines of code!
And by the way: Yes, an IntentService handles every Intent one after another sequentially in a single worker Thread. You can look at the relevant implementation here. It's actually very simple and quite straight forward.
All UI and Service methods are by default invoked on the same main thread. Unless you explicitly create threads or use AsyncTask there is no concurrency in an Android application per se.
This means that all intents, alarms, broad-casts are by default handled on the main thread.
Also note that doing I/O and/or network requests may be forbidden on the main thread (depending on Android version, see e.g. How to fix android.os.NetworkOnMainThreadException?).
Using AsyncTask or creating your own threads will bring you to concurrency problems but they are the same as with any multi-threaded programming, there is nothing special to Android there.
One more point to consider when doing concurrency is that background threads need to hold a WakeLock or the CPU may go to sleep.
Just some idea.
You may try to make use of serial executor for your file, therefore, only one thread can be execute at a time.
http://developer.android.com/reference/android/os/AsyncTask.html#SERIAL_EXECUTOR
I designed a java application. A friend suggested using multi-threading, he claims that running my application as several threads will decrease the run time significantly.
In my main class, I carry several operations that are out of our scope to fill global static variables and hash maps to be used across the whole life time of the process. Then I run the core of the application on the entries of an array list.
for(int customerID : customers){
ConsumerPrinter consumerPrinter = new ConsumerPrinter();
consumerPrinter.runPE(docsPath,outputPath,customerID);
System.out.println("Customer with CustomerID:"+customerID+" Done");
}
for each iteration of this loop XMLs of the given customer is fetched from the machine, parsed and calculations are taken on the parsed data. Later, processed results are written in a text file (Fetched and written data can reach up to several Giga bytes at most and 50 MBs on average). More than one iteration can write on the same file.
Should I make this piece of code multi-threaded so each group of customers are taken in an independent thread?
How can I know the most optimal number of threads to run?
What are the best practices to take into consideration when implementing multi-threading?
Should I make this piece of code multi-threaded so each group of customers are taken
in an independent thread?
Yes multi-threading will save your processing time. While iterating on your list you can spawn new thread each iteration and do customer processing in it. But you need to do proper synchronization meaning if two customers processing requires operation on same resource you must synchronize that operation to avoid possible race condition or memory inconsistency issues.
How can I know the most optimal number of threads to run?
You cannot really without actually analyzing the processing time for n customers with different number of threads. It will depend on number of cores your processor has, and what is the actually processing that is taking place for each customer.
What are the best practices to take into consideration when implementing multi-threading?
First and foremost criteria is you must have multiple cores and your OS must support multi-threading. Almost every system does that in present times but is a good criteria to look into. Secondly you must analyze all the possible scenarios that may led to race condition. All the resource that you know will be shared among multiple threads must be thread-safe. Also you must also look out for possible chances of memory inconsistency issues(declare your variable as volatile). Finally there are something that you cannot predict or analyze until you actually run test cases like deadlocks(Need to analyze Thread dump) or memory leaks(Need to analyze Heap dump).
The idea of multi thread is to make some heavy process into another, lets say..., "block of memory".
Any UI updates have to be done on the main/default thread, like print messenges or inflate a view for example. You can ask the app to draw a bitmap, donwload images from the internet or a heavy validation/loop block to run them on a separate thread, imagine that you are creating a second short life app to handle those tasks for you.
Remember, you can ask the app to download/draw a image on another thread, but you have to print this image on the screen on the main thread.
This is common used to load a large bitmap on a separated thread, make math calculations to resize this large image and then, on the main thread, inflate/print/paint/show the smaller version of that image to te user.
In your case, I don't know how heavy runPE() method is, I don't know what it does, you could try to create another thread for him, but the rest should be on the main thread, it is the main process of your UI.
You could optmize your loop by placing the "ConsumerPrinter consumerPrinter = new ConsumerPrinter();" before the "for(...)", since it does not change dinamically, you can remove it inside the loop to avoid the creating of the same object each time the loop restarts : )
While straight java multi-threading can be used (java.util.concurrent) as other answers have discussed, consider also alternate programming approaches to multi-threading, such as the actor model. The actor model still uses threads underneath, but much complexity is handled by the actor framework rather than directly by you the programmer. In addition, there is less (or no) need to reason about synchronizing on shared state between threads because of the way programs using the actor model are created.
See Which Actor model library/framework for Java? for a discussion of popular actor model libraries.
Even after reading http://krondo.com/?p=1209 or Does an asynchronous call always create/call a new thread? I am still confused about how to provide asynchronous calls on an inherently single-threaded system. I will explain my understanding so far and point out my doubts.
One of the examples I read was describing a TCP server providing asynch processing of requests - a user would call a method e.g. get(Callback c) and the callback would be invoked some time later. Now, my first issue here - we have already two systems, one server and one client. This is not what I mean, cause in fact we have two threads at least - one in the server and one on the client side.
The other example I read was JavaScript, as this is the most prominent example of single-threaded asynch system with Node.js. What I cannot get through my head, maybe thinking in Java terms, is this:If I execute the code below (apologies for incorrect, probably atrocious syntax):
function foo(){
read_file(FIle location, Callback c) //asynchronous call, does not block
//do many things more here, potentially for hours
}
the call to read file executes (sth) and returns, allowing the rest of my function to execute. Since there is only one thread i.e. the one that is executing my function, how on earth the same thread (the one and only one which is executing my stuff) will ever get to read in the bytes from disk?
Basically, it seems to me I am missing some underlying mechanism that is acting like round-robin scheduler of some sort, which is inherently single-threaded and might split the tasks to smaller ones or call into a multiothraded components that would spawn a thread and read the file in.
Thanks in advance for all comments and pointing out my mistakes on the way.
Update: Thanks for all responses. Further good sources that helped me out with this are here:
http://www.html5rocks.com/en/tutorials/async/deferred/
http://lostechies.com/johnteague/2012/11/30/node-js-must-know-concepts-asynchrounous/
http://www.interact-sw.co.uk/iangblog/2004/09/23/threadless (.NET)
http://ejohn.org/blog/how-javascript-timers-work/ (intrinsics of timers)
http://www.mobl-lang.org/283/reducing-the-pain-synchronous-asynchronous-programming/
The real answer is that it depends on what you mean by "single thread".
There are two approaches to multitasking: cooperative and interrupt-driven. Cooperative, which is what the other StackOverflow item you cited describes, requires that routines explicitly relinquish ownership of the processor so it can do other things. Event-driven systems are often designed this way. The advantage is that it's a lot easier to administer and avoids most of the risks of conflicting access to data since only one chunk of your code is ever executing at any one time. The disadvantage is that, because only one thing is being done at a time, everything has to either be designed to execute fairly quickly or be broken up into chunks that to so (via explicit pauses like a yield() call), or the system will appear to freeze until that event has been fully processed.
The other approach -- threads or processes -- actively takes the processor away from running chunks of code, pausing them while something else is done. This is much more complicated to implement, and requires more care in coding since you now have the risk of simultaneous access to shared data structures, but is much more powerful and -- done right -- much more robust and responsive.
Yes, there is indeed a scheduler involved in either case. In the former version the scheduler is just spinning until an event arrives (delivered from the operating system and/or runtime environment, which is implicitly another thread or process) and dispatches that event before handling the next to arrive.
The way I think of it in JavaScript is that there is a Queue which holds events. In the old Java producer/consumer parlance, there is a single consumer thread pulling stuff off this queue and executing every function registered to receive the current event. Events such as asynchronous calls (AJAX requests completing), timeouts or mouse events get pushed on to the Queue as soon as they happen. The single "consumer" thread pulls them off the queue and locates any interested functions and then executes them, it cannot get to the next Event until it has finished invoking all the functions registered on the current one. Thus if you have a handler that never completes, the Queue just fills up - it is said to be "blocked".
The system has more than one thread (it has at least one producer and a consumer) since something generates the events to go on the queue, but as the author of the event handlers you need to be aware that events are processed in a single thread, if you go into a tight loop, you will lock up the only consumer thread and make the system unresponsive.
So in your example :
function foo(){
read_file(location, function(fileContents) {
// called with the fileContents when file is read
}
//do many things more here, potentially for hours
}
If you do as your comments says and execute potentially for hours - the callback which handles fileContents will not fire for hours even though the file has been read. As soon as you hit the last } of foo() the consumer thread is done with this event and can process the next one where it will execute the registered callback with the file contents.
HTH
My application takes a lot of measurements of it's internal processes. For example I time certain methods, I time external webservice calls and I also have variables which have a changing value, and processes which have a 'state' (e.g. PAUSED, WAITING etc).
The application uses 100 to 200 threads, and each bit of data would be associated with a particular thread.
I am looking for some software that I can channel all this information into that would produce useful metrics and graphs of the data (ideally in real time or close to real time), let me set thresholds to trigger warnings, would allow me to filter the data by thread or thread group, etc etc.
The application is performing time critical tasks so the software/api would need to be very fast and never block.
The application is written in java, and ideally the software/api would be in java as well. I think what I'm looking for is called Event Stream Processing, but I'm really not sure what language to use to describe it.
All I've found so far are Esper and ERMA. Can anyone give me a recommendation? I'm the only one working on this project so I'm hoping for something that is pretty easy to set up and use, and has a workable front end.
In the end I found Graphite which was pretty close to being exactly what I wanted. Not the simplest to set up and configure however, but I got it working in the end.
http://graphite.wikidot.com/
In my case I send data directly from my application to Statsd (via UDP), which collects the data and does some pre processing before it ends up in the whisper back end, there is a simple example of a java interface here https://github.com/etsy/statsd/commit/2253223f3c19d2149d65ec5bc802198ff93da4cb
Alternatively you could send your data directly to graphite, example here http://neopatel.blogspot.co.uk/2011/04/logging-to-graphite-monitoring-tool.html
I am working on a program (Java) that uses concurrent threading quite heavily. I run into issues with the work being performed by these threads very regularly. It's not an issue with the actual thread handling, instead it is the actual stuff it's doing (db access, math computations, file IO etc).
I would like to provide some way of seeing the status of threads in realtime from the console. Perhaps something like this:
THREAD ID THREAD STATUS TABLE NAME ELAPSED TIME
Thread 1: Dumping MSF011 22s
Thread 2: Conversion MSF002 2h 8m
Thread 3: Conversion MSF020 10s
Thread 4: Loading MSF001 14m
ITEMS LEFT IN QUEUE: MSF033, MSF123, MSFXYZ
sort of thing.
Ideally I'd like to see that updated in place (so no new lines etc, but I am open to ANY idea that lets me see information like this quickly.
How important is the console output? I mean, will other mechanisms (ie graphical) be ok?
Either way, I'd approach it as two steps.
Instrument your threads
Display the instrument data
Instrument your threads
If JConole and the default thread information isn't enough (WAITING, stack traces etc), you can get your threads to post updates to their state as they go along. I like to use MBeans to do this so that way you can separate the posting of updates from the reading. Otherwise you could update some shared location with the state and have the reading done in the same VM. Perhaps even dumping process information to a file?
Display the instrument data
Once you've got the threads updating the process information within, displaying it should be straight forward. If you really want the console output and to have it not scroll, I think something like ncurses is your only choice.
Otherwise, it's probably simpler to write a little UI that reads the instrument data and updates a display. You can read this data via the MBean server if your using MBeans (and so separate the UI physically from the server) or just read from say a file. JFreeChart is nice if you want some pretty graphs.
Having said all that, Haim has written a 'top' style thing to monitor threads. See here. Might be useful