I have a map which holds some data similar to an in memory cache.
Map<String,Object> map;
There are multiple theads which are reading the data from the map. Each thread may read the data more than one time.
public void processData(){
...
map.get("something");
...
map.get("someOther");
...
}
The map needs to be updated with latest values from database. I use a webservice for that.
public void refreshService(){
//this code should wait until no one is reading the data
map.clear();
map.put("latestFromDb",readData());
}
The requirement is that my web service should wait until all the reading threads are finished. So that the readers should get either the old data fully or the new data fully.
Edit: The reading threads should not wait for anything. The reading thread can wait for the web service(Since this is infrequent). but the reading threads should not wait for other reading threads.
Which java 8 lock/mechanism/design pattern I can use to implement this.
Since the reading operation queries the map multiple times, the only way to get a consistent result (without locking), is to never modify the map at all.
In other words, instead of calling clear(), instantiate a new map, populate it, and change the map reference to point to the new map, as an atomic update. Don’t forget that the read operation must not read map multiple times then, but copy the current reference into a local variable right at the beginning.
volatile Map<String, Object> map;
public void processData(){
Map<String, Object> map = this.map;
...
map.get("something");
...
map.get("someOther");
...
}
public void refreshService() {
Map<String, Object> map = new HashMap<>();
map.put("latestFromDb", readData());
...
this.map = Collections.unmodifiableMap(map);
}
Wrapping the map with unmodifiableMap is not strictly necessary, but will help spotting errors, as any modification beyond this point would lead to nondeterministic behavior, including the possibility to never spot the problem during testing. Therefore, replacing the nondeterministic behavior with deterministically throwing an exception on subsequent modification attempts, is preferable.
I have a situation where I need a set of operations be enclosed into a single transaction and be thread safe from a MDB.
If thread A executes the instruction 1, do not want other threads can read, at least not the same, data that thread A is processing.
In the code below since IMAGE table contains duplicated data, coming from different sources, this will lead in a duplicated INFRANCTION. Situation that needs to be avoided.
The actual solution that I found is declaring a new transaction for each new message and synchronize the entire transaction.
Simplifying the code:
#Stateless
InfranctionBean{
#TransactionAttribute(TransactionAttributeType.REQUIRES_NEW)
checkInfranction(String plate){
1. imageBean.getImage(plate); // read from table IMAGE
2. infranctionBean.insertInfranction(String plate); // insert into table INFRANCTION
3. imageBean.deleteImage(String plate); //delete from table IMAGE
}
}
#MessageDriven
public class ImageReceiver {
private static Object lock = new Object();
public void onMessage(Message msg){
String plate = msg.plate;
synchronized (lock) {
infanctionBean.checkInfranction(plate);
}
}
}
I am aware that using synchronized blocks inside the EJB is not recommanded by EJB specification. This can lead even in problems if the applicaton server runs in two node cluster.
Seems like EE6 has introduced a solution for this scenario, which is the EJB Singleton.
In this case, my solution would be something like this:
#ConcurrencyManagement(ConcurrencyManagementType.CONTAINER)
#Singleton
InfranctionBean{
#Lock(LockType.WRITE)
checkInfranction(String plate){
1...
2...
3...
}
}
And from MDB would not be neccessary the usage of synchronized block since the container will handle the concurrency.
With #Lock(WRITE) the container guarantees the access of single thread inside checkInfranction().
My queston is: How can I handle this situation in EE5? There is a cleaner solution without using synchronized block?
Environment: Java5,jboss-4.2.3.GA,Oracle10.
ACTUAL SOLUTION
#Stateless
InfranctionBean{
#TransactionAttribute(TransactionAttributeType.REQUIRES_NEW)
checkInfranction(String plate){
1. imageBean.lockImageTable(); // lock table IMAGE in exclusive mode
2. imageBean.getImage(plate); // read from table IMAGE
3. infranctionBean.insertInfranction(String plate); // insert into table INFRANCTION
4. imageBean.deleteImage(String plate); //delete from table IMAGE
}
}
#MessageDriven
public class ImageReceiver {
public void onMessage(Message msg){
infanctionBean.checkInfranction(msg.plate);
}
}
On 20.000 incoming messages (half of them simultaneously) seems the application works ok.
#Lock(WRITE) is only a lock within a single application/JVM, so unless you can guarantee that only one application/JVM is accessing the data, you're not getting much protection anyway. If you're only looking for single application/JVM protection, the best solution in EE 5 would be a ReadWriteLock or perhaps a synchronized block. (The EJB specification has language to dissuade applications from doing this to avoid compromising the thread management of the server, so take care that you don't block indefinitely, that you don't ignore interrupts, etc.)
If you're looking for a more robust cross-application/JVM solution, I would use database locks or isolation levels rather than trying to rely on JVM synchronized primitives. That is probably the best solution regardless of the EJB version being used.
We are building REST using spray and akka. For this we need to read more than 10k files from disk (Mostly static, updates might come twice per day). Reading from disk for each request is giving performance hit, we put all required information in DataMap (Map object). Using akka scheduler updating DataMap for each 15min(Needs to be up-to date with disk data).
class SampleScheduler extends Actor with ActorLogging {
import context._
val tick = context.system.scheduler.schedule(1.second,15.minute, self,"mytick")
override def postStop() = tick.cancel()
override def receive: Receive = {
case "mytick" => {
println(s"Yes got the tick now ${new Date().toGMTString}")
Test.setDataMap()
}
}
}
object Test {
var DataMap:Map[String,List[String]]=Map()
def setDataMap()={
DataMap = //Read files from disk
}
}
object Main extends App {
//For each new request look into DataMap
if(Test.DataMap.isEmpty) {
//How to handle this, can i use like this
Thread.sleep(1000)
}
}
So when the new request comes, it searches required data from map and get information, process accordingly.
How to achieve below requirements with above said design.
Now for each request, creating one actor and reading above DataMap and starts processing. After started processing, if DataMap becomes empty and re-loaded, how to handle this?
If DataMap found empty, how to retry? Can i use Thread.sleep method?
Is storing DataMap and resetting it for each 15min in "Object" good practice?
First and most important of all, you must avoid (3). Storing state outside of actor is evil! Besides, storing state and maintaining it is what actors are good at.
And after you put state inside of actor and share it via messages, (2) will be obsolete. The request actor will ask state actor and if state actor is busy with re-reading files, it will answer after its job done.
Lastly, there are 2 different strategies you can follow to solve (1). State actor will process each messages in order so it can (a) reply message with last know state or (b) hold messages and reply with newly populated state if it thinks it should re-read files.
I have the following code:
Dictionary<string, WSResponse> responseDictionary = new Dictionary<string, WSResponse>();
List<Task> taskList = new List<Task>();
foreach (string ID in IDs)
{
string localID = ID;
Task newTask = Task.Factory.StartNew(() =>
{
WSResponse response = Query.GetListFor(localID);
responseDictionary.Add(localID, response);
});
taskList.Add(newTask);
}
Task.WaitAll(taskList.ToArray());
Should I be using a ConcurrentDictionary instead of a Dictionary in this case? Even if I make sure keys do not repeate on the logical level?
ConcurrentDictionary and locking are NOT interchangeable or equivalent.
Adding a lock will force all tasks to write to the dictionary sequentially, essentially negating any benefits you may have from concurrent processing. The Dictionary class will also throw a somewhat cryptic exception if more than two threads try to write to it concurrently. This is because unlocked access will corrupt its internal structures.
A ConcurrentDictionary on the other hand allows all tasks to write to the dictionary concurrently without any need of locking. The penalty is slower synchronous performance compared to the unlocked synchronous version. In concurrent scenarios though, performance and scalability are much better.
You should use syncronization, yes. A simple lock would be enough.
Recently I tried to Access a textbox from a thread (other than the UI thread) and an exception was thrown. It said something about the "code not being thread safe" and so I ended up writing a delegate (sample from MSDN helped) and calling it instead.
But even so I didn't quite understand why all the extra code was necessary.
Update:
Will I run into any serious problems if I check
Controls.CheckForIllegalCrossThread..blah =true
Eric Lippert has a nice blog post entitled What is this thing you call "thread safe"? about the definition of thread safety as found of Wikipedia.
3 important things extracted from the links :
“A piece of code is thread-safe if it functions correctly during
simultaneous execution by multiple threads.”
“In particular, it must satisfy the need for multiple threads to
access the same shared data, …”
“…and the need for a shared piece of data to be accessed by only one
thread at any given time.”
Definitely worth a read!
In the simplest of terms threadsafe means that it is safe to be accessed from multiple threads. When you are using multiple threads in a program and they are each attempting to access a common data structure or location in memory several bad things can happen. So, you add some extra code to prevent those bad things. For example, if two people were writing the same document at the same time, the second person to save will overwrite the work of the first person. To make it thread safe then, you have to force person 2 to wait for person 1 to complete their task before allowing person 2 to edit the document.
Wikipedia has an article on Thread Safety.
This definitions page (you have to skip an ad - sorry) defines it thus:
In computer programming, thread-safe describes a program portion or routine that can be called from multiple programming threads without unwanted interaction between the threads.
A thread is an execution path of a program. A single threaded program will only have one thread and so this problem doesn't arise. Virtually all GUI programs have multiple execution paths and hence threads - there are at least two, one for processing the display of the GUI and handing user input, and at least one other for actually performing the operations of the program.
This is done so that the UI is still responsive while the program is working by offloading any long running process to any non-UI threads. These threads may be created once and exist for the lifetime of the program, or just get created when needed and destroyed when they've finished.
As these threads will often need to perform common actions - disk i/o, outputting results to the screen etc. - these parts of the code will need to be written in such a way that they can handle being called from multiple threads, often at the same time. This will involve things like:
Working on copies of data
Adding locks around the critical code
Opening files in the appropriate mode - so if reading, don't open the file for write as well.
Coping with not having access to resources because they're locked by other threads/processes.
Simply, thread-safe means that a method or class instance can be used by multiple threads at the same time without any problems occurring.
Consider the following method:
private int myInt = 0;
public int AddOne()
{
int tmp = myInt;
tmp = tmp + 1;
myInt = tmp;
return tmp;
}
Now thread A and thread B both would like to execute AddOne(). but A starts first and reads the value of myInt (0) into tmp. Now for some reason, the scheduler decides to halt thread A and defer execution to thread B. Thread B now also reads the value of myInt (still 0) into it's own variable tmp. Thread B finishes the entire method so in the end myInt = 1. And 1 is returned. Now it's Thread A's turn again. Thread A continues. And adds 1 to tmp (tmp was 0 for thread A). And then saves this value in myInt. myInt is again 1.
So in this case the method AddOne() was called two times, but because the method was not implemented in a thread-safe way the value of myInt is not 2, as expected, but 1 because the second thread read the variable myInt before the first thread finished updating it.
Creating thread-safe methods is very hard in non-trivial cases. And there are quite a few techniques. In Java you can mark a method as synchronized, this means that only one thread can execute that method at a given time. The other threads wait in line. This makes a method thread-safe, but if there is a lot of work to be done in a method, then this wastes a lot of space. Another technique is to 'mark only a small part of a method as synchronized' by creating a lock or semaphore, and locking this small part (usually called the critical section). There are even some methods that are implemented as lock-less thread-safe, which means that they are built in such a way that multiple threads can race through them at the same time without ever causing problems, this can be the case when a method only executes one atomic call. Atomic calls are calls that can't be interrupted and can only be done by one thread at a time.
In real world example for the layman is
Let's suppose you have a bank account with the internet and mobile banking and your account have only $10.
You performed transfer balance to another account using mobile banking, and the meantime, you did online shopping using the same bank account.
If this bank account is not threadsafe, then the bank allows you to perform two transactions at the same time and then the bank will become bankrupt.
Threadsafe means that an object's state doesn't change if simultaneously multiple threads try to access the object.
You can get more explanation from the book "Java Concurrency in Practice":
A class is thread‐safe if it behaves correctly when accessed from multiple threads, regardless of the scheduling or interleaving of the execution of those threads by the runtime environment, and with no additional synchronization or other coordination on the part of the calling code.
A module is thread-safe if it guarantees it can maintain its invariants in the face of multi-threaded and concurrence use.
Here, a module can be a data-structure, class, object, method/procedure or function. Basically scoped piece of code and related data.
The guarantee can potentially be limited to certain environments such as a specific CPU architecture, but must hold for those environments. If there is no explicit delimitation of environments, then it is usually taken to imply that it holds for all environments that the code can be compiled and executed.
Thread-unsafe modules may function correctly under mutli-threaded and concurrent use, but this is often more down to luck and coincidence, than careful design. Even if some module does not break for you under, it may break when moved to other environments.
Multi-threading bugs are often hard to debug. Some of them only happen occasionally, while others manifest aggressively - this too, can be environment specific. They can manifest as subtly wrong results, or deadlocks. They can mess up data-structures in unpredictable ways, and cause other seemingly impossible bugs to appear in other remote parts of the code. It can be very application specific, so it is hard to give a general description.
Thread safety: A thread safe program protects it's data from memory consistency errors. In a highly multi-threaded program, a thread safe program does not cause any side effects with multiple read/write operations from multiple threads on same objects. Different threads can share and modify object data without consistency errors.
You can achieve thread safety by using advanced concurrency API. This documentation page provides good programming constructs to achieve thread safety.
Lock Objects support locking idioms that simplify many concurrent applications.
Executors define a high-level API for launching and managing threads. Executor implementations provided by java.util.concurrent provide thread pool management suitable for large-scale applications.
Concurrent Collections make it easier to manage large collections of data, and can greatly reduce the need for synchronization.
Atomic Variables have features that minimize synchronization and help avoid memory consistency errors.
ThreadLocalRandom (in JDK 7) provides efficient generation of pseudorandom numbers from multiple threads.
Refer to java.util.concurrent and java.util.concurrent.atomic packages too for other programming constructs.
Producing Thread-safe code is all about managing access to shared mutable states. When mutable states are published or shared between threads, they need to be synchronized to avoid bugs like race conditions and memory consistency errors.
I recently wrote a blog about thread safety. You can read it for more information.
You are clearly working in a WinForms environment. WinForms controls exhibit thread affinity, which means that the thread in which they are created is the only thread that can be used to access and update them. That is why you will find examples on MSDN and elsewhere demonstrating how to marshall the call back onto the main thread.
Normal WinForms practice is to have a single thread that is dedicated to all your UI work.
I find the concept of http://en.wikipedia.org/wiki/Reentrancy_%28computing%29 to be what I usually think of as unsafe threading which is when a method has and relies on a side effect such as a global variable.
For example I have seen code that formatted floating point numbers to string, if two of these are run in different threads the global value of decimalSeparator can be permanently changed to '.'
//built in global set to locale specific value (here a comma)
decimalSeparator = ','
function FormatDot(value : real):
//save the current decimal character
temp = decimalSeparator
//set the global value to be
decimalSeparator = '.'
//format() uses decimalSeparator behind the scenes
result = format(value)
//Put the original value back
decimalSeparator = temp
To understand thread safety, read below sections:
4.3.1. Example: Vehicle Tracker Using Delegation
As a more substantial example of delegation, let's construct a version of the vehicle tracker that delegates to a thread-safe class. We store the locations in a Map, so we start with a thread-safe Map implementation, ConcurrentHashMap. We also store the location using an immutable Point class instead of MutablePoint, shown in Listing 4.6.
Listing 4.6. Immutable Point class used by DelegatingVehicleTracker.
class Point{
public final int x, y;
public Point() {
this.x=0; this.y=0;
}
public Point(int x, int y) {
this.x = x;
this.y = y;
}
}
Point is thread-safe because it is immutable. Immutable values can be freely shared and published, so we no longer need to copy the locations when returning them.
DelegatingVehicleTracker in Listing 4.7 does not use any explicit synchronization; all access to state is managed by ConcurrentHashMap, and all the keys and values of the Map are immutable.
Listing 4.7. Delegating Thread Safety to a ConcurrentHashMap.
public class DelegatingVehicleTracker {
private final ConcurrentMap<String, Point> locations;
private final Map<String, Point> unmodifiableMap;
public DelegatingVehicleTracker(Map<String, Point> points) {
this.locations = new ConcurrentHashMap<String, Point>(points);
this.unmodifiableMap = Collections.unmodifiableMap(locations);
}
public Map<String, Point> getLocations(){
return this.unmodifiableMap; // User cannot update point(x,y) as Point is immutable
}
public Point getLocation(String id) {
return locations.get(id);
}
public void setLocation(String id, int x, int y) {
if(locations.replace(id, new Point(x, y)) == null) {
throw new IllegalArgumentException("invalid vehicle name: " + id);
}
}
}
If we had used the original MutablePoint class instead of Point, we would be breaking encapsulation by letting getLocations publish a reference to mutable state that is not thread-safe. Notice that we've changed the behavior of the vehicle tracker class slightly; while the monitor version returned a snapshot of the locations, the delegating version returns an unmodifiable but “live” view of the vehicle locations. This means that if thread A calls getLocations and thread B later modifies the location of some of the points, those changes are reflected in the Map returned to thread A.
4.3.2. Independent State Variables
We can also delegate thread safety to more than one underlying state variable as long as those underlying state variables are independent, meaning that the composite class does not impose any invariants involving the multiple state variables.
VisualComponent in Listing 4.9 is a graphical component that allows clients to register listeners for mouse and keystroke events. It maintains a list of registered listeners of each type, so that when an event occurs the appropriate listeners can be invoked. But there is no relationship between the set of mouse listeners and key listeners; the two are independent, and therefore VisualComponent can delegate its thread safety obligations to two underlying thread-safe lists.
Listing 4.9. Delegating Thread Safety to Multiple Underlying State Variables.
public class VisualComponent {
private final List<KeyListener> keyListeners
= new CopyOnWriteArrayList<KeyListener>();
private final List<MouseListener> mouseListeners
= new CopyOnWriteArrayList<MouseListener>();
public void addKeyListener(KeyListener listener) {
keyListeners.add(listener);
}
public void addMouseListener(MouseListener listener) {
mouseListeners.add(listener);
}
public void removeKeyListener(KeyListener listener) {
keyListeners.remove(listener);
}
public void removeMouseListener(MouseListener listener) {
mouseListeners.remove(listener);
}
}
VisualComponent uses a CopyOnWriteArrayList to store each listener list; this is a thread-safe List implementation particularly suited for managing listener lists (see Section 5.2.3). Each List is thread-safe, and because there are no constraints coupling the state of one to the state of the other, VisualComponent can delegate its thread safety responsibilities to the underlying mouseListeners and keyListeners objects.
4.3.3. When Delegation Fails
Most composite classes are not as simple as VisualComponent: they have invariants that relate their component state variables. NumberRange in Listing 4.10 uses two AtomicIntegers to manage its state, but imposes an additional constraint—that the first number be less than or equal to the second.
Listing 4.10. Number Range Class that does Not Sufficiently Protect Its Invariants. Don't do this.
public class NumberRange {
// INVARIANT: lower <= upper
private final AtomicInteger lower = new AtomicInteger(0);
private final AtomicInteger upper = new AtomicInteger(0);
public void setLower(int i) {
//Warning - unsafe check-then-act
if(i > upper.get()) {
throw new IllegalArgumentException(
"Can't set lower to " + i + " > upper ");
}
lower.set(i);
}
public void setUpper(int i) {
//Warning - unsafe check-then-act
if(i < lower.get()) {
throw new IllegalArgumentException(
"Can't set upper to " + i + " < lower ");
}
upper.set(i);
}
public boolean isInRange(int i){
return (i >= lower.get() && i <= upper.get());
}
}
NumberRange is not thread-safe; it does not preserve the invariant that constrains lower and upper. The setLower and setUpper methods attempt to respect this invariant, but do so poorly. Both setLower and setUpper are check-then-act sequences, but they do not use sufficient locking to make them atomic. If the number range holds (0, 10), and one thread calls setLower(5) while another thread calls setUpper(4), with some unlucky timing both will pass the checks in the setters and both modifications will be applied. The result is that the range now holds (5, 4)—an invalid state. So while the underlying AtomicIntegers are thread-safe, the composite class is not. Because the underlying state variables lower and upper are not independent, NumberRange cannot simply delegate thread safety to its thread-safe state variables.
NumberRange could be made thread-safe by using locking to maintain its invariants, such as guarding lower and upper with a common lock. It must also avoid publishing lower and upper to prevent clients from subverting its invariants.
If a class has compound actions, as NumberRange does, delegation alone is again not a suitable approach for thread safety. In these cases, the class must provide its own locking to ensure that compound actions are atomic, unless the entire compound action can also be delegated to the underlying state variables.
If a class is composed of multiple independent thread-safe state variables and has no operations that have any invalid state transitions, then it can delegate thread safety to the underlying state variables.