ConcurrentHashMap class is thread-safe i.e. multiple threads can operate on a single object without any complications. At a time any number of threads are applicable for a read operation without locking the ConcurrentHashMap object which is not there in HashMap.
keySet() is thread safe. However, it may act in very strange ways, as pointed out in the quote you included. As a Set , entries may appear and/or disappear at random. I.e. if you call contains twice on the same object, the two results may differ.
If two thread is accessing same partition, it will lock the segment and do its work. However, it is not blocking in the sense you are talking about in your question. It only blocks for the period of accessing (get/put etc), and lock is released once the operation is finished.
The get()
method is thread-safe, and the other users gave you useful answers regarding this particular issue.
However, although ConcurrentHashMap
is a thread-safe drop-in replacement for HashMap
, it is important to realize that if you are doing multiple operations you may have to change your code significantly. For example, take this code:
if (!map.containsKey(key))
return map.put(key, value);
else
return map.get(key);
In a multi-thread environment, this is a race condition. You have to use the ConcurrentHashMap.putIfAbsent(K key, V value)
and pay attention to the return value, which tells you if the put operation was successful or not. Read the docs for more details.
Answering to a comment that asks for clarification on why this is a race condition.
Imagine there are two threads A
, B
that are going to put two different values in the map, v1
and v2
respectively, having the same key. The key is initially not present in the map. They interleave in this way:
A
calls containsKey
and finds out that the key is not present, but is immediately suspended.B
calls containsKey
and finds out that the key is not present, and has the time to insert its value v2
.A
resumes and inserts v1
, "peacefully" overwriting (since put
is threadsafe) the value inserted by thread B
.Now thread B
"thinks" it has successfully inserted its very own value v2
, but the map contains v1
. This is really a disaster because thread B
may call v2.updateSomething()
and will "think" that the consumers of the map (e.g. other threads) have access to that object and will see that maybe important update ("like: this visitor IP address is trying to perform a DOS, refuse all the requests from now on"). Instead, the object will be soon garbage collected and lost.
It is thread-safe. However, the way it is being thread-safe may not be what you expect. There are some "hints" you can see from:
This class is fully interoperable with
Hashtable
in programs that rely on its thread safety but not on its synchronization details
To know the whole story in a more complete picture, you need to be aware of the ConcurrentMap
interface.
The original Map
provides some very basic read/update methods. Even I was able to make a thread-safe implementation of Map
; there are lots of cases that people cannot use my Map without considering my synchronization mechanism. This is a typical example:
if (!threadSafeMap.containsKey(key)) {
threadSafeMap.put(key, value);
}
This piece of code is not thread-safe, even though the map itself is. Two threads calling containsKey()
at the same time could think there is no such key they both therefore insert into the Map
.
In order to fix the problem, we need to do extra synchronization explicitly. Assume the thread-safety of my Map is achieved by synchronized keywords, you will need to do:
synchronized(threadSafeMap) {
if (!threadSafeMap.containsKey(key)) {
threadSafeMap.put(key, value);
}
}
Such extra code needs you to know about the "synchronization details" of the map. In the above example, we need to know that the synchronization is achieved by "synchronized".
ConcurrentMap
interface take this one step further. It defines some common "complex" actions that involves multiple access to map. For example, the above example is exposed as putIfAbsent()
. With these "complex" actions, users of ConcurrentMap
(in most case) don't need to synchronise actions with multiple access to the map. Hence, the implementation of Map can perform more complicated synchronization mechanism for better performance. ConcurrentHashhMap
is a good example. Thread-safety is in fact maintained by keeping separate locks for different partitions of the map. It is thread-safe because concurrent access to the map will not corrupt the internal data structure, or cause any update lost unexpected, etc.
With all the above in mind, the meaning of Javadoc will be clearer:
"Retrieval operations (including get) generally do not block" because ConcurrentHashMap
is not using "synchronized" for its thread-safety. The logic of get
itself takes care of the thread-safeness; and If you look further in the Javadoc:
The table is internally partitioned to try to permit the indicated number of concurrent updates without contention
Not only is retrieval non-blocking, even updates can happen concurrently. However, non-blocking/concurrent-updates does not means that it is thread-UNsafe. It simply means that it is using some ways other than simple "synchronized" for thread-safety.
However, as the internal synchronization mechanism is not exposed, if you want to do some complicated actions other than those provided by ConcurrentMap
, you may need to consider changing your logic, or consider not using ConcurrentHashMap
. For example:
// only remove if both key1 and key2 exists
if (map.containsKey(key1) && map.containsKey(key2)) {
map.remove(key1);
map.remove(key2);
}
ConcurrentHashmap.get()
is thread-safe, in the sense that
ConcurrentModificationException
Map
as well.HashMap
is divided into "buckets" based on hashCode
. ConcurrentHashMap
uses this fact. Its synchronization mechanism is based on blocking buckets rather than on entire Map
. This way few threads can simultaneously write to few different buckets (one thread can write to one bucket at a time).
Reading from ConcurrentHashMap
almost doesn't use synchronization. Synchronization is used when while fetching value for key, it sees null
value. Since ConcurrentHashMap
can't store null
as values (yes, aside from keys, values also can't be null
s) it suggests that fetching null
while reading happened in the middle of initializing map entry (key-value pair) by another thread: when key was assigned, but value not yet, and it still holds default null.
In such case reading thread will need to wait until entry will be written fully.
So results from read()
will be based on current state of map. If you read value of key that was in the middle of updating you will likely get old value since writing process hasn't finished yet.
get() in ConcurrentHashMap is thread-safe because It reads the value which is Volatile. And in cases when value is null of any key, then get() method waits till it gets the lock and then it reads the updated value.
When put()
method is updating CHM, then it sets the value of that key to null, and then it creates a new entry and updates the CHM. This null value is used by get()
method as signal that another thread is updating the CHM with the same key.
It just means that when one thread is updating and one thread is reading there is no guarantee that the one that called the ConcurrentHashMap method first, in time, will have their operation occur first.
Think about an update on the item telling where Bob is. If one thread asks where Bob is at about the same time that another thread updates to say he came 'inside', you can't predict whether the reader thread will get Bob's status as 'inside' or 'outside'. Even if the update thread calls the method first, the reader thread might get the 'outside' status.
The threads will not cause each other problems. The code is ThreadSafe.
One thread won't go into an infinite loop or start generating wierd NullPointerExceptions or get "itside" with half of the old status and half of the new.
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