Java Question
How ConcurrentHashMap works in Java

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Java Question

How ConcurrentHashMap works in Java

Accepted Answer

According to ConcurrentHashMap Oracle docs,

The constructor of ConcurrentHashMap looks like this :

public ConcurrentHashMap (int initialCapacity, float loadFactor, int concurrencyLevel)

So the above line creates a new, empty map with the specified initial capacity, load factor and concurrency level.
where,
Important Parameters to consider from ConcurrentHashMap Constructor :

initialCapacity - the initial capacity. The implementation performs internal sizing to accommodate this many elements.

concurrencyLevel - the estimated number of concurrently updating threads. The implementation performs internal
sizing to try to accommodate this many threads.

In the ConcurrentHashMap Api , you will find the following constants.

static final int DEFAULT_INITIAL_CAPACITY = 16;
static final int DEFAULT_CONCURRENCY_LEVEL = 16;

initial capacity parameter and concurrency level parameters of ConcurrentHashMap constructor (or Object) are set to
16 by default.

1) Thus, instead of a map wide lock, ConcurrentHashMap maintains a list of 16 locks by default ( number of locks
equal to the initial capacity , which is by default 16) each of which is used to lock on a single bucket of the Map.

2) This indicates that 16 threads (number of threads equal to the concurrency level , which is by default 16) can
modify the collection at the same time , given ,each thread works on different bucket.

3) So unlike hashtable, we perform any sort of operation ( update ,delete ,read ,create) without locking on entire map
in ConcurrentHashMap.

Retrieval operations (including get) generally do not block, so may overlap with update operations (including put and
remove). Retrievals reflect the results of the most recently completed update operations holding upon their onset.

1) The allowed concurrency among update operations is guided by the optional concurrencyLevel constructor
argument (default 16), which is used as a hint for internal sizing.

2) The table is internally partitioned to try to permit the indicated number of concurrent updates without contention.

3) Because placement in hash tables is essentially random, the actual concurrency will vary. Ideally, you should
choose a value to accommodate as many threads as will ever concurrently modify the table.

4) Using a significantly higher value than you need can waste space and time, and a significantly lower
value can lead to thread contention

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