Entry Processor

Hazelcast supports entry processing. An entry processor is a function that executes your code on a map entry in an atomic way.

An entry processor is a good option if you perform bulk processing on an IMap. Usually, you perform a loop of keys: executing IMap.get(key), mutating the value, and finally putting the entry back in the map using IMap.put(key,value). If you perform this process from a client or from a member where the keys do not exist, you effectively perform 2 network hops for each update: the first to retrieve the data and the second to update the mutated value.

If you are doing the above, you should consider using entry processors. An entry processor executes a read and updates upon the member where the data resides. This eliminates the costly network hops described previously.

Entry Processor Overview

An entry processor enables fast in-memory operations on your map without you having to worry about locks or concurrency issues. It can be applied to a single map entry or to all map entries. It supports choosing target entries using predicates. You do not need any explicit lock on entry: Hazelcast locks the entry, runs the EntryProcessor, and then unlocks the entry.

Hazelcast sends the entry processor to each cluster member and these members apply it to map entries. Therefore, if you add more members, your processing is completed faster.

If entry processing is the major operation for a map and if the map consists of complex objects, you should use OBJECT as the in-memory-format to minimize serialization cost. By default, the entry value is stored as a byte array (BINARY format). When it is stored as an object (OBJECT format), then the entry processor is applied directly on the object. In that case, no serialization or deserialization is performed. But if there is a defined event listener, a new entry value will be serialized when passing to the event publisher service.

image NOTE: When in-memory-format is OBJECT, old value of the updated entry will be null.

Entry Processing with IMap

The methods below are in the IMap interface for entry processing.

  • executeOnKey processes an entry mapped by a key.
  • executeOnKeys processes entries mapped by a collection of keys.
  • submitToKey processes an entry mapped by a key while listening to event status.
  • executeOnEntries processes all entries in a map.
  • executeOnEntries can also process all entries in a map with a defined predicate.
 * Applies the user defined EntryProcessor to the entry mapped by the key.
 * Returns the object which is the result of the process() method of EntryProcessor.
Object executeOnKey( K key, EntryProcessor entryProcessor );

 * Applies the user defined EntryProcessor to the entries mapped by the collection of keys.
 * Returns the results mapped by each key in the collection.
Map<K, Object> executeOnKeys( Set<K> keys, EntryProcessor entryProcessor );

 * Applies the user defined EntryProcessor to the entry mapped by the key with
 * specified ExecutionCallback to listen to event status and return immediately.
void submitToKey( K key, EntryProcessor entryProcessor, ExecutionCallback callback );

 * Applies the user defined EntryProcessor to all entries in the map.
 * Returns the results mapped by each key in the map.
Map<K, Object> executeOnEntries( EntryProcessor entryProcessor );

 * Applies the user defined EntryProcessor to the entries in the map which satisfies 
 provided predicate.
 * Returns the results mapped by each key in the map.
Map<K, Object> executeOnEntries( EntryProcessor entryProcessor, Predicate predicate );

Entry Processing with EntryProcessor

And, here is the EntryProcessor interface:

public interface EntryProcessor<K, V> extends Serializable {
  Object process( Map.Entry<K, V> entry );

  EntryBackupProcessor<K, V> getBackupProcessor();

image NOTE: If you want to execute a task on a single key, you can also use executeOnKeyOwner provided by Executor Service. But, in this case, you need to perform a lock and serialization.

When using executeOnEntries method, if the number of entries is high and you do need the results, then returning null in process() method is a good practice. By this way, results of the processing is not stored in the map and hence out of memory errors are eliminated.

Processing Backup Entries

If your code modifies the data, then you should also provide a processor for backup entries. This is required to prevent the primary map entries from having different values than the backups; it causes the entry processor to be applied both on the primary and backup entries.

public interface EntryBackupProcessor<K, V> extends Serializable {
    void processBackup( Map.Entry<K, V> entry );

image NOTE: You should explicitly call setValue method of Map.Entry when modifying data in Entry Processor. Otherwise, Entry Processor will be accepted as read-only.

image NOTE: An EntryProcessor instance is not thread safe. If you are storing partition specific state between invocations be sure to register this in a thread-local. A EntryProcessor instance can be used by multiple partition threads.

image NOTE: EntryProcessors run via Operation Threads that are dedicated to specific partitions. Therefore with long running EntryProcessor executions other partition operations cannot be processed, such as a 'map.put(key)'. With this is in mind it is good practice to make your EntryProcessor executions as quick as possible