Die Java HashMap unter der Haube

1. Übersicht

In diesem Artikel werden wir die beliebteste Implementierung der Map- Oberfläche aus dem Java Collections Framework genauer untersuchen und dort weitermachen, wo unser Intro-Artikel aufgehört hat.

Bevor wir mit der Implementierung beginnen, ist es wichtig darauf hinzuweisen, dass die primären Listen- und Set- Sammlungsschnittstellen die Sammlung erweitern , Map jedoch nicht.

Einfach ausgedrückt, speichert die HashMap Werte nach Schlüssel und bietet APIs zum Hinzufügen, Abrufen und Bearbeiten gespeicherter Daten auf verschiedene Arten. Die Implementierung basiert auf den Prinzipien einer Hashtabelle , die zunächst etwas komplex klingt, aber eigentlich sehr einfach zu verstehen ist.

Schlüssel-Wert-Paare werden in sogenannten Buckets gespeichert, die zusammen eine sogenannte Tabelle bilden, die eigentlich ein internes Array ist.

Sobald wir den Schlüssel unter dem ein Objekt wissen , gespeichert ist oder gespeichert werden soll, Speichern und Abrufen Operationen treten in konstanter Zeit , O (1) in einer gut dimensionierten hash map.

Um zu verstehen, wie Hash-Maps unter der Haube funktionieren, muss man den von der HashMap verwendeten Speicher- und Abrufmechanismus verstehen . Wir werden uns sehr darauf konzentrieren.

Schließlich sind Fragen zu HashMap in Interviews weit verbreitet . Dies ist also eine gute Möglichkeit, ein Interview vorzubereiten oder sich darauf vorzubereiten.

2. Die put () API

Um einen Wert in einer Hash-Map zu speichern, rufen wir die put- API auf, die zwei Parameter akzeptiert. ein Schlüssel und der entsprechende Wert:

V put(K key, V value);

Wenn der Map unter einem Schlüssel ein Wert hinzugefügt wird, wird die hashCode () -API des Schlüsselobjekts aufgerufen, um den sogenannten anfänglichen Hashwert abzurufen.

Um dies in Aktion zu sehen, erstellen wir ein Objekt, das als Schlüssel fungiert. Wir werden nur ein einziges Attribut erstellen, das als Hash-Code verwendet wird, um die erste Phase des Hashings zu simulieren:

public class MyKey { private int id; @Override public int hashCode() { System.out.println("Calling hashCode()"); return id; } // constructor, setters and getters }

Mit diesem Objekt können wir jetzt einen Wert in der Hash-Map zuordnen:

@Test public void whenHashCodeIsCalledOnPut_thenCorrect() { MyKey key = new MyKey(1); Map map = new HashMap(); map.put(key, "val"); }

Im obigen Code passiert nicht viel, aber achten Sie auf die Konsolenausgabe. In der Tat wird die hashCode- Methode aufgerufen:

Calling hashCode()

Als nächstes wird die Hash () - API der Hash-Map intern aufgerufen, um den endgültigen Hash-Wert unter Verwendung des anfänglichen Hash-Werts zu berechnen.

Dieser endgültige Hashwert läuft letztendlich auf einen Index im internen Array oder einen sogenannten Bucket-Speicherort hinaus.

Die Hash- Funktion von HashMap sieht folgendermaßen aus:

static final int hash(Object key) { int h; return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16); }

Was wir hier beachten sollten, ist nur die Verwendung des Hash-Codes aus dem Schlüsselobjekt, um einen endgültigen Hash-Wert zu berechnen.

In der Put- Funktion wird der endgültige Hash-Wert folgendermaßen verwendet:

public V put(K key, V value) { return putVal(hash(key), key, value, false, true); }

Beachten Sie, dass eine interne putVal- Funktion aufgerufen wird und der endgültige Hashwert als erster Parameter angegeben wird.

Man könnte sich fragen, warum der Schlüssel in dieser Funktion wieder verwendet wird, da wir ihn bereits zur Berechnung des Hashwerts verwendet haben.

Der Grund dafür ist, dass Hash-Maps sowohl Schlüssel als auch Wert in der Bucket-Position als Map.Entry- Objekt speichern .

Wie bereits erwähnt, erweitern alle Java-Sammlungsframework-Schnittstellen die Sammlungsschnittstelle , Map jedoch nicht. Vergleichen Sie die Deklaration der Map-Schnittstelle, die wir zuvor gesehen haben, mit der der Set- Schnittstelle:

public interface Set extends Collection

Der Grund dafür ist, dass Karten nicht genau wie andere Sammlungen einzelne Elemente speichern, sondern eine Sammlung von Schlüssel-Wert-Paaren.

Daher sind die generischen Methoden der Sammlungsschnittstelle wie add , toArray in Bezug auf Map nicht sinnvoll .

Das Konzept, das wir in den letzten drei Absätzen behandelt haben, ist eine der beliebtesten Interviewfragen zum Java Collections Framework . Es lohnt sich also zu verstehen.

Ein besonderes Attribut der Hash-Map ist, dass sie Nullwerte und Nullschlüssel akzeptiert :

@Test public void givenNullKeyAndVal_whenAccepts_thenCorrect(){ Map map = new HashMap(); map.put(null, null); }

When a null key is encountered during a put operation, it is automatically assigned a final hash value of 0, which means it becomes the first element of the underlying array.

This also means that when the key is null, there is no hashing operation and therefore, the hashCode API of the key is not invoked, ultimately avoiding a null pointer exception.

During a put operation, when we use a key that was already used previously to store a value, it returns the previous value associated with the key:

@Test public void givenExistingKey_whenPutReturnsPrevValue_thenCorrect() { Map map = new HashMap(); map.put("key1", "val1"); String rtnVal = map.put("key1", "val2"); assertEquals("val1", rtnVal); }

otherwise, it returns null:

@Test public void givenNewKey_whenPutReturnsNull_thenCorrect() { Map map = new HashMap(); String rtnVal = map.put("key1", "val1"); assertNull(rtnVal); }

When put returns null, it could also mean that the previous value associated with the key is null, not necessarily that it's a new key-value mapping:

@Test public void givenNullVal_whenPutReturnsNull_thenCorrect() { Map map = new HashMap(); String rtnVal = map.put("key1", null); assertNull(rtnVal); }

The containsKey API can be used to distinguish between such scenarios as we will see in the next subsection.

3. The get API

To retrieve an object already stored in the hash map, we must know the key under which it was stored. We call the get API and pass to it the key object:

@Test public void whenGetWorks_thenCorrect() { Map map = new HashMap(); map.put("key", "val"); String val = map.get("key"); assertEquals("val", val); }

Internally, the same hashing principle is used. The hashCode() API of the key object is called to obtain the initial hash value:

@Test public void whenHashCodeIsCalledOnGet_thenCorrect() { MyKey key = new MyKey(1); Map map = new HashMap(); map.put(key, "val"); map.get(key); }

This time, the hashCode API of MyKey is called twice; once for put and once for get:

Calling hashCode() Calling hashCode()

This value is then rehashed by calling the internal hash() API to obtain the final hash value.

As we saw in the previous section, this final hash value ultimately boils down to a bucket location or an index of the internal array.

The value object stored in that location is then retrieved and returned to the calling function.

When the returned value is null, it could mean that the key object is not associated with any value in the hash map:

@Test public void givenUnmappedKey_whenGetReturnsNull_thenCorrect() { Map map = new HashMap(); String rtnVal = map.get("key1"); assertNull(rtnVal); }

Or it could simply mean that the key was explicitly mapped to a null instance:

@Test public void givenNullVal_whenRetrieves_thenCorrect() { Map map = new HashMap(); map.put("key", null); String val=map.get("key"); assertNull(val); }

To distinguish between the two scenarios, we can use the containsKey API, to which we pass the key and it returns true if and only if a mapping was created for the specified key in the hash map:

@Test public void whenContainsDistinguishesNullValues_thenCorrect() { Map map = new HashMap(); String val1 = map.get("key"); boolean valPresent = map.containsKey("key"); assertNull(val1); assertFalse(valPresent); map.put("key", null); String val = map.get("key"); valPresent = map.containsKey("key"); assertNull(val); assertTrue(valPresent); }

For both cases in the above test, the return value of the get API call is null but we are able to distinguish which one is which.

4. Collection Views in HashMap

HashMap offers three views that enable us to treat its keys and values as another collection. We can get a set of all keys of the map:

@Test public void givenHashMap_whenRetrievesKeyset_thenCorrect() { Map map = new HashMap(); map.put("name", "baeldung"); map.put("type", "blog"); Set keys = map.keySet(); assertEquals(2, keys.size()); assertTrue(keys.contains("name")); assertTrue(keys.contains("type")); }

The set is backed by the map itself. So any change made to the set is reflected in the map:

@Test public void givenKeySet_whenChangeReflectsInMap_thenCorrect() { Map map = new HashMap(); map.put("name", "baeldung"); map.put("type", "blog"); assertEquals(2, map.size()); Set keys = map.keySet(); keys.remove("name"); assertEquals(1, map.size()); }

We can also obtain a collection view of the values:

@Test public void givenHashMap_whenRetrievesValues_thenCorrect() { Map map = new HashMap(); map.put("name", "baeldung"); map.put("type", "blog"); Collection values = map.values(); assertEquals(2, values.size()); assertTrue(values.contains("baeldung")); assertTrue(values.contains("blog")); }

Just like the key set, any changes made in this collection will be reflected in the underlying map.

Finally, we can obtain a set view of all entries in the map:

@Test public void givenHashMap_whenRetrievesEntries_thenCorrect() { Map map = new HashMap(); map.put("name", "baeldung"); map.put("type", "blog"); Set
    
      entries = map.entrySet(); assertEquals(2, entries.size()); for (Entry e : entries) }
    

Remember that a hash map specifically contains unordered elements, therefore we assume any order when testing the keys and values of entries in the for each loop.

Many times, you will use the collection views in a loop as in the last example, and more specifically using their iterators.

Just remember that the iterators for all the above views are fail-fast.

If any structural modification is made on the map, after the iterator has been created, a concurrent modification exception will be thrown:

@Test(expected = ConcurrentModificationException.class) public void givenIterator_whenFailsFastOnModification_thenCorrect() { Map map = new HashMap(); map.put("name", "baeldung"); map.put("type", "blog"); Set keys = map.keySet(); Iterator it = keys.iterator(); map.remove("type"); while (it.hasNext()) { String key = it.next(); } }

The only allowed structural modification is a remove operation performed through the iterator itself:

public void givenIterator_whenRemoveWorks_thenCorrect() { Map map = new HashMap(); map.put("name", "baeldung"); map.put("type", "blog"); Set keys = map.keySet(); Iterator it = keys.iterator(); while (it.hasNext()) { it.next(); it.remove(); } assertEquals(0, map.size()); }

The final thing to remember about these collection views is the performance of iterations. This is where a hash map performs quite poorly compared with its counterparts linked hash map and tree map.

Iteration over a hash map happens in worst case O(n) where n is the sum of its capacity and the number of entries.

5. HashMap Performance

The performance of a hash map is affected by two parameters: Initial Capacity and Load Factor. The capacity is the number of buckets or the underlying array length and the initial capacity is simply the capacity during creation.

The load factor or LF, in short, is a measure of how full the hash map should be after adding some values before it is resized.

The default initial capacity is 16 and default load factor is 0.75. We can create a hash map with custom values for initial capacity and LF:

Map hashMapWithCapacity=new HashMap(32); Map hashMapWithCapacityAndLF=new HashMap(32, 0.5f);

The default values set by the Java team are well optimized for most cases. However, if you need to use your own values, which is very okay, you need to understand the performance implications so that you know what you are doing.

When the number of hash map entries exceeds the product of LF and capacity, then rehashing occurs i.e. another internal array is created with twice the size of the initial one and all entries are moved over to new bucket locations in the new array.

A low initial capacity reduces space cost but increases the frequency of rehashing. Rehashing is obviously a very expensive process. So as a rule, if you anticipate many entries, you should set a considerably high initial capacity.

On the flip side, if you set the initial capacity too high, you will pay the cost in iteration time. As we saw in the previous section.

So a high initial capacity is good for a large number of entries coupled with little to no iteration.

A low initial capacity is good for few entries with a lot of iteration.

6. Collisions in the HashMap

A collision, or more specifically, a hash code collision in a HashMap, is a situation where two or more key objects produce the same final hash value and hence point to the same bucket location or array index.

This scenario can occur because according to the equals and hashCode contract, two unequal objects in Java can have the same hash code.

It can also happen because of the finite size of the underlying array, that is, before resizing. The smaller this array, the higher the chances of collision.

That said, it's worth mentioning that Java implements a hash code collision resolution technique which we will see using an example.

Keep in mind that it's the hash value of the key that determines the bucket the object will be stored in. And so, if the hash codes of any two keys collide, their entries will still be stored in the same bucket.

And by default, the implementation uses a linked list as the bucket implementation.

The initially constant time O(1)put and get operations will occur in linear time O(n) in the case of a collision. This is because after finding the bucket location with the final hash value, each of the keys at this location will be compared with the provided key object using the equals API.

To simulate this collision resolution technique, let's modify our earlier key object a little:

public class MyKey { private String name; private int id; public MyKey(int id, String name) { this.id = id; this.name = name; } // standard getters and setters @Override public int hashCode() { System.out.println("Calling hashCode()"); return id; } // toString override for pretty logging @Override public boolean equals(Object obj) { System.out.println("Calling equals() for key: " + obj); // generated implementation } }

Notice how we're simply returning the id attribute as the hash code – and thus force a collision to occur.

Also, note that we've added log statements in our equals and hashCode implementations – so that we know exactly when the logic is called.

Let's now go ahead to store and retrieve some objects that collide at some point:

@Test public void whenCallsEqualsOnCollision_thenCorrect() { HashMap map = new HashMap(); MyKey k1 = new MyKey(1, "firstKey"); MyKey k2 = new MyKey(2, "secondKey"); MyKey k3 = new MyKey(2, "thirdKey"); System.out.println("storing value for k1"); map.put(k1, "firstValue"); System.out.println("storing value for k2"); map.put(k2, "secondValue"); System.out.println("storing value for k3"); map.put(k3, "thirdValue"); System.out.println("retrieving value for k1"); String v1 = map.get(k1); System.out.println("retrieving value for k2"); String v2 = map.get(k2); System.out.println("retrieving value for k3"); String v3 = map.get(k3); assertEquals("firstValue", v1); assertEquals("secondValue", v2); assertEquals("thirdValue", v3); }

In the above test, we create three different keys – one has a unique id and the other two have the same id. Since we use id as the initial hash value, there will definitely be a collision during both storage and retrieval of data with these keys.

In addition to that, thanks to the collision resolution technique we saw earlier, we expect each of our stored values to be retrieved correctly, hence the assertions in the last three lines.

When we run the test, it should pass, indicating that collisions were resolved and we will use the logging produced to confirm that the collisions indeed occurred:

storing value for k1 Calling hashCode() storing value for k2 Calling hashCode() storing value for k3 Calling hashCode() Calling equals() for key: MyKey [name=secondKey, id=2] retrieving value for k1 Calling hashCode() retrieving value for k2 Calling hashCode() retrieving value for k3 Calling hashCode() Calling equals() for key: MyKey [name=secondKey, id=2]

Notice that during storage operations, k1 and k2 were successfully mapped to their values using only the hash code.

However, storage of k3 was not so simple, the system detected that its bucket location already contained a mapping for k2. Therefore, equals comparison was used to distinguish them and a linked list was created to contain both mappings.

Any other subsequent mapping whose key hashes to the same bucket location will follow the same route and end up replacing one of the nodes in the linked list or be added to the head of the list if equals comparison returns false for all existing nodes.

Likewise, during retrieval, k3 and k2 were equals-compared to identify the correct key whose value should be retrieved.

On a final note, from Java 8, the linked lists are dynamically replaced with balanced binary search trees in collision resolution after the number of collisions in a given bucket location exceed a certain threshold.

This change offers a performance boost, since, in the case of a collision, storage and retrieval happen in O(log n).

This section is very common in technical interviews, especially after the basic storage and retrieval questions.

7. Conclusion

In this article, we have explored HashMap implementation of Java Map interface.

Der vollständige Quellcode für alle in diesem Artikel verwendeten Beispiele befindet sich im GitHub-Projekt.