Introducción a la clase Java.util.Hashtable

1. Información general

Hashtable es la implementación más antigua de una estructura de datos de tabla hash en Java. El HashMap es la segunda aplicación, que se introdujo en JDK 1.2.

Ambas clases proporcionan una funcionalidad similar, pero también hay pequeñas diferencias, que exploraremos en este tutorial.

2. Cuándo usar Hashtable

Digamos que tenemos un diccionario, donde cada palabra tiene su definición. Además, necesitamos obtener, insertar y eliminar palabras del diccionario rápidamente.

Por lo tanto, Hashtable (o HashMap ) tiene sentido. Las palabras serán las claves en la tabla hash , ya que se supone que son únicas. Las definiciones, por otro lado, serán los valores.

3. Ejemplo de uso

Continuemos con el ejemplo del diccionario. Modelaremos Word como clave:

public class Word { private String name; public Word(String name) { this.name = name; } // ... }

Digamos que los valores son cadenas . Ahora podemos crear una tabla hash :

Hashtable table = new Hashtable();

Primero, agreguemos una entrada:

Word word = new Word("cat"); table.put(word, "an animal");

Además, para obtener una entrada:

String definition = table.get(word);

Finalmente, eliminemos una entrada:

definition = table.remove(word);

Hay muchos más métodos en la clase y describiremos algunos de ellos más adelante.

Pero primero, hablemos de algunos requisitos para el objeto clave.

4. La importancia de hashCode ()

Para ser utilizado como clave en una Hashtable , el objeto no debe violar el contrato hashCode () . En resumen, los objetos iguales deben devolver el mismo código. Para entender por qué, veamos cómo está organizada la tabla hash.

Hashtable usa una matriz. Cada posición en la matriz es un "depósito" que puede ser nulo o contener uno o más pares clave-valor. Se calcula el índice de cada par.

Pero, ¿por qué no almacenar elementos secuencialmente, agregando nuevos elementos al final de la matriz?

El punto es que encontrar un elemento por índice es mucho más rápido que iterar a través de los elementos con la comparación secuencialmente. Por lo tanto, necesitamos una función que asigne claves a índices.

4.1. Tabla de direcciones directas

El ejemplo más simple de tal mapeo es la tabla de direcciones directas. Aquí las claves se utilizan como índices:

index(k)=k, where k is a key

Las claves son únicas, es decir, cada depósito contiene un par clave-valor. Esta técnica funciona bien para claves enteras cuando el rango posible de ellas es razonablemente pequeño.

Pero tenemos dos problemas aquí:

  • Primero, nuestras claves no son números enteros, sino objetos de Word
  • En segundo lugar, si fueran números enteros, nadie garantizaría que fueran pequeños. Imagina que las claves son 1, 2 y 1000000. Tendremos una gran variedad de tamaño 1000000 con solo tres elementos, y el resto será un espacio desperdiciado.

El método hashCode () resuelve el primer problema.

La lógica para la manipulación de datos en Hashtable resuelve el segundo problema.

Discutamos esto en profundidad.

4.2. Método hashCode ()

Cualquier objeto Java hereda el método hashCode () que devuelve un valor int . Este valor se calcula a partir de la dirección de memoria interna del objeto. Por defecto, hashCode () devuelve enteros distintos para objetos distintos.

Por lo tanto, cualquier objeto clave se puede convertir en un número entero usando hashCode () . Pero este número entero puede ser grande.

4.3. Reducir el rango

Los métodos get () , put () y remove () contienen el código que resuelve el segundo problema: reducir el rango de números enteros posibles.

La fórmula calcula un índice para la clave:

int index = (hash & 0x7FFFFFFF) % tab.length;

Donde tab.length es el tamaño de la matriz y hash es un número devuelto por el método hashCode () de la clave .

Como podemos ver, index es un recordatorio del hash de división por el tamaño de la matriz . Tenga en cuenta que los códigos hash iguales producen el mismo índice.

4.4. Colisiones

Además, incluso diferentes códigos hash pueden producir el mismo índice . Nos referimos a esto como una colisión. Para resolver colisiones, Hashtable almacena una LinkedList de pares clave-valor.

Esta estructura de datos se denomina tabla hash con encadenamiento.

4.5. Factor de carga

It is easy to guess that collisions slow down operations with elements. To get an entry it is not enough to know its index, but we need to go through the list and perform a comparison with each item.

Therefore it's important to reduce the number of collisions. The bigger is an array, the smaller is the chance of a collision. The load factor determines the balance between the array size and the performance. By default, it's 0.75 which means that the array size doubles when 75% of the buckets become not empty. This operation is executed by rehash() method.

But let's return to the keys.

4.6. Overriding equals() and hashCode()

When we put an entry into a Hashtable and get it out of it, we expect that the value can be obtained not only with same the instance of the key but also with an equal key:

Word word = new Word("cat"); table.put(word, "an animal"); String extracted = table.get(new Word("cat"));

To set the rules of equality, we override the key’s equals() method:

public boolean equals(Object o) { if (o == this) return true; if (!(o instanceof Word)) return false; Word word = (Word) o; return word.getName().equals(this.name); }

But if we don’t override hashCode() when overriding equals() then two equal keys may end up in the different buckets because Hashtable calculates the key’s index using its hash code.

Let’s take a close look at the above example. What happens if we don’t override hashCode()?

  • Two instances of Word are involved here – the first is for putting the entry and the second is for getting the entry. Although these instances are equal, their hashCode() method return different numbers
  • The index for each key is calculated by the formula from section 4.3. According to this formula, different hash codes may produce different indexes
  • This means that we put the entry into one bucket and then try to get it out from the other bucket. Such logic breaks Hashtable

Equal keys must return equal hash codes, that’s why we override the hashCode() method:

public int hashCode() { return name.hashCode(); }

Note that it's also recommended to make not equal keys return different hash codes, otherwise they end up in the same bucket. This will hit the performance, hence, losing some of the advantages of a Hashtable.

Also, note that we don’t care about the keys of String, Integer, Long or another wrapper type. Both equal() and hashCode() methods are already overridden in wrapper classes.

5. Iterating Hashtables

There are a few ways to iterate Hashtables. In this section well talk about them and explain some of the implications.

5.1. Fail Fast: Iteration

Fail-fast iteration means that if a Hashtable is modified after its Iterator is created, then the ConcurrentModificationException will be thrown. Let's demonstrate this.

First, we'll create a Hashtable and add entries to it:

Hashtable table = new Hashtable(); table.put(new Word("cat"), "an animal"); table.put(new Word("dog"), "another animal");

Second, we'll create an Iterator:

Iterator it = table.keySet().iterator();

And third, we'll modify the table:

table.remove(new Word("dog"));

Now if we try to iterate through the table, we'll get a ConcurrentModificationException:

while (it.hasNext()) { Word key = it.next(); }
java.util.ConcurrentModificationException at java.util.Hashtable$Enumerator.next(Hashtable.java:1378)

ConcurrentModificationException helps to find bugs and thus avoid unpredictable behavior, when, for example, one thread is iterating through the table, and another one is trying to modify it at the same time.

5.2. Not Fail Fast: Enumeration

Enumeration in a Hashtable is not fail-fast. Let's look at an example.

First, let's create a Hashtable and add entries to it:

Hashtable table = new Hashtable(); table.put(new Word("1"), "one"); table.put(new Word("2"), "two");

Second, let's create an Enumeration:

Enumeration enumKey = table.keys();

Third, let's modify the table:

table.remove(new Word("1"));

Now if we iterate through the table it won't throw an exception:

while (enumKey.hasMoreElements()) { Word key = enumKey.nextElement(); }

5.3. Unpredictable Iteration Order

Also, note that iteration order in a Hashtable is unpredictable and does not match the order in which the entries were added.

This is understandable as it calculates each index using the key's hash code. Moreover, rehashing takes place from time to time, rearranging the order of the data structure.

Hence, let's add some entries and check the output:

Hashtable table = new Hashtable(); table.put(new Word("1"), "one"); table.put(new Word("2"), "two"); // ... table.put(new Word("8"), "eight"); Iterator
    
      it = table.entrySet().iterator(); while (it.hasNext()) { Map.Entry entry = it.next(); // ... } }
    
five four three two one eight seven

6. Hashtable vs. HashMap

Hashtable and HashMap provide very similar functionality.

Both of them provide:

  • Fail-fast iteration
  • Unpredictable iteration order

But there are some differences too:

  • HashMap doesn't provide any Enumeration, while Hashtable provides not fail-fast Enumeration
  • Hashtable doesn't allow null keys and null values, while HashMap do allow one null key and any number of null values
  • Hashtable‘s methods are synchronized while HashMaps‘s methods are not

7. Hashtable API in Java 8

Java 8 has introduced new methods which help make our code cleaner. In particular, we can get rid of some if blocks. Let's demonstrate this.

7.1. getOrDefault()

Let's say we need to get the definition of the word “dogand assign it to the variable if it is on the table. Otherwise, assign “not found” to the variable.

Before Java 8:

Word key = new Word("dog"); String definition; if (table.containsKey(key)) { definition = table.get(key); } else { definition = "not found"; }

After Java 8:

definition = table.getOrDefault(key, "not found");

7.2. putIfAbsent()

Let's say we need to put a word “cat only if it's not in the dictionary yet.

Before Java 8:

if (!table.containsKey(new Word("cat"))) { table.put(new Word("cat"), definition); }

After Java 8:

table.putIfAbsent(new Word("cat"), definition);

7.3. boolean remove()

Let's say we need to remove the word “cat” but only if it's definition is “an animal”.

Before Java 8:

if (table.get(new Word("cat")).equals("an animal")) { table.remove(new Word("cat")); }

After Java 8:

boolean result = table.remove(new Word("cat"), "an animal");

Finally, while old remove() method returns the value, the new method returns boolean.

7.4. replace()

Let's say we need to replace a definition of “cat”, but only if its old definition is “a small domesticated carnivorous mammal”.

Before Java 8:

if (table.containsKey(new Word("cat")) && table.get(new Word("cat")).equals("a small domesticated carnivorous mammal")) { table.put(new Word("cat"), definition); }

After Java 8:

table.replace(new Word("cat"), "a small domesticated carnivorous mammal", definition);

7.5. computeIfAbsent()

This method is similar to putIfabsent(). But putIfabsent() takes the value directly, and computeIfAbsent() takes a mapping function. It calculates the value only after it checks the key, and this is more efficient, especially if the value is difficult to obtain.

table.computeIfAbsent(new Word("cat"), key -> "an animal");

Hence, the above line is equivalent to:

if (!table.containsKey(cat)) { String definition = "an animal"; // note that calculations take place inside if block table.put(new Word("cat"), definition); }

7.6. computeIfPresent()

This method is similar to the replace() method. But, again, replace() takes the value directly, and computeIfPresent() takes a mapping function. It calculates the value inside of the if block, that's why it's more efficient.

Let's say we need to change the definition:

table.computeIfPresent(cat, (key, value) -> key.getName() + " - " + value);

Hence, the above line is equivalent to:

if (table.containsKey(cat)) { String concatination=cat.getName() + " - " + table.get(cat); table.put(cat, concatination); }

7.7. compute()

Now we'll solve another task. Let's say we have an array of String, where the elements are not unique. Also, let's calculate how many occurrences of a String we can get in the array. Here is the array:

String[] animals = { "cat", "dog", "dog", "cat", "bird", "mouse", "mouse" };

Also, we want to create a Hashtable which contains an animal as a key and the number of its occurrences as a value.

Here is a solution:

Hashtable table = new Hashtable(); for (String animal : animals) { table.compute(animal, (key, value) -> (value == null ? 1 : value + 1)); }

Finally, let's make sure, that the table contains two cats, two dogs, one bird and two mouses:

assertThat(table.values(), hasItems(2, 2, 2, 1));

7.8. merge()

There is another way to solve the above task:

for (String animal : animals) { table.merge(animal, 1, (oldValue, value) -> (oldValue + value)); }

The second argument, 1, is the value which is mapped to the key if the key is not yet on the table. If the key is already in the table, then we calculate it as oldValue+1.

7.9. foreach()

This is a new way to iterate through the entries. Let's print all the entries:

table.forEach((k, v) -> System.out.println(k.getName() + " - " + v)

7.10. replaceAll()

Additionally, we can replace all the values without iteration:

table.replaceAll((k, v) -> k.getName() + " - " + v);

8. Conclusion

In this article, we've described the purpose of the hash table structure and showed how to complicate a direct-address table structure to get it.

Además, hemos cubierto qué son las colisiones y qué es un factor de carga en una tabla hash. Además, hemos aprendido por qué anular equals () y hashCode () para objetos clave.

Finalmente, hemos hablado sobre las propiedades de Hashtable y la API específica de Java 8.

Como de costumbre, el código fuente completo está disponible en Github.