java hashmap 是怎么序列化的？

深藏阁楼爱情的钟 2023-03-02 10:16 3阅读 0赞

[Java中HashMap关键字transient的疑惑][Java_HashMap_transient]  
[transient HashMap使用目的分析][transient HashMap]  
[HashMap实现序列化][HashMap]

hashMap 在序列化的时候用的是readObject和wirteObject，这两个方法。

/**
         * Save the state of the <tt>HashMap</tt> instance to a stream (i.e.,
         * serialize it).
         *
         * @serialData The <i>capacity</i> of the HashMap (the length of the
         *             bucket array) is emitted (int), followed by the
         *             <i>size</i> (an int, the number of key-value
         *             mappings), followed by the key (Object) and value (Object)
         *             for each key-value mapping.  The key-value mappings are
         *             emitted in no particular order.
         */
        private void writeObject(java.io.ObjectOutputStream s)
            throws IOException {
            int buckets = capacity();
            // Write out the threshold, loadfactor, and any hidden stuff
            s.defaultWriteObject();
            s.writeInt(buckets);
            s.writeInt(size);
            internalWriteEntries(s);
        }
    
        /**
         * Reconstitutes this map from a stream (that is, deserializes it).
         * @param s the stream
         * @throws ClassNotFoundException if the class of a serialized object
         *         could not be found
         * @throws IOException if an I/O error occurs
         */
        private void readObject(java.io.ObjectInputStream s)
            throws IOException, ClassNotFoundException {
            // Read in the threshold (ignored), loadfactor, and any hidden stuff
            s.defaultReadObject();
            reinitialize();
            if (loadFactor <= 0 || Float.isNaN(loadFactor))
                throw new InvalidObjectException("Illegal load factor: " +
                                                 loadFactor);
            s.readInt();                // Read and ignore number of buckets
            int mappings = s.readInt(); // Read number of mappings (size)
            if (mappings < 0)
                throw new InvalidObjectException("Illegal mappings count: " +
                                                 mappings);
            else if (mappings > 0) { // (if zero, use defaults)
                // Size the table using given load factor only if within
                // range of 0.25...4.0
                float lf = Math.min(Math.max(0.25f, loadFactor), 4.0f);
                float fc = (float)mappings / lf + 1.0f;
                int cap = ((fc < DEFAULT_INITIAL_CAPACITY) ?
                           DEFAULT_INITIAL_CAPACITY :
                           (fc >= MAXIMUM_CAPACITY) ?
                           MAXIMUM_CAPACITY :
                           tableSizeFor((int)fc));
                float ft = (float)cap * lf;
                threshold = ((cap < MAXIMUM_CAPACITY && ft < MAXIMUM_CAPACITY) ?
                             (int)ft : Integer.MAX_VALUE);
    
                // Check Map.Entry[].class since it's the nearest public type to
                // what we're actually creating.
                SharedSecrets.getJavaOISAccess().checkArray(s, Map.Entry[].class, cap);
                @SuppressWarnings({"rawtypes","unchecked"})
                Node<K,V>[] tab = (Node<K,V>[])new Node[cap];
                table = tab;
    
                // Read the keys and values, and put the mappings in the HashMap
                for (int i = 0; i < mappings; i++) {
                    @SuppressWarnings("unchecked")
                        K key = (K) s.readObject();
                    @SuppressWarnings("unchecked")
                        V value = (V) s.readObject();
                    putVal(hash(key), key, value, false, false);
                }
            }
        }

[Java_HashMap_transient]: https://segmentfault.com/q/1010000000630486
[transient HashMap]: https://blog.csdn.net/21aspnet/article/details/88954824
[HashMap]: https://blog.csdn.net/qq_27347991/article/details/54195261?utm_medium=distribute.pc_relevant.none-task-blog-OPENSEARCH-1.channel_param&depth_1-utm_source=distribute.pc_relevant.none-task-blog-OPENSEARCH-1.channel_param