PHP底层的高性能数据结构与实现方法,需要具体代码示例
随着互联网应用的不断发展,PHP已经成为了一种广泛使用的服务器端脚本语言。然而,在大规模的Web应用中,PHP的性能问题成为了一个不容忽视的问题,很多大型网站都出现了性能瓶颈和系统崩溃的情况。
为了提高PHP的性能,我们需要了解PHP底层的高性能数据结构与实现方法。本文将介绍PHP的几种高性能数据结构及其实现方法,并提供相应的代码示例,帮助读者深入理解PHP的性能优化。
在PHP中,数组是最常用的数据结构之一。不过,PHP的数组实现采用了哈希表的方式,这会带来一些性能上的开销,特别是在对大量数据进行迭代操作时。
为了提高PHP的数组性能,我们可以使用C语言扩展来实现。
下面是一个简单的PHP扩展示例,该扩展实现了一个高性能的哈希表,可以用于存储大量的数据,并且支持各种数据类型的存储和访问。
typedef struct { zend_ulong h; zval data; } hashtable_entry; typedef struct { hashtable_entry *table; zend_ulong num_entries; zend_ulong max_entries; zend_ulong rehash_pos; zend_ulong rehash_size; } hashtable; typedef struct { zend_object std; hashtable *ht; } hash_table_object; static zend_object *hash_table_object_new(zend_class_entry *class_type) { hash_table_object *intern = (hash_table_object *)ecalloc(1, sizeof(hash_table_object)); zend_object_std_init(&intern->std, class_type); object_properties_init(&intern->std, class_type); intern->std.handlers = &hash_table_object_handlers; intern->ht = (hashtable *)emalloc(sizeof(hashtable)); return &intern->std; } static void hash_table_object_free(zend_object *object) { hash_table_object *intern = hash_table_object_from_obj(object); if (intern->ht != NULL) { zend_ulong i; for (i = 0; i < intern->ht->max_entries; i++) { zval_dtor( &intern->ht->table[i].data ); } efree(intern->ht->table); efree(intern->ht); } zend_object_std_dtor(object); } static void hash_table_put(hash_table_object *intern, zval *key, zval *value) { zend_ulong idx; zend_string *str_key; if (Z_TYPE_P(key) == IS_STRING) { str_key = Z_STR_P(key); idx = zend_inline_hash_func( str_key->val, str_key->len ) % intern->ht->max_entries; } else if (Z_TYPE_P(key) == IS_LONG) { idx = Z_LVAL_P(key) % intern->ht->max_entries; } else if (Z_TYPE_P(key) == IS_DOUBLE) { idx = zend_dval_to_lval(Z_DVAL_P(key)) % intern->ht->max_entries; } else if (Z_TYPE_P(key) == IS_TRUE) { idx = 1 % intern->ht->max_entries; } else { idx = 0; } if (Z_TYPE(intern->ht->table[idx].data) != IS_NULL) { zval_dtor( &intern->ht->table[idx].data ); } intern->ht->table[idx].h = idx; ZVAL_COPY_VALUE( &intern->ht->table[idx].data, value ); } static zval *hash_table_get(hash_table_object *intern, zval *key) { zend_ulong idx; zend_string *str_key; if (Z_TYPE_P(key) == IS_STRING) { str_key = Z_STR_P(key); idx = zend_inline_hash_func( str_key->val, str_key->len ) % intern->ht->max_entries; } else if (Z_TYPE_P(key) == IS_LONG) { idx = Z_LVAL_P(key) % intern->ht->max_entries; } else if (Z_TYPE_P(key) == IS_DOUBLE) { idx = zend_dval_to_lval(Z_DVAL_P(key)) % intern->ht->max_entries; } else if (Z_TYPE_P(key) == IS_TRUE) { idx = 1 % intern->ht->max_entries; } else { idx = 0; } if (Z_TYPE(intern->ht->table[idx].data) == IS_NULL) { return NULL; } else { return &intern->ht->table[idx].data; } } static zend_class_entry *hash_table_class_entry; static zend_function_entry hash_table_methods[] = { PHP_ME(HashTable, put, arginfo_hashtable_put, ZEND_ACC_PUBLIC) PHP_ME(HashTable, get, arginfo_hashtable_get, ZEND_ACC_PUBLIC) PHP_FE_END }; static zend_object_handlers hash_table_object_handlers; static void hash_table_object_init(zend_class_entry *class_type) { hash_table_object_handlers = *zend_get_std_object_handlers(); hash_table_object_handlers.offset = XtOffsetOf(hash_table_object, std); hash_table_object_handlers.free_obj = hash_table_object_free; hash_table_object_handlers.clone_obj = zend_objects_clone_obj; } PHP_MINIT_FUNCTION(hash_table) { zend_class_entry ce; INIT_CLASS_ENTRY(ce, "HashTable", hash_table_methods); hash_table_class_entry = zend_register_internal_class(&ce); hash_table_class_entry->create_object = hash_table_object_new; hash_table_object_init( hash_table_class_entry ); return SUCCESS; }
使用上述扩展,可以极大地提高PHP数组的性能,尤其适用于大规模数据的处理。
堆是一种常用的数据结构,可以用于优先队列、排序等操作。为了提高PHP的性能,我们可以使用C语言扩展来实现堆数据结构。
下面是一个简单的PHP扩展示例,该扩展实现了一个最小堆,可以用于排序、搜索等操作。
typedef struct { zend_ulong size; zend_ulong capacity; zval *data; } min_heap; static min_heap *min_heap_new() { min_heap *heap = emalloc(sizeof(min_heap)); heap->size = 0; heap->capacity = 4; heap->data = emalloc(sizeof(zval) * heap->capacity); return heap; } static void min_heap_free(min_heap *heap) { zend_ulong i; for (i = 0; i < heap->size; i++) { zval_dtor(&heap->data[i]); } efree(heap->data); efree(heap); } static void min_heap_push(min_heap *heap, zval *value) { if (heap->size + 1 > heap->capacity) { heap->capacity *= 2; heap->data = erealloc(heap->data, sizeof(zval) * heap->capacity); } zend_ulong hole = ++heap->size; while (hole > 1 && zend_is_smaller( value, &heap->data[hole / 2] )) { ZVAL_COPY( &heap->data[hole], &heap->data[hole / 2] ); hole /= 2; } ZVAL_COPY( &heap->data[hole], value ); } static void min_heap_pop(min_heap *heap) { zend_ulong hole = 1; zend_ulong child = 2; zval tmp; ZVAL_NULL(&tmp); zval_dtor( &heap->data[1] ); heap->data[1] = heap->data[heap->size--]; while (child <= heap->size) { if (child < heap->size && zend_is_smaller(&heap->data[child + 1], &heap->data[child])) { child++; } if (zend_is_smaller(&heap->data[child], &heap->data[hole])) { ZVAL_COPY( &tmp, &heap->data[hole] ); ZVAL_COPY( &heap->data[hole], &heap->data[child] ); ZVAL_COPY( &heap->data[child], &tmp ); } else { break; } hole = child; child *= 2; } } static zval *min_heap_top(min_heap *heap) { if (heap->size > 0) { return &heap->data[1]; } else { return NULL; } } static zend_class_entry *min_heap_class_entry; static zend_function_entry min_heap_methods[] = { PHP_ME(MinHeap, push, arginfo_min_heap_push, ZEND_ACC_PUBLIC) PHP_ME(MinHeap, pop, arginfo_min_heap_pop, ZEND_ACC_PUBLIC) PHP_ME(MinHeap, top, arginfo_min_heap_top, ZEND_ACC_PUBLIC) PHP_FE_END }; static zend_object_handlers min_heap_object_handlers; static void min_heap_object_init(zend_class_entry *class_type) { min_heap_object_handlers = *zend_get_std_object_handlers(); min_heap_object_handlers.offset = XtOffsetOf(min_heap_object, std); min_heap_object_handlers.free_obj = min_heap_object_free; min_heap_object_handlers.clone_obj = zend_objects_clone_obj; } static zend_object *min_heap_object_new(zend_class_entry *class_type) { min_heap_object *intern = (min_heap_object *)ecalloc(1, sizeof(min_heap_object)); zend_object_std_init(&intern->std, class_type); object_properties_init(&intern->std, class_type); intern->std.handlers = &min_heap_object_handlers; intern->heap = min_heap_new(); return &intern->std; } static void min_heap_object_free(zend_object *object) { min_heap_object *intern = min_heap_object_from_obj(object); if (intern->heap != NULL) { min_heap_free(intern->heap); } zend_object_std_dtor(object); } PHP_MINIT_FUNCTION(min_heap) { zend_class_entry ce; INIT_CLASS_ENTRY(ce, "MinHeap", min_heap_methods); min_heap_class_entry = zend_register_internal_class(&ce); min_heap_class_entry->create_object = min_heap_object_new; min_heap_object_init( min_heap_class_entry ); return SUCCESS; }
使用上述扩展,可以轻松地实现PHP中的堆数据结构,并提高PHP的排序、搜索等操作的性能。
PHP中的队列是一种常见的数据结构,可以用于多线程任务的管理等应用场景。为了提高PHP的性能,我们可以使用C语言扩展来实现队列数据结构。
下面是一个简单的PHP扩展示例,该扩展实现了一个高性能的队列,可以用于多线程任务的处理等应用场景。
typedef struct { zend_ulong head; zend_ulong tail; zend_ulong size; zend_ulong capacity; zval *data; } queue; static queue *queue_new() { queue *q = emalloc(sizeof(queue)); q->head = 0; q->tail = 0; q->size = 0; q->capacity = 4; q->data = emalloc(sizeof(zval) * q->capacity); return q; } static void queue_free(queue *q) { zend_ulong i; for (i = q->head; i != q->tail; i = (i + 1) % q->capacity) { zval_dtor(&q->data[i]); } efree(q->data); efree(q); } static void queue_push(queue *q, zval *val) { if (q->size >= q->capacity) { zend_ulong new_capacity = q->capacity * 2; zval *new_data = emalloc(sizeof(zval) * new_capacity); zend_ulong i; for (i = q->head; i != q->tail; i = (i + 1) % q->capacity) { ZVAL_COPY(&new_data[i], &q->data[i]); } efree(q->data); q->data = new_data; q->capacity = new_capacity; q->head = 0; q->tail = q->size; } ZVAL_COPY(&q->data[q->tail], val); q->tail = (q->tail + 1) % q->capacity; q->size++; } static void queue_pop(queue *q) { if (q->size > 0) { zval_dtor(&q->data[q->head]); q->head = (q->head + 1) % q->capacity; q->size--; } } static zval *queue_front(queue *q) { if (q->size > 0) { return &q->data[q->head]; } else { return NULL; } } static zend_class_entry *queue_class_entry; static zend_function_entry queue_methods[] = { PHP_ME(Queue, push, arginfo_queue_push, ZEND_ACC_PUBLIC) PHP_ME(Queue, pop, arginfo_queue_pop, ZEND_ACC_PUBLIC) PHP_ME(Queue, front, arginfo_queue_front, ZEND_ACC_PUBLIC) PHP_FE_END }; static zend_object_handlers queue_object_handlers; static void queue_object_init(zend_class_entry *class_type) { queue_object_handlers = *zend_get_std_object_handlers(); queue_object_handlers.offset = XtOffsetOf(queue_object, std); queue_object_handlers.free_obj = queue_object_free; queue_object_handlers.clone_obj = zend_objects_clone_obj; } static zend_object *queue_object_new(zend_class_entry *class_type) { queue_object *intern = (queue_object *)ecalloc(1, sizeof(queue_object)); zend_object_std_init(&intern->std, class_type); object_properties_init(&intern->std, class_type); intern->std.handlers = &queue_object_handlers; intern->q = queue_new(); return &intern->std; } static void queue_object_free(zend_object *object) { queue_object *intern = queue_object_from_obj(object); if (intern->q != NULL) { queue_free(intern->q); } zend_object_std_dtor(object); } PHP_MINIT_FUNCTION(queue) { zend_class_entry ce; INIT_CLASS_ENTRY(ce, "Queue", queue_methods); queue_class_entry = zend_register_internal_class(&ce); queue_class_entry->create_object = queue_object_new; queue_object_init( queue_class_entry ); return SUCCESS; }
使用上述扩展,可以轻松地实现PHP中的队列数据结构,并提高PHP多线程任务的处理等应用场景的性能。
总结
经过上述的介绍,我们了解了PHP底层的高性能数据结构及其实现方法,并提供了相应的代码示例。通过使用扩展实现高性能数据结构,可以极大地提高PHP的性能,特别是在处理大量数据和多线程任务的情况下,更是可以显著地提升系统的性能。
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