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。
- 数组
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;
}
登录后复制
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
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;
}
登录后复制
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。
- 队列
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;
}
登录后复制
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。
以上就是PHP底层的高性能数据结构与实现方法的详细内容，更多请关注php中文网其它相关文章！