About three years ago I wrote an article analyzing the memory usage of arrays in PHP 5. As part of the work on the upcoming PHP 7, large parts of the Zend Engine have been rewritten with a focus on smaller data structures requiring fewer allocations. In this article I will provide an overview of the new hashtable implementation and show why it is more efficient than the previous implementation.

To measure memory utilization I am using the following script, which tests the creation of an array with 100000 distinct integers:

$startMemory = memory_get_usage (); $array = range ( 1 , 100000 ); echo memory_get_usage () - $startMemory , " bytes

" ;

The following table shows the results using PHP 5.6 and PHP 7 on 32bit and 64bit systems:

| 32 bit | 64 bit ------------------------------ PHP 5.6 | 7.37 MiB | 13.97 MiB ------------------------------ PHP 7.0 | 3.00 MiB | 4.00 MiB

In other words, arrays in PHP 7 use about 2.5 times less memory on 32bit and 3.5 on 64bit (LP64), which is quite impressive.

Introduction to hashtables

In essence PHP’s arrays are ordered dictionaries, i.e. they represent an ordered list of key/value pairs, where the key/value mapping is implemented using a hashtable.

A Hashtable is an ubiquitous data structure, which essentially solves the problem that computers can only directly represent continuous integer-indexed arrays, whereas programmers often want to use strings or other complex types as keys.

The concept behind a hashtable is very simple: The string key is run through a hashing function, which returns an integer. This integer is then used as an index into a “normal” array. The problem is that two different strings can result in the same hash, as the number of possible strings is virtually infinite while the hash is limited by the integer size. As such hashtables need to implement some kind of collision resolution mechanism.

There are two primary approaches to collision resolution: Open addressing, where elements will be stored at a different index if a collision occurs, and chaining, where all elements hashing to the same index are stored in a linked list. PHP uses the latter mechanism.

Typically hashtables are not explicitly ordered: The order in which elements are stored in the underlying array depends on the hashing function and will be fairly random. But this behavior is not consistent with the semantics of PHP arrays: If you iterate over a PHP array you will get back the elements in the exact order in which they were inserted. This means that PHP’s hashtable implementation has to support an additional mechanism for remembering the order of array elements.

The old hashtable implementation

I’ll only provide a short overview of the old hashtable implementation here, for a more comprehensive explanation please see the hashtable chapter of the PHP Internals Book. The following graphic is a very high-level view of how a PHP 5 hashtable looks like:

The elements in the “collision resolution” chain are referred to as “buckets”. Every bucket is individually allocated. What the image glosses over are the actual values stored in these buckets (only the keys are shown here). Values are stored in separately allocated zval structures, which are 16 bytes (32bit) or 24 bytes (64bit) large.

Another thing the image does not show is that the collision resolution list is actually a doubly linked list (which simplifies deletion of elements). Next to the collision resolution list, there is another doubly linked list storing the order of the array elements. For an array containing the keys "a", "b", "c" in this order, this list could look as follows:

So why was the old hashtable structure so inefficient, both in terms of memory usage and performance? There are a number of primary factors:

Buckets require separate allocations. Allocations are slow and additionally require 8 / 16 bytes of allocation overhead. Separate allocations also means that the buckets will be more spread out in memory and as such reduce cache efficiency.

Zvals also require separate allocations. Again this is slow and incurs allocation header overhead. Furthermore this requires us to store a pointer to a zval in each bucket. Because the old implementation was overly generic it actually needed not just one, but two pointers for this.

The two doubly linked lists require a total of four pointers per bucket. This alone takes up 16 / 32 bytes.. Furthermore traversing linked lists is a very cache-unfriendly operation.

The new hashtable implementation tries to solve (or at least ameliorate) all of these problems.

The new zval implementation

Before getting to the actual hashtable, I’d like to take a quick look at the new zval structure and highlight how it differs from the old one. The zval struct is defined as follows:

struct _zval_struct { zend_value value ; union { struct { ZEND_ENDIAN_LOHI_4 ( zend_uchar type , zend_uchar type_flags , zend_uchar const_flags , zend_uchar reserved ) } v ; uint32_t type_info ; } u1 ; union { uint32_t var_flags ; uint32_t next ; /* hash collision chain */ uint32_t cache_slot ; /* literal cache slot */ uint32_t lineno ; /* line number (for ast nodes) */ } u2 ; };

You can safely ignore the ZEND_ENDIAN_LOHI_4 macro in this definition - it is only present to ensure a predictable memory layout across machines with different endianness.

The zval structure has three parts: The first member is the value . The zend_value union is 8 bytes large and can store different kinds of values, including integers, strings, arrays, etc. What is actually stored in there depend on the zval type.

The second part is the 4 byte type_info , which consists of the actual type (like IS_STRING or IS_ARRAY ), as well as a number of additional flags providing information about this type. E.g. if the zval is storing an object, then the type flags would say that it is a non-constant, refcounted, garbage-collectible, non-copying type.

The last 4 bytes of the zval structure are normally unused (it’s really just explicit padding, which the compiler would introduce automatically otherwise). However in special contexts this space is used to store some extra information. E.g. AST nodes use it to store a line number, VM constants use it to store a cache slot index and hashtables use it to store the next element in the collision resolution chain - that last part will be important to us.

If you compare this to the previous zval implementation, one difference particularly stands out: The new zval structure no longer stores a refcount. The reason behind this, is that the zvals themselves are no longer individually allocated. Instead the zval is directly embedded into whatever is storing it (e.g. a hashtable bucket).

While the zvals themselves no longer use refcounting, complex data types like strings, arrays, objects and resources still use them. Effectively the new zval design has pushed out the refcount (and information for the cycle-collector) from the zval to the array/object/etc. There are a number of advantages to this approach, some of them listed in the following:

Zvals storing simple values (like booleans, integers or floats) no longer require any allocations. So this saves the allocation header overhead and improves performance by avoiding unnecessary allocs and frees and improving cache locality.

Zvals storing simple values don’t need to store a refcount and GC root buffer.

We avoid double refcounting. E.g. previously objects both used the zval refcount and an additional object refcount, which was necessary to support by-object passing semantics.

As all complex values now embed a refcount, they can be shared independently of the zval mechanism. In particular it is now also possible to share strings. This is important to the hashtable implementation, as it no longer needs to copy non-interned string keys.

The new hashtable implementation

With all the preliminaries behind us, we can finally look at the new hashtable implementation used by PHP 7. Lets start by looking at the bucket structure:

typedef struct _Bucket { zend_ulong h ; zend_string * key ; zval val ; } Bucket ;

A bucket is an entry in the hashtable. It contains pretty much what you would expect: A hash h , a string key key and a zval value val . Integer keys are stored in h (the key and hash are identical in this case), in which case the key member will be NULL .

As you can see the zval is directly embedded in the bucket structure, so it doesn’t have to be allocated separately and we don’t have to pay for allocation overhead.

The main hashtable structure is more interesting:

typedef struct _HashTable { uint32_t nTableSize ; uint32_t nTableMask ; uint32_t nNumUsed ; uint32_t nNumOfElements ; zend_long nNextFreeElement ; Bucket * arData ; uint32_t * arHash ; dtor_func_t pDestructor ; uint32_t nInternalPointer ; union { struct { ZEND_ENDIAN_LOHI_3 ( zend_uchar flags , zend_uchar nApplyCount , uint16_t reserve ) } v ; uint32_t flags ; } u ; } HashTable ;

The buckets (= array elements) are stored in the arData array. This array is allocated in powers of two, with the size being stored in nTableSize (the minimum value is 8). The actual number of stored elements is nNumOfElements . Note that this array directly contains the Bucket structures. Previously we used an array of pointers to separately allocated buckets, which means that we needed more alloc/frees, had to pay allocation overhead and also had to pay for the extra pointer.

Order of elements

The arData array stores the elements in order of insertion. So the first array element will be stored in arData[0] , the second in arData[1] etc. This does not in any way depend on the used key, only the order of insertion matters here.

So if you store five elements in the hashtable, slots arData[0] to arData[4] will be used and the next free slot is arData[5] . We remember this number in nNumUsed . You may wonder: Why do we store this separately, isn’t it the same as nNumOfElements ?

It is, but only as long as only insertion operations are performed. If an element is deleted from a hashtable, we obviously don’t want to move all elements in arData that occur after the deleted element in order to have a continuous array again. Instead we simply mark the deleted value with an IS_UNDEF zval type.

As an example, consider the following code:

$array = [ 'foo' => 0 , 'bar' => 1 , 0 => 2 , 'xyz' => 3 , 2 => 4 ]; unset ( $array [ 0 ]); unset ( $array [ 'xyz' ]);

This will result in the following arData structure:

nTableSize = 8 nNumOfElements = 3 nNumUsed = 5 [0]: key="foo", val=int(0) [1]: key="bar", val=int(1) [2]: val=UNDEF [3]: val=UNDEF [4]: h=2, val=int(4) [5]: NOT INITIALIZED [6]: NOT INITIALIZED [7]: NOT INITIALIZED

As you can see the first five arData elements have been used, but elements at position 2 (key 0 ) and 3 (key 'xyz' ) have been replaced with an IS_UNDEF tombstone, because they were unset . These elements will just remain wasted memory for now. However, once nNumUsed reaches nTableSize PHP will try compact the arData array, by dropping any UNDEF entries that have been added along the way. Only if all buckets really contain a value the arData will be reallocated to twice the size.

The new way of maintaining array order has several advantages over the doubly linked list that was used in PHP 5.x. One obvious advantage is that we save two pointers per bucket, which corresponds to 8/16 bytes. Additionally it means that iterating an array looks roughly as follows:

uint32_t i ; for ( i = 0 ; i < ht -> nNumUsed ; ++ i ) { Bucket * b = & ht -> arData [ i ]; if ( Z_ISUNDEF ( b -> val )) continue ; // do stuff with bucket }

This corresponds to a linear scan of memory, which is much more cache-efficient than a linked list traversal (where you go back and forth between relatively random memory addresses).

One problem with the current implementation is that arData never shrinks (unless explicitly told to). So if you create an array with a few million elements and remove them afterwards, the array will still take a lot of memory. We should probably half the arData size if utilization falls below a certain level.

Hashtable lookup

Until now we have only discussed how PHP arrays represent order. The actual hashtable lookup uses the second arHash array, which consists of uint32_t values. The arHash array has the same size ( nTableSize ) as arData and both are actually allocated as one chunk of memory.

The hash returned from the hashing function (DJBX33A for string keys) is a 32-bit or 64-bit unsigned integer, which is too large to directly use as an index into the hash array. We first need to adjust it to the table size using a modulus operation. Instead of hash % ht->nTableSize we use hash & (ht->nTableSize - 1) , which is the same if the size is a power of two, but doesn’t require expensive integer division. The value ht->nTableSize - 1 is stored in ht->nTableMask .

Next, we look up the index idx = ht->arHash[hash & ht->nTableMask] in the hash array. This index corresponds to the head of the collision resolution list. So ht->arData[idx] is the first entry we have to examine. If the key stored there matches the one we’re looking for, we’re done.

Otherwise we must continue to the next element in the collision resolution list. The index to this element is stored in bucket->val.u2.next , which are the normally unused last four bytes of the zval structure that get a special meaning in this context. We continue traversing this linked list (which uses indexes instead of pointers) until we either find the right bucket or hit an INVALID_IDX - which means that an element with the given key does not exist.

In code, the lookup mechanism looks like this:

zend_ulong h = zend_string_hash_val ( key ); uint32_t idx = ht -> arHash [ h & ht -> nTableMask ]; while ( idx != INVALID_IDX ) { Bucket * b = & ht -> arData [ idx ]; if ( b -> h == h && zend_string_equals ( b -> key , key )) { return b ; } idx = Z_NEXT ( b -> val ); // b->val.u2.next } return NULL ;

Lets consider how this approach improves over the previous implementation: In PHP 5.x the collision resolution used a doubly linked pointer list. Using uint32_t indices instead of pointers is better, because they take half the size on 64bit systems. Additionally fitting in 4 bytes means that we can embed the “next” link into the unused zval slot, so we essentially get it for free.

We also use a singly linked list now, there is no “prev” link anymore. The prev link is primarily useful for deleting elements, because you have to adjust the “next” link of the “prev” element when you perform a deletion. However, if the deletion happens by key, you already know the previous element as a result of traversing the collision resolution list.

The few cases where deletion occurs in some other context (e.g. “delete the element the iterator is currently at”) will have to traverse the collision list to find the previous element. But as this is a rather unimportant scenario, we prefer saving memory over saving a list traversal for that case.

Packed hashtables

PHP uses hashtables for all arrays. However in the rather common case of continuous, integer-indexed arrays (i.e. real arrays) the whole hashing thing doesn’t make much sense. This is why PHP 7 introduces the concept of “packed hashtables”.

In packed hashtables the arHash array is NULL and lookups will directly index into arData . If you’re looking for the key 5 then the element will be located at arData[5] or it doesn’t exist at all. There is no need to traverse a collision resolution list.

Note that even for integer indexed arrays PHP has to maintain order. The arrays [0 => 1, 1 => 2] and [1 => 2, 0 => 1] are not the same. The packed hashtable optimization only works if keys are in ascending order. There can be gaps in between them (the keys don’t have to be continuous), but they need to always increase. So if elements are inserted into an array in a “wrong” order (e.g. in reverse) the packed hashtable optimization will not be used.

Note furthermore that packed hashtables still store a lot of useless information. For example we can determine the index of a bucket based on its memory address, so bucket->h is redundant. The value bucket->key will always be NULL , so it’s just wasted memory as well.

We keep these useless values around so that buckets always have the same structure, independently of whether or not packing is used. This means that iteration can always use the same code. However we might switch to a “fully packed” structure in the future, where a pure zval array is used if possible.

Empty hashtables

Empty hashtables get a bit of special treating both in PHP 5.x and PHP 7. If you create an empty array [] chances are pretty good that you won’t actually insert any elements into it. As such the arData / arHash arrays will only be allocated when the first element is inserted into the hashtable.

To avoid checking for this special case in many places, a small trick is used: While the nTableSize is set to either the hinted size or the default value of 8, the nTableMask (which is usually nTableSize - 1 ) is set to zero. This means that hash & ht->nTableMask will always result in the value zero as well.

So the arHash array for this case only needs to have one element (with index zero) that contains an INVALID_IDX value (this special array is called uninitialized_bucket and is allocated statically). When a lookup is performed, we always find the INVALID_IDX value, which means that the key has not been found (which is exactly what you want for an empty table).

Memory utilization

This should cover the most important aspects of the PHP 7 hashtable implementation. First lets summarize why the new implementation uses less memory. I’ll only use the numbers for 64bit systems here and only look at the per-element size, ignoring the main HashTable structure (which is less significant asymptotically).

In PHP 5.x a whopping 144 bytes per element were required. In PHP 7 the value is down to 36 bytes, or 32 bytes for the packed case. Here’s where the difference comes from:

Zvals are not individually allocated, so we save 16 bytes allocation overhead.

Buckets are not individually allocated, so we save another 16 bytes of allocation overhead.

Zvals are 16 bytes smaller for simple values.

Keeping order no longer needs 16 bytes for a doubly linked list, instead the order is implicit.

The collision list is now singly linked, which saves 8 bytes. Furthermore it’s now an index list and the index is embedded into the zval, so effectively we save another 8 bytes.

As the zval is embedded into the bucket, we no longer need to store a pointer to it. Due to details of the previous implementation we actually save two pointers, so that’s another 16 bytes.

The length of the key is no longer stored in the bucket, which is another 8 bytes. However, if the key is actually a string and not an integer, the length still has to be stored in the zend_string structure. The exact memory impact in this case is hard to quantify, because zend_string structures are shared, whereas previously hashtables had to copy the string if it wasn’t interned.

structure. The exact memory impact in this case is hard to quantify, because structures are shared, whereas previously hashtables had to copy the string if it wasn’t interned. The array containing the collision list heads is now index based, so saves 4 bytes per element. For packed arrays it is not necessary at all, in which case we save another 4 bytes.

However it should be clearly said that this summary is making things look better than they really are in several respects. First of all, the new hashtable implementation uses a lot more embedded (as opposed to separately allocated) structures. How can this negatively affect things?

If you look at the actually measured numbers at the start of this article, you’ll find that on 64bit PHP 7 an array with 100000 elements took 4.00 MiB of memory. In this case we’re dealing with a packed array, so we would actually expect 32 * 100000 = 3.05 MiB memory utilization. The reason behind this is that we allocate everything in powers of two. The nTableSize will be 2^17 = 131072 in this case, so we’ll allocate 32 * 131072 bytes of memory (which is 4.00 MiB).

Of course the previous hashtable implementation also used power of two allocations. However it only allocated an array with bucket pointers in this way (where each pointer is 8 bytes). Everything else was allocated on demand. So in PHP 7 we loose 32 * 31072 (0.95 MiB) in unused memory, while in PHP 5.x we only waste 8 * 31072 (0.24 MiB).

Another thing to consider is what happens if not all values stored in the array are distinct. For simplicity lets assume that all values in the array are identical. So lets replace the range in the starting example with an array_fill :

$startMemory = memory_get_usage (); $array = array_fill ( 0 , 100000 , 42 ); echo memory_get_usage () - $startMemory , " bytes

" ;

This script results in the following numbers:

| 32 bit | 64 bit ------------------------------ PHP 5.6 | 4.70 MiB | 9.39 MiB ------------------------------ PHP 7.0 | 3.00 MiB | 4.00 MiB

As you can see the memory usage on PHP 7 stays the same as in the range case. There is no reason why it would change, as all zvals are separate. On PHP 5.x on the other hand the memory usage is now significantly lower, because only one zval is used for all values. So while we’re still a good bit better off on PHP 7, the difference is smaller now.

Things become even more complicated once we consider string keys (which may or not be shared or interned) and complex values. The point being that arrays in PHP 7 will take significantly less memory than in PHP 5.x, but the numbers from the introduction are likely too optimistic in many cases.

Performance

I’ve already talked a lot about memory usage, so lets move to the next point, namely performance. In the end, the goal of the phpng project wasn’t to improve memory usage, but to improve performance. The memory utilization improvement is only a means to an end, in that less memory results in better CPU cache utilization, resulting in better performance.

However there are of course a number of other reasons why the new implementation is faster: First of all we need less allocations. Depending on whether or not values are shared we save two allocations per element. Allocations being rather expensive operations this is quite significant.

Array iteration in particular is now more cache-friendly, because it’s now a linear memory traversal, instead of a random-access linked list traversal.

There’s probably a lot more to be said on the topic of performance, but the main interest in this article was memory usage, so I won’t go into further detail here.

Closing thoughts

PHP 7 undoubtedly has made a big step forward as far as the hashtable implementation is concerned. A lot of useless overhead is gone now.

So the question is: where we can go from here? One idea I already mentioned is to use “fully packed” hashes for the case of increasing integer keys. This would mean using a plain zval array, which is the best we can do without starting to specialize uniformly typed arrays.

There’s probably some other directions one could go as well. For example switching from collision-chaining to open addressing (e.g. using Robin Hood probing), could be better both in terms of memory usage (no collision resolution list) and performance (better cache efficiency, depending on the details of the probing algorithm). However open-addressing is relatively hard to combine with the ordering requirement, so this may not be possible to do in a reasonable way.

Another idea is to combine the h and key fields in the bucket structure. Integer keys only use h and string keys already store the hash in key as well. However this would likely have an adverse impact on performance, because fetching the hash will require an additional memory indirection.

One last thing that I wish to mention is that PHP 7 improved not only the internal representation of hashtables, but also the API used to work them. I’ve regularly had to look up how even simple operations like zend_hash_find had to be used, especially regarding how many levels of indirection are required (hint: three). In PHP 7 you just write zend_hash_find(ht, key) and get back a zval* . Generally I find that writing extensions for PHP 7 has become quite a bit more pleasant.

Hopefully I was able to provide you some insight into the internals of PHP 7 hashtables. Maybe I’ll write a followup article focusing on zvals. I’ve already touched on some of the difference in this post, but there’s a lot more to be said on the topic.