The go a bit further than the article on the advantages of intrusive data structures, taking linked lists as an example:
As the article mentions, intrusive data structures naturally lead to one fewer indirection. To do the same with a traditional list (where the list node owns the payload), a different node type is needed for each payload type. This is easy to do with the proper support for monomorphized generics, see C++'s std::list. It is awkward in C, where the implementation has to be macro-generated. C naturally pushes towards an indirection through void *, which makes intrusive lists more attractive.
One other advantage of intrusive data structures is the ability to link a payload into several parallel collections without indirections (where traditional collections would require e.g. one collection owning the payloads, and the other collections merely holding non-owning pointers to them).
Las but not least, the defining property of intrusive data structures is that they leave the responsibility of allocating the elements to the user. The elements can be allocated on the heap, on the stack, in a global array (like "initholes" in the article), in a special arena, etc. It is even reasonable to use non-uniform allocation strategies; for example, for a circular list, allocate an anchor node on the stack and the other nodes (those embedded in payloads) on the heap.
> One other advantage of intrusive data structures is the ability to link a payload into several parallel collections without indirections
My example here from the top of my head are intrusive heaps, which are provide a neat way of implementing A*. Here you combine a HashMap and a Heap (over a Vec) where the Heap has the data, and the HashMap maps SearchNodeId to Heap indices.
This allows O(1) lookups by search node Id into the Heap (as opposed to a linear scan) despite elements in the heap being constantly shuffled around as search nodes enter and leave the heap.
I'm sure that using HashMaps as a parallel index to other collections can be useful in other scenarios, but I don't know if combination of other data structures works this well, the synchronisation cost might not be worth it.
> It is awkward in C, where the implementation has to be macro-generated.
You can avoid having the implementation be macro-generated by "hiding" the list pointers before a char payload[0]. See https://pastebin.com/DE69mbJD for an example.
The same technique is used by glibc's malloc to store metadata about the allocation right next to your data, and then recover it when you call realloc/free, without needing a separate metadata allocation.
The caveat is that the type of the pointer does not indicate provenance. For example, nothing stops you from calling list_next on an arbitrary pointer to data that is not on a list, and that would be UB. The same happens with realloc and free, where it's UB if you pass them a pointer that was not returned by the heap allocator.
Zero-sized arrays are not standard. Accessing an array out of bounds is UB. At the very least, you should use a flexible array member instead (char payload[];).
But even if you did that, strict aliasing implies that 'payload' can only be accessed as an array of character type. It is correct to memcpy between 'payload' and another object of arbitrary type T of the appropriate size (as list_push_ does in your example), but it is UB to access 'payload' in place as a T (as main does, by casting to struct point * and dereferencing). Oh, and 'payload' may not satisfy the alignment requirement of T.
There is no realistic strict-aliasing-abiding way around a distinct node type per payload type.
IIRC GCC and Clang lets character types alias to any type. Otherwise glibc’s malloc also doesn’t abide to strict aliasing.
In practice you wouldn’t have the payload in the struct at all, just a fixed offset aligned with the maximum alignment, but this is more illustrative of what’s happening for an example.
There is no OoB access of an array; the calculated pointer is pointing to the payload object that's residing in the malloc-returned storage right after the node struct.
I think the actual problem is the alignment; that malloc-returned storage simply can't have enough space to hold a "struct { struct node header; PAYLOAD_TYPE payload; }" (which is what the parent comment is trying to emulate) if the payload type has an alignment that's greater than the size of a pointer, and that pointer will be pointing at what would've been the padding in that struct.
Yes, there is. It does not matter that storage happens to be allocated beyond the end of said array. Strict aliasing implies that it is UB to reinterpret the array as anything else. And it is UB to access an array out of bounds.
Flexible array members specifically exist for these dynamically-allocated trailing arrays. They do not solve the strict aliasing problem, though.
> if the payload type has an alignment that's greater than the size of a pointer
The amount of padding is implementation-defined. The only portable guarantee is that 'payload' is aligned for its element type, char. To over-align, use _Alignas, as in:
struct node {
struct node *next;
_Alignas(max_align_t) char payload[]; // Satisfies all fundamental alignment requirements
};
> It is awkward in C, where the implementation has to be macro-generated
I assume this is why they are putting the list pointer and payload in separate structs and doing pointer math to access the payload, so that it’s easy to build a set of macros that act like a generic list class for building lists out of any payload, right?
> One other advantage of intrusive data structures is the ability to link a payload into several parallel collections without indirections
Wait - how does this work? If I do address math on the pointer in order to find a payload, then isn’t the payload tied into exactly one next pointer, and thus exactly one list? For a minute I thought maybe this is why they put the pointer after the payload, but now I don’t see how to use a payload in more than one list, nor why they use subtract on the list pointer to find the payload instead of putting the list in front of the payload and adding (or using a type-cast pointer for direct access).
> the defining property of intrusive data structures is that they leave the responsibility of allocating elements to the user.
Indeed! This is why you see them in OS’s, in memory managers, and in embedded systems. We used to use them all the time in console video games before dynamic memory and heap allocations were common (or even allowed). Use of STL wasn’t allowed. Often the memory needed would be pre-allocated, and lists would be created and managed at run time without allocation, just by wiring up the pointers. Similar to what a memory manager has to do.
This was in C++, but back when (and before) EASTL was popular. EASTL was EA’s version of the STL without built-in heap allocation for container classes. We usually built payload classes with the list next pointer placed directly in the payload, and essentially did the list management as a one-off separately for each payload, because it was typically only a few lines of code and there weren’t enough list types for it to be a problem. This is the kind of intrusive list I’ve seen the most of, hence the questions about the particular C flavor shown here.
> If I do address math on the pointer in order to find a payload, then isn’t the payload tied into exactly one next pointer, and thus exactly one list?
The container_of macro takes the type and member - so for a different member it can subtract a different offset.
Going more basic, you could imagine creating something like:
I do not think a type-safe macro-generated list in C is any more awkward to implement or inferior to a C++ template version. The issue is more than there is no standardized version directly available except perhaps the old BSD ones and those are not ideal. I agree with the rest of your comment.
> I do not think a type-safe macro-generated list in C is any more awkward to implement or inferior to a C++ template version.
I have some experience with this, and while this is one of these things that are feasible, I find them significantly inferior to templates in practice.
For one thing, footguns are everywhere in C macro-based metaprogramming. E.g. do not declare the payload as 'payload_type payload;' in the node structure, but choose 'typeof(payload_type) payload;' instead, as someone may pass an array type or function pointer type for 'payload_type'. Speaking of array types, how do you deal with the fact that you cannot pass them by value? I will choose C++ templates' semantic substitution over C macros' textual substitution.
Anyway, to me, the biggest limitation of macro-generation compared to templates is that there is no centralized monomorphization. If an application uses two libraries, each of which handles lists of int, each library will have to independently macro-generate its separate list implementation, and because C's type system is nominal, the generated types will be isomorphic but incompatible. Contrast this with C++ templates, where two independent libraries can happily share std::list<int> values.
> If an application uses two libraries, each of which handles lists of int, each library will have to independently macro-generate its separate list implementation, and because C's type system is nominal, the generated types will be isomorphic but incompatible.
Um, what? C89, 3.1.2.6: "Moreover, two structure, union, or enumeration types declared in separate translation units are compatible if they have the same number of members, the same member names, and compatible member types; for two structures, the members shall be in the same order".
There has been some minor changes over the years, but as long as the struct tags are the same, and the fields are in the same order and have compatible types, the two structs defined in separate compilation units are compatible.
> This is easy to do with the proper support for monomorphized generics, see C++'s std::list. It is awkward in C, where the implementation has to be macro-generated.
Fairly pleasant in Zig, through abuse of @fieldParentPointer and a pinch of comptime.
It was a little nicer in the `usingnamespace` days. So it goes.
> The elements can be allocated on the heap, on the stack, in a global array (like "initholes" in the article), in a special arena, etc.
An "etc" worth mentioning specifically is a memory pool: they're useful for any same-sized struct which gets recycled a lot, but for linked lists there are further advantages. You don't have to cast the object to bytes and declare a link pointer, since it already has one: not really an advantage, casting is free, but: if you can arrange to give both sides of the list back, then recycling can be done on a per-list level by prepending the whole thing to the freelist.
I was surprised to see the main benefit of intrusive linking mentioned as a bit of a side note: The ability to move data around between lists (and within a list) without copying. You also get O(1) removal from the middle of the list, assuming you have a pointer to the object somewhere else. As a result, when you have large state structs and you don't do a lot of list scans, intrusive linking makes things a lot faster than use of packed structures like vectors.
Data is generally read more often than written and data is read in locally spatial way.
That’s why having elements laid out next to one another is often more important than the algorithmic complexity of occasionally doing an O(n) or O(n log n) operation updating the layout.
It’s not always the case of course but it is the case more often than you’d think.
Hmm interesting, the doubly linked list presented here is missing the elegant 'overlapped list header' trick from AmigaOS (at least that's where I saw it first):
E.g. an AmigaOS list node looks conventional, it has two pointers, one to the next node (succ), and one to the previous node (pred):
In an empty list, lh_Head points to &lh_Tail, and lh_TailPred points to &lh_Head. The lh_Tail pointer is always null (this is the 'end marker').
In a populated list, lh_Head points to the embedded Node struct of the first list node, and lh_TailPred points to the embedded Node struct of the last list node. The ln_Succ pointer of the last node points to the address of the list header's lh_Tail pointer (...which is always null).
That way you only need an existing node pointer to walk forward and backward, or insert or remove a node. When walking the list by following the succ or pred pointers you know you've reached the end when encountering a null pointer.
Apparently the Linux-style lists in the article require to know the address of the list header to detect when the end is reached which isn't needed for the Amiga style list (at the cost of an additional 'sentinel null pointer' in the list header).
Pretty much all of AmigaOS was held together by such doubly linked lists.
(I hope I got that all right, it's been a long time)
I googled it and got the response that Bjarne Stroustrup first used “intrusive” in his 1985 C++ book. He was adding a new distinction between the older intrusive kind and the new ‘non-intrusive’ kind, because some people had started using C++ to allocate the list nodes and the payload structs separately.
Now with std::list and college classes often teaching non-intrusive linked lists, and intrusive lists only being used in deep dark places like the OS kernel, maybe it’s easy to assume the ‘regular’ kind is non-intrusive.
What Stroustrup called ‘intrusive’ had been the default understanding of linked lists since around 1955, and what people used most often. A ‘regular’ linked list to most people back then was the intrusive kind, and the term ‘non-intrusive’ might have been an attempt to sell people on the benefits of abstracting and separating node types from payloads, but that maybe papers over the disadvantages a little.
The only kind of linked list I’ve ever used in my professional career is the intrusive kind. There are very few good reasons to ever use non-intrusive lists outside of the classroom. At least, not if you care about performance at all. They might be convenient & easy, but it’s usually the case that either an array or an intrusive list would be a better engineering choice.
It really depends on the ecosystem you’re working in. For a good while, most developers have been working with managed runtimes, where “non-intrusive” linked lists are generally the default and “intrusive” linked lists correspondingly rare.
(Actually, in many cases arrays are the default (like ArrayList in Java), because lists tend to only get assembled once and then passed around without further modification.)
Back in the day what is being called out here as an "intrusive" linked list was just a linked list, since you didn't have the luxury of having memory and CPU cycles to waste with extra allocations and indirection.
In the C++ world the STL introduced generic data types such as linked lists, which became the default, but "instrusive" linked lists still have their place in specialized list-heavy use cases where performance matters. In a previous job I wrote a widely adopted XML/JSON library using instrusive lists to link child elements, and the performance benefit was considerable, with my DOM API basically hiding this implementation detail from the user.
"Intrusive" may be a C++ speak, but I wouldn't say that one or the other type of lists is necessarily much older or more "normal". After all, a cons cell embeds data and not the other way around and lisp is one of the oldest programming languages in existence
You have it backwards, an intrusive linked list is a linked list that is embedded in another data structure. The classic example is a linked list whose elements live on the stack.
The article is wrong too, or at least using the term over-specifically.
GP points out that what the article calls "intrusive linked list" is a regular linked list. Wikipedia for instance gives the canonical linked list example of a struct with one embedded integer and a next link and of course does not call it "intrusive linked list".
"Intrusive" got popular with C++ intrusive pointers, and that is where the article gets is misinformation from.
And of coursed the web jockeys downvote the correct objection since they have no clue about data structures, history, logic or basic reading skills.
I came to this relatively late (2013-ish, windows kernel development, scouring OSDev, etc) so I thought that was always the right name for them. Prior experience was mostly... higher-level langs.
I concur. I recall being a student and when implementing LL for the first time, you did it this way (mix your data and ptr to next node). It is baby's first linked list.
As the article mentions, intrusive data structures naturally lead to one fewer indirection. To do the same with a traditional list (where the list node owns the payload), a different node type is needed for each payload type. This is easy to do with the proper support for monomorphized generics, see C++'s std::list. It is awkward in C, where the implementation has to be macro-generated. C naturally pushes towards an indirection through void *, which makes intrusive lists more attractive.
One other advantage of intrusive data structures is the ability to link a payload into several parallel collections without indirections (where traditional collections would require e.g. one collection owning the payloads, and the other collections merely holding non-owning pointers to them).
Las but not least, the defining property of intrusive data structures is that they leave the responsibility of allocating the elements to the user. The elements can be allocated on the heap, on the stack, in a global array (like "initholes" in the article), in a special arena, etc. It is even reasonable to use non-uniform allocation strategies; for example, for a circular list, allocate an anchor node on the stack and the other nodes (those embedded in payloads) on the heap.
My example here from the top of my head are intrusive heaps, which are provide a neat way of implementing A*. Here you combine a HashMap and a Heap (over a Vec) where the Heap has the data, and the HashMap maps SearchNodeId to Heap indices. This allows O(1) lookups by search node Id into the Heap (as opposed to a linear scan) despite elements in the heap being constantly shuffled around as search nodes enter and leave the heap.
I'm sure that using HashMaps as a parallel index to other collections can be useful in other scenarios, but I don't know if combination of other data structures works this well, the synchronisation cost might not be worth it.
You can avoid having the implementation be macro-generated by "hiding" the list pointers before a char payload[0]. See https://pastebin.com/DE69mbJD for an example.
The same technique is used by glibc's malloc to store metadata about the allocation right next to your data, and then recover it when you call realloc/free, without needing a separate metadata allocation.
The caveat is that the type of the pointer does not indicate provenance. For example, nothing stops you from calling list_next on an arbitrary pointer to data that is not on a list, and that would be UB. The same happens with realloc and free, where it's UB if you pass them a pointer that was not returned by the heap allocator.
But even if you did that, strict aliasing implies that 'payload' can only be accessed as an array of character type. It is correct to memcpy between 'payload' and another object of arbitrary type T of the appropriate size (as list_push_ does in your example), but it is UB to access 'payload' in place as a T (as main does, by casting to struct point * and dereferencing). Oh, and 'payload' may not satisfy the alignment requirement of T.
There is no realistic strict-aliasing-abiding way around a distinct node type per payload type.
In practice you wouldn’t have the payload in the struct at all, just a fixed offset aligned with the maximum alignment, but this is more illustrative of what’s happening for an example.
There is no OoB access of an array; the calculated pointer is pointing to the payload object that's residing in the malloc-returned storage right after the node struct.
I think the actual problem is the alignment; that malloc-returned storage simply can't have enough space to hold a "struct { struct node header; PAYLOAD_TYPE payload; }" (which is what the parent comment is trying to emulate) if the payload type has an alignment that's greater than the size of a pointer, and that pointer will be pointing at what would've been the padding in that struct.
Yes, there is. It does not matter that storage happens to be allocated beyond the end of said array. Strict aliasing implies that it is UB to reinterpret the array as anything else. And it is UB to access an array out of bounds.
Flexible array members specifically exist for these dynamically-allocated trailing arrays. They do not solve the strict aliasing problem, though.
> if the payload type has an alignment that's greater than the size of a pointer
The amount of padding is implementation-defined. The only portable guarantee is that 'payload' is aligned for its element type, char. To over-align, use _Alignas, as in:
I assume this is why they are putting the list pointer and payload in separate structs and doing pointer math to access the payload, so that it’s easy to build a set of macros that act like a generic list class for building lists out of any payload, right?
> One other advantage of intrusive data structures is the ability to link a payload into several parallel collections without indirections
Wait - how does this work? If I do address math on the pointer in order to find a payload, then isn’t the payload tied into exactly one next pointer, and thus exactly one list? For a minute I thought maybe this is why they put the pointer after the payload, but now I don’t see how to use a payload in more than one list, nor why they use subtract on the list pointer to find the payload instead of putting the list in front of the payload and adding (or using a type-cast pointer for direct access).
> the defining property of intrusive data structures is that they leave the responsibility of allocating elements to the user.
Indeed! This is why you see them in OS’s, in memory managers, and in embedded systems. We used to use them all the time in console video games before dynamic memory and heap allocations were common (or even allowed). Use of STL wasn’t allowed. Often the memory needed would be pre-allocated, and lists would be created and managed at run time without allocation, just by wiring up the pointers. Similar to what a memory manager has to do.
This was in C++, but back when (and before) EASTL was popular. EASTL was EA’s version of the STL without built-in heap allocation for container classes. We usually built payload classes with the list next pointer placed directly in the payload, and essentially did the list management as a one-off separately for each payload, because it was typically only a few lines of code and there weren’t enough list types for it to be a problem. This is the kind of intrusive list I’ve seen the most of, hence the questions about the particular C flavor shown here.
The container_of macro takes the type and member - so for a different member it can subtract a different offset.
Going more basic, you could imagine creating something like:
The normal, 10ths, and 100ths lists are distinct collections, this is the basic idea. The macros just help generalise it and make it more usable.I have some experience with this, and while this is one of these things that are feasible, I find them significantly inferior to templates in practice.
For one thing, footguns are everywhere in C macro-based metaprogramming. E.g. do not declare the payload as 'payload_type payload;' in the node structure, but choose 'typeof(payload_type) payload;' instead, as someone may pass an array type or function pointer type for 'payload_type'. Speaking of array types, how do you deal with the fact that you cannot pass them by value? I will choose C++ templates' semantic substitution over C macros' textual substitution.
Anyway, to me, the biggest limitation of macro-generation compared to templates is that there is no centralized monomorphization. If an application uses two libraries, each of which handles lists of int, each library will have to independently macro-generate its separate list implementation, and because C's type system is nominal, the generated types will be isomorphic but incompatible. Contrast this with C++ templates, where two independent libraries can happily share std::list<int> values.
Um, what? C89, 3.1.2.6: "Moreover, two structure, union, or enumeration types declared in separate translation units are compatible if they have the same number of members, the same member names, and compatible member types; for two structures, the members shall be in the same order".
There has been some minor changes over the years, but as long as the struct tags are the same, and the fields are in the same order and have compatible types, the two structs defined in separate compilation units are compatible.
Fairly pleasant in Zig, through abuse of @fieldParentPointer and a pinch of comptime.
https://github.com/mnemnion/zelda
It was a little nicer in the `usingnamespace` days. So it goes.
> The elements can be allocated on the heap, on the stack, in a global array (like "initholes" in the article), in a special arena, etc.
An "etc" worth mentioning specifically is a memory pool: they're useful for any same-sized struct which gets recycled a lot, but for linked lists there are further advantages. You don't have to cast the object to bytes and declare a link pointer, since it already has one: not really an advantage, casting is free, but: if you can arrange to give both sides of the list back, then recycling can be done on a per-list level by prepending the whole thing to the freelist.
That’s why having elements laid out next to one another is often more important than the algorithmic complexity of occasionally doing an O(n) or O(n log n) operation updating the layout.
It’s not always the case of course but it is the case more often than you’d think.
E.g. an AmigaOS list node looks conventional, it has two pointers, one to the next node (succ), and one to the previous node (pred):
Most AmigaOS structs embed such a Node struct at the start....but the list header has three pointers which basically form two overlapped Node structs:
In an empty list, lh_Head points to &lh_Tail, and lh_TailPred points to &lh_Head. The lh_Tail pointer is always null (this is the 'end marker').In a populated list, lh_Head points to the embedded Node struct of the first list node, and lh_TailPred points to the embedded Node struct of the last list node. The ln_Succ pointer of the last node points to the address of the list header's lh_Tail pointer (...which is always null).
That way you only need an existing node pointer to walk forward and backward, or insert or remove a node. When walking the list by following the succ or pred pointers you know you've reached the end when encountering a null pointer.
Apparently the Linux-style lists in the article require to know the address of the list header to detect when the end is reached which isn't needed for the Amiga style list (at the cost of an additional 'sentinel null pointer' in the list header).
Pretty much all of AmigaOS was held together by such doubly linked lists.
(I hope I got that all right, it's been a long time)
"Intrusive" is C++ speak. The regular linked lists always had embedded data or a mix of embedded data and pointers to outside data in a C struct.
Now with std::list and college classes often teaching non-intrusive linked lists, and intrusive lists only being used in deep dark places like the OS kernel, maybe it’s easy to assume the ‘regular’ kind is non-intrusive.
What Stroustrup called ‘intrusive’ had been the default understanding of linked lists since around 1955, and what people used most often. A ‘regular’ linked list to most people back then was the intrusive kind, and the term ‘non-intrusive’ might have been an attempt to sell people on the benefits of abstracting and separating node types from payloads, but that maybe papers over the disadvantages a little.
The only kind of linked list I’ve ever used in my professional career is the intrusive kind. There are very few good reasons to ever use non-intrusive lists outside of the classroom. At least, not if you care about performance at all. They might be convenient & easy, but it’s usually the case that either an array or an intrusive list would be a better engineering choice.
(Actually, in many cases arrays are the default (like ArrayList in Java), because lists tend to only get assembled once and then passed around without further modification.)
In the C++ world the STL introduced generic data types such as linked lists, which became the default, but "instrusive" linked lists still have their place in specialized list-heavy use cases where performance matters. In a previous job I wrote a widely adopted XML/JSON library using instrusive lists to link child elements, and the performance benefit was considerable, with my DOM API basically hiding this implementation detail from the user.
The article is wrong too, or at least using the term over-specifically.
It's not really tied to C++isms at all.
"Intrusive" got popular with C++ intrusive pointers, and that is where the article gets is misinformation from.
And of coursed the web jockeys downvote the correct objection since they have no clue about data structures, history, logic or basic reading skills.