One more thing: Looking back on the previous discussion[1] (which Weston pointed out in his earlier message), Jorge suggested that the old list types might be deprecated in favor of view variants [2]. Others were worried that it might undermine the perception that the Arrow format is stable. I think it might be worth thinking about "soft deprecating" the old list type: suggesting new implementations prefer the list view, but reassuring that implementations should support the old format, even if they just convert to the new format. To be clear, this wouldn't mean we plan to create breaking changes in the format; but if we ever did for other reasons, the old list type might go.
Arrow compute libraries could choose either format for compute support, and plan to do conversion at the boundaries. Libraries that use the new type will have cheap conversion when reading the old type. Meanwhile those that are still on the old type will have some incentive to move towards the new one, since that conversion will not be as efficient. [1] https://lists.apache.org/thread/49qzofswg1r5z7zh39pjvd1m2ggz2kdq [2] https://lists.apache.org/thread/smn13j1rnt23mb3fwx75sw3f877k3nwx On Sun, May 21, 2023 at 3:07 PM Will Jones <will.jones...@gmail.com> wrote: > Hello, > > I think Sasha brings up a good point, that the advantages of this format > seem to be primarily about query processing. Other encodings like REE and > dictionary have space-saving advantages that justify them simply in terms > of space efficiency (although they have query processing advantages as > well). As discussed, most use cases are already well served by existing > list types and dictionary encoding. > > I agree that there are cases where transferring this type without > conversion would be ideal. One use case I can think of is if Velox wants to > be able to take Arrow-based UDFs (possibly written with PyArrow, for > example) that operate on this column type and therefore wants zero-copy > exchange over the C Data Interface. > > One big question I have: we already have three list types: list, large > list (64-bit offsets), and fixed size list. Do we think we will only want a > view version of the 32-bit offset variable length list? Or are we > potentially talking about view variants for all three? > > Best, > > Will Jones > > > On Sun, May 21, 2023 at 2:19 PM Felipe Oliveira Carvalho < > felipe...@gmail.com> wrote: > >> The benefit of having a memory format that’s friendly to non-deterministic >> order writes is unlocked by the transport and processing of the data being >> agnostic to the physical order as much as possible. >> >> Requiring a conversion could cancel out that benefit. But it can be a >> provisory step for compatibility between systems that don’t understand the >> format yet. This is similar to the situation with compression schemes like >> run-end encoding — the goal is processing the compressed data directly >> without an expansion step whenever possible. >> >> This is why having it as part of the open Arrow format is so important: >> everyone can agree on a format that’s friendly to parallel and/or >> vectorized compute kernels without introducing multiple incompatible >> formats to the ecosystem and without imposing a conversion step between >> the >> different systems. >> >> — >> Felipe >> >> On Sat, 20 May 2023 at 20:04 Aldrin <octalene....@pm.me.invalid> wrote: >> >> > I don't feel like this representation is necessarily a detail of the >> query >> > engine, but I am also not sure why this representation would have to be >> > converted to a non-view format when serializing. Could you clarify >> that? My >> > impression is that this representation could be used for persistence or >> > data transfer, though it can be more complex to guarantee the portion of >> > the buffer that an index points to is also present in memory. >> > >> > Sent from Proton Mail for iOS >> > >> > >> > On Sat, May 20, 2023 at 15:00, Sasha Krassovsky < >> krassovskysa...@gmail.com >> > <On+Sat,+May+20,+2023+at+15:00,+Sasha+Krassovsky+%3C%3Ca+href=>> wrote: >> > >> > Hi everyone, >> > I understand that there are numerous benefits to this representation >> > during query processing, but would it be fair to say that this is an >> > implementation detail of the query engine? Query engines don’t >> necessarily >> > need to conform to the Arrow format internally, only at ingest/egress >> > points, and performing a conversion from the non-view to view format >> seems >> > like it would be very cheap (though I understand not necessarily the >> other >> > way around, but you’d need to do that anyway if you’re serializing). >> > >> > Sasha Krassovsky >> > >> > > 20 мая 2023 г., в 13:00, Will Jones <will.jones...@gmail.com> >> > написал(а): >> > > >> > > Thanks for sharing these details, Pedro. The conditional branches >> > argument >> > > makes a lot of sense to me. >> > > >> > > The tensors point brings up some interesting issues. For now, we've >> > defined >> > > our only tensor extension type to be built on a fixed size list. If a >> use >> > > case of this might be manipulating tensors with zero copy, perhaps >> that >> > > suggests that we want a fixed size list variant? In addition, would we >> > have >> > > to define another extension type to be a ListView variant? Or would we >> > want >> > > to think about making extension types somehow valid across various >> > > encodings of the same "logical type"? >> > > >> > >> On Fri, May 19, 2023 at 1:59 PM Pedro Eugenio Rocha Pedreira >> > >> <pedro...@meta.com.invalid> wrote: >> > >> >> > >> Hi all, >> > >> >> > >> This is Pedro from the Velox team at Meta. This is my first time >> here, >> > so >> > >> nice to e-meet you! >> > >> >> > >> Adding to what Felipe said, the main reason we created “ListView” >> > (though >> > >> we just call them ArrayVector/MapVector in Velox) is that, along with >> > >> StringViews for strings, they allow us to write any columnar buffer >> > >> out-or-order, regardless of their types or encodings. This is >> naturally >> > >> doable for all primitive types (fixed-size), but not for types that >> > don’t >> > >> have fixed size and are required to be contiguous. The StringView and >> > >> ListView formats allow us to keep this invariant in Velox. >> > >> >> > >> Being able to write vectors out-of-order is useful when executing >> > >> conditionals like IF/SWITCH statements, which are pervasive among our >> > >> workloads. To fully vectorize it, one first evaluates the expression, >> > then >> > >> generate a bitmap containing which rows take the THEN and which take >> the >> > >> ELSE branch. Then you populate all rows that match the first branch >> by >> > >> evaluating the THEN expression in a vectorized (branch-less and cache >> > >> friendly) way, and subsequently the ELSE branch. If you can’t write >> them >> > >> out-of-order, you would either have a big branch per row dispatching >> to >> > the >> > >> right expression (slow), or populate two distinct vectors then >> merging >> > them >> > >> at the end (potentially even slower). How much faster our approach is >> > >> highly depends on the buffer sizes and expressions, but we found it >> to >> > be >> > >> faster enough on average to justify us extending the underlying >> layout. >> > >> >> > >> With that said, this is all within a single thread of execution. >> > >> Parallelization is done by feeding each thread its own vector/data. >> As >> > >> pointed out in a previous message, this also gives you the >> flexibility >> > to >> > >> implement cardinality increasing/reducing operations, but we don’t >> use >> > it >> > >> for that purpose. Operations like filtering, joining, unnesting and >> > similar >> > >> are done by wrapping the internal vector in a dictionary, as these >> need >> > to >> > >> work not only on “ListViews” but on any data types with any encoding. >> > There >> > >> are more details on Section 4.2.1 in [1] >> > >> >> > >> Beyond this, it also gives function/kernel developers more >> flexibility >> > to >> > >> implement operations that manipulate Arrays/Maps. For example, >> > operations >> > >> that slice these containers can be implemented in a zero-copy manner >> by >> > >> just rearranging the lengths/offsets indices, without ever touching >> the >> > >> larger internal buffers. This is a similar motivation as for >> StringView >> > >> (think of substr(), trim(), and similar). One nice last property is >> that >> > >> this layout allows for overlapping ranges. This is something >> discussed >> > with >> > >> our ML people to allow deduping feature values in a tensor (which is >> > fairly >> > >> common), but not something we have leveraged just yet. >> > >> >> > >> [1] - https://vldb.org/pvldb/vol15/p3372-pedreira.pdf >> > >> >> > >> Best, >> > >> -- >> > >> Pedro Pedreira >> > >> ________________________________ >> > >> From: Felipe Oliveira Carvalho <felipe...@gmail.com> >> > >> Sent: Friday, May 19, 2023 10:01 AM >> > >> To: dev@arrow.apache.org <dev@arrow.apache.org> >> > >> Cc: Pedro Eugenio Rocha Pedreira <pedro...@meta.com> >> > >> Subject: Re: [DISCUSS][Format] Starting the draft implementation of >> the >> > >> ArrayView array format >> > >> >> > >> +pedroerp On Thu, 11 May 2023 at 17: 51 Raphael Taylor-Davies <r. >> > >> taylordavies@ googlemail. com. invalid> wrote: Hi All, > if we added >> > >> this, do we think many Arrow and query > engine implementations (for >> > >> example, DataFusion) will be >> > >> ZjQcmQRYFpfptBannerStart >> > >> This Message Is From an External Sender >> > >> >> > >> ZjQcmQRYFpfptBannerEnd >> > >> +pedroerp >> > >> >> > >> On Thu, 11 May 2023 at 17:51 Raphael Taylor-Davies >> > >> <r.taylordav...@googlemail.com.invalid> wrote: >> > >> Hi All, >> > >> >> > >>> if we added this, do we think many Arrow and query >> > >>> engine implementations (for example, DataFusion) will be eager to >> add >> > >> full >> > >>> support for the type, including compute kernels? Or are they likely >> to >> > >> just >> > >>> convert this type to ListArray at import boundaries? >> > >> I can't speak for query engines in general, but at least for arrow-rs >> > >> and by extension DataFusion, and based on my current understanding of >> > >> the use-cases I would be rather hesitant to add support to the >> kernels >> > >> for this array type, definitely instead favouring conversion at the >> > >> edges. We already have issues with the amount of code generation >> > >> resulting in binary bloat and long compile times, and I worry this >> would >> > >> worsen this situation whilst not really providing compelling >> advantages >> > >> for the vast majority of workloads that don't interact with Velox. >> > >> Whilst I can definitely see that the ListView representation is >> probably >> > >> a better way to represent variable length lists than what arrow >> settled >> > >> upon, I'm not yet convinced it is sufficiently better to incentivise >> > >> broad ecosystem adoption. >> > >> >> > >> Kind Regards, >> > >> >> > >> Raphael Taylor-Davies >> > >> >> > >>> On 11/05/2023 21:20, Will Jones wrote: >> > >>> Hi Felipe, >> > >>> >> > >>> Thanks for the additional details. >> > >>> >> > >>> >> > >>>> Velox kernels benefit from being able to append data to the array >> from >> > >>>> different threads without care for strict ordering. Only the >> offsets >> > >> array >> > >>>> has to be written according to logical order but that is >> potentially a >> > >> much >> > >>>> smaller buffer than the values buffer. >> > >>>> >> > >>> It still seems to me like applications are still pretty niche, as I >> > >> suspect >> > >>> in most cases the benefits are outweighed by the costs. The benefit >> > here >> > >>> seems pretty limited: if you are trying to split work between >> threads, >> > >>> usually you will have other levels such as array chunks to >> parallelize. >> > >> And >> > >>> if you have an incoming stream of row data, you'll want to append in >> > >>> predictable order to match the order of the other arrays. Am I >> missing >> > >>> something? >> > >>> >> > >>> And, IIUC, the cost of using ListView with out-of-order values over >> > >>> ListArray is you lose memory locality; the values of element 2 are >> no >> > >>> longer adjacent to the values of element 1. What do you think about >> > that >> > >>> tradeoff? >> > >>> >> > >>> I don't mean to be difficult about this. I'm excited for both the >> REE >> > and >> > >>> StringView arrays, but this one I'm not so sure about yet. I suppose >> > >> what I >> > >>> am trying to ask is, if we added this, do we think many Arrow and >> query >> > >>> engine implementations (for example, DataFusion) will be eager to >> add >> > >> full >> > >>> support for the type, including compute kernels? Or are they likely >> to >> > >> just >> > >>> convert this type to ListArray at import boundaries? >> > >>> >> > >>> Because if it turns out to be the latter, then we might as well ask >> > Velox >> > >>> to export this type as ListArray and save the rest of the ecosystem >> > some >> > >>> work. >> > >>> >> > >>> Best, >> > >>> >> > >>> Will Jones >> > >>> >> > >>> On Thu, May 11, 2023 at 12:32 PM Felipe Oliveira Carvalho < >> > >>> felipe...@gmail.com<mailto:felipe...@gmail.com>> wrote: >> > >>> >> > >>>> Initial reason for ListView arrays in Arrow is zero-copy >> compatibility >> > >> with >> > >>>> Velox which uses this format. >> > >>>> >> > >>>> Velox kernels benefit from being able to append data to the array >> from >> > >>>> different threads without care for strict ordering. Only the >> offsets >> > >> array >> > >>>> has to be written according to logical order but that is >> potentially a >> > >> much >> > >>>> smaller buffer than the values buffer. >> > >>>> >> > >>>> Acero kernels could take advantage of that in the future. >> > >>>> >> > >>>> In implementing ListViewArray/Type I was able to reuse some C++ >> > >> templates >> > >>>> used for ListArray which can reduce some of the burden on kernel >> > >>>> implementations that aim to work with all the types. >> > >>>> >> > >>>> I’m can fix Acero kernels for working with ListView. This is >> similar >> > to >> > >> the >> > >>>> work I’ve doing in kernels dealing with run-end encoded arrays. >> > >>>> >> > >>>> — >> > >>>> Felipe >> > >>>> >> > >>>> >> > >>>> On Wed, 26 Apr 2023 at 01:03 Will Jones <will.jones...@gmail.com >> > >> <mailto:will.jones...@gmail.com>> wrote: >> > >>>> >> > >>>>> I suppose one common use case is materializing list columns after >> > some >> > >>>>> expanding operation like a join or unnest. That's a case where I >> > could >> > >>>>> imagine a lot of repetition of values. Haven't yet thought of >> common >> > >>>> cases >> > >>>>> where there is overlap but not full duplication, but am eager to >> hear >> > >>>> any. >> > >>>>> The dictionary encoding point Raphael makes is interesting, >> > especially >> > >>>>> given the existence of LargeList and FixedSizeList. For many >> > >> operations, >> > >>>> it >> > >>>>> might make more sense to just compose those existing types. >> > >>>>> >> > >>>>> IIUC the operations that would be unique to the ArrayView are ones >> > >>>> altering >> > >>>>> the shape. One could truncate each array to a certain length >> cheaply >> > >>>> simply >> > >>>>> by replacing the sizes buffer. Or perhaps there are interesting >> > >>>> operations >> > >>>>> on tensors that would benefit. >> > >>>>> >> > >>>>> On Tue, Apr 25, 2023 at 7:47 PM Raphael Taylor-Davies >> > >>>>> <r.taylordav...@googlemail.com.invalid> wrote: >> > >>>>> >> > >>>>>> Unless I am missing something, I think the selection use-case >> could >> > be >> > >>>>>> equally well served by a dictionary-encoded BinarArray/ListArray, >> > and >> > >>>>> would >> > >>>>>> have the benefit of not requiring any modifications to the >> existing >> > >>>>> format >> > >>>>>> or kernels. >> > >>>>>> >> > >>>>>> The major additional flexibility of the proposed encoding would >> be >> > >>>>>> permitting disjoint or overlapping ranges, are these common >> enough >> > in >> > >>>>>> practice to represent a meaningful bottleneck? >> > >>>>>> >> > >>>>>> >> > >>>>>> On 26 April 2023 01:40:14 BST, David Li <lidav...@apache.org >> > <mailto: >> > >> lidav...@apache.org>> wrote: >> > >>>>>>> Is there a need for a 64-bit offsets version the same way we >> have >> > >> List >> > >>>>>> and LargeList? >> > >>>>>>> And just to be clear, the difference with List is that the lists >> > >> don't >> > >>>>>> have to be stored in their logical order (or in other words, >> offsets >> > >> do >> > >>>>> not >> > >>>>>> have to be nondecreasing and so we also need sizes)? >> > >>>>>>> On Wed, Apr 26, 2023, at 09:37, Weston Pace wrote: >> > >>>>>>>> For context, there was some discussion on this back in [1]. At >> > that >> > >>>>>> time >> > >>>>>>>> this was called "sequence view" but I do not like that name. >> > >>>> However, >> > >>>>>>>> array-view array is a little confusing. Given this is similar >> to >> > >>>> list >> > >>>>>> can >> > >>>>>>>> we go with list-view array? >> > >>>>>>>> >> > >>>>>>>>> Thanks for the introduction. I'd be interested to hear about >> the >> > >>>>>>>>> applications Velox has found for these vectors, and in what >> > >>>>> situations >> > >>>>>>>> they >> > >>>>>>>>> are useful. This could be contrasted with the current >> ListArray >> > >>>>>>>>> implementations. >> > >>>>>>>> I believe one significant benefit is that take (and by proxy, >> > >>>> filter) >> > >>>>>> and >> > >>>>>>>> sort are O(# of items) with the proposed format and O(# of >> bytes) >> > >>>> with >> > >>>>>> the >> > >>>>>>>> current format. Jorge did some profiling to this effect in [1]. >> > >>>>>>>> >> > >>>>>>>> [1] >> > >>>> https://lists.apache.org/thread/49qzofswg1r5z7zh39pjvd1m2ggz2kdq< >> > >> https://lists.apache.org/thread/49qzofswg1r5z7zh39pjvd1m2ggz2kdq> >> > >>>>>>>> On Tue, Apr 25, 2023 at 3:13 PM Will Jones < >> > will.jones...@gmail.com >> > >> <mailto:will.jones...@gmail.com> >> > >>>>>> wrote: >> > >>>>>>>>> Hi Felipe, >> > >>>>>>>>> >> > >>>>>>>>> Thanks for the introduction. I'd be interested to hear about >> the >> > >>>>>>>>> applications Velox has found for these vectors, and in what >> > >>>>> situations >> > >>>>>> they >> > >>>>>>>>> are useful. This could be contrasted with the current >> ListArray >> > >>>>>>>>> implementations. >> > >>>>>>>>> >> > >>>>>>>>> IIUC it would be fairly cheap to transform a ListArray to an >> > >>>>>> ArrayView, but >> > >>>>>>>>> expensive to go the other way. >> > >>>>>>>>> >> > >>>>>>>>> Best, >> > >>>>>>>>> >> > >>>>>>>>> Will Jones >> > >>>>>>>>> >> > >>>>>>>>> On Tue, Apr 25, 2023 at 3:00 PM Felipe Oliveira Carvalho < >> > >>>>>>>>> felipe...@gmail.com<mailto:felipe...@gmail.com>> wrote: >> > >>>>>>>>> >> > >>>>>>>>>> Hi folks, >> > >>>>>>>>>> >> > >>>>>>>>>> I would like to start a public discussion on the inclusion >> of a >> > >>>> new >> > >>>>>> array >> > >>>>>>>>>> format to Arrow — array-view array. The name is also up for >> > >>>> debate. >> > >>>>>>>>>> This format is inspired by Velox's ArrayVector format [1]. >> > >>>>> Logically, >> > >>>>>>>>> this >> > >>>>>>>>>> array represents an array of arrays. Each element is an >> > >>>> array-view >> > >>>>>>>>> (offset >> > >>>>>>>>>> and size pair) that points to a range within a nested >> "values" >> > >>>>> array >> > >>>>>>>>>> (called "elements" in Velox docs). The nested array can be of >> > any >> > >>>>>> type, >> > >>>>>>>>>> which makes this format very flexible and powerful. >> > >>>>>>>>>> >> > >>>>>>>>>> [image: ../_images/array-vector.png] >> > >>>>>>>>>> < >> > >>>>> >> https://facebookincubator.github.io/velox/_images/array-vector.png< >> > >> https://facebookincubator.github.io/velox/_images/array-vector.png>> >> > >>>>>>>>>> I'm currently working on a C++ implementation and plan to >> work >> > >>>> on a >> > >>>>>> Go >> > >>>>>>>>>> implementation to fulfill the two-implementations requirement >> > for >> > >>>>>> format >> > >>>>>>>>>> changes. >> > >>>>>>>>>> >> > >>>>>>>>>> The draft design: >> > >>>>>>>>>> >> > >>>>>>>>>> - 3 buffers: [validity_bitmap, int32 offsets buffer, int32 >> sizes >> > >>>>>> buffer] >> > >>>>>>>>>> - 1 child array: "values" as an array of the type parameter >> > >>>>>>>>>> >> > >>>>>>>>>> validity_bitmap is used to differentiate between empty array >> > >>>> views >> > >>>>>>>>>> (sizes[i] == 0) and NULL array views (validity_bitmap[i] == >> 0). >> > >>>>>>>>>> >> > >>>>>>>>>> When the validity_bitmap[i] is 0, both sizes and offsets are >> > >>>>>> undefined >> > >>>>>>>>> (as >> > >>>>>>>>>> usual), and when sizes[i] == 0, offsets[i] is undefined. 0 is >> > >>>>>> recommended >> > >>>>>>>>>> if setting a value is not an issue to the system producing >> the >> > >>>>>> arrays. >> > >>>>>>>>>> offsets buffer is not required to be ordered and views don't >> > have >> > >>>>> to >> > >>>>>> be >> > >>>>>>>>>> disjoint. >> > >>>>>>>>>> >> > >>>>>>>>>> [1] >> > >>>>>>>>>> >> > >>>> >> > >> >> > >> https://facebookincubator.github.io/velox/develop/vectors.html#arrayvector >> > >> < >> > >> >> > >> https://facebookincubator.github.io/velox/develop/vectors.html#arrayvector >> > >>> >> > >>>>>>>>>> Thanks, >> > >>>>>>>>>> Felipe O. Carvalho >> > >>>>>>>>>> >> > >> >> > >> > >> >
