+1 on what Ian said.

And as I write kernels for this new format, I’m learning that it’s possible
to re-use the common infrastructure used by List and LargeList to implement
the ListView related features with some adjustments.

IMO having this format as a second-class citizen would more likely
complicate things because it would make this unification harder.

—
Felipe

On Tue, 6 Jun 2023 at 18:45 Ian Cook <ianmc...@apache.org> wrote:

> To clarify why we cannot simply propose adding ListView as a new
> “canonical extension type”: The extension type mechanism in Arrow
> depends on the underlying data being organized in an existing Arrow
> layout—that way an implementation that does not support the extension
> type can still handle the underlying data. But ListView is a wholly
> new layout.
>
> I strongly agree with Weston’s idea that it is a good time for Arrow
> to introduce the notion of “canonical alternative layouts.”
>
> Taken together, I think that canonical extension types and canonical
> alternative layouts could serve as an “incubator” for proposed new
> representations. For example, if a proposed canonical alternative
> layout ends up being broadly adopted, then that will serve as a signal
> that we should consider adding it as a primary layout in the core
> spec.
>
> It seems to me that most projects that are implementing Arrow today
> are not aiming to provide complete coverage of Arrow; rather they are
> adopting Arrow because of its role as a standard and they are
> implementing only as much of the Arrow standard as they require to
> achieve some goal. I believe that such projects are important Arrow
> stakeholders, and I believe that this proposed notion of canonical
> alternative layouts will serve them well and will create efficiencies
> by standardizing implementations around a shared set of alternatives.
>
> However I think that the documentation for canonical alternative
> layouts should strongly encourage implementers to default to using the
> primary layouts defined in the core spec and only use alternative
> layouts in cases where the primary layouts do not meet their needs.
>
>
> On Sat, May 27, 2023 at 7:44 PM Micah Kornfield <emkornfi...@gmail.com>
> wrote:
> >
> > This sounds reasonable to me but my main concern is, I'm not sure there
> is
> > a great mechanism to enforce canonical layouts don't somehow become
> default
> > (or the only implementation).
> >
> > Even for these new layouts, I think it might be worth rethinking binding
> a
> > layout into the schema versus having a different concept of encoding (and
> > changing some of the corresponding data structures).
> >
> >
> > On Mon, May 22, 2023 at 10:37 AM Weston Pace <weston.p...@gmail.com>
> wrote:
> >
> > > Trying to settle on one option is a fruitless endeavor.  Each type has
> pros
> > > and cons.  I would also predict that the largest existing usage of
> Arrow is
> > > shuttling data from one system to another.  The newly proposed format
> > > doesn't appear to have any significant advantage for that use case (if
> > > anything, the existing format is arguably better as it is more
> compact).
> > >
> > > I am very biased towards historical precedent and avoiding breaking
> > > changes.
> > >
> > > We have "canonical extension types", perhaps it is time for "canonical
> > > alternative layouts".  We could define it as such:
> > >
> > >  * There are one or more primary layouts
> > >    * Existing layouts are automatically considered primary layouts,
> even if
> > > they wouldn't
> > >      have been primary layouts initially (e.g. large list)
> > >  * A new layout, if it is semantically equivalent to another, is
> considered
> > > an alternative layout
> > >  * An alternative layout still has the same requirements for adoption
> (two
> > > implementations and a vote)
> > >    * An implementation should not feel pressured to rush and implement
> the
> > > new layout.
> > >      It would be good if they contribute in the discussion and
> consider the
> > > layout and vote
> > >      if they feel it would be an acceptable design.
> > >  * We can define and vote and approve as many canonical alternative
> layouts
> > > as we want:
> > >    * A canonical alternative layout should, at a minimum, have some
> > >      reasonable justification, such as improved performance for
> algorithm X
> > >  * Arrow implementations MUST support the primary layouts
> > >  * An Arrow implementation MAY support a canonical alternative,
> however:
> > >    * An Arrow implementation MUST first support the primary layout
> > >    * An Arrow implementation MUST support conversion to/from the
> primary
> > > and canonical layout
> > >    * An Arrow implementation's APIs MUST only provide data in the
> > > alternative
> > >      layout if it is explicitly asked for (e.g. schema inference should
> > > prefer the primary layout).
> > >  * We can still vote for new primary layouts (e.g. promoting a
> canonical
> > > alternative) but, in these
> > >     votes we don't only consider the value (e.g. performance) of the
> layout
> > > but also the interoperability.
> > >     In other words, a layout can only become a primary layout if there
> is
> > > significant evidence that most
> > >     implementations plan to adopt it.
> > >
> > > This lets us evolve support for new layouts more naturally.  We can
> > > generally assume that users will not, initially, be aware of these
> > > alternative layouts.  However, everything will just work.  They may
> start
> > > to see a performance penalty stemming from a lack of support for these
> > > layouts.  If this performance penalty becomes significant then they
> will
> > > discover it and become aware of the problem.  They can then ask
> whatever
> > > library they are using to add support for the alternative layout.  As
> > > enough users find a need for it then libraries will add support.
> > > Eventually, enough libraries will support it that we can adopt it as a
> > > primary layout.
> > >
> > > Also, it allows libraries to adopt alternative layouts more
> aggressively if
> > > they would like while still hopefully ensuring that we eventually all
> > > converge on the same implementation of the alternative layout.
> > >
> > > On Mon, May 22, 2023 at 9:35 AM Will Jones <will.jones...@gmail.com>
> > > wrote:
> > >
> > > > Hello Arrow devs,
> > > >
> > > > I don't understand why we would start deprecating features in the
> Arrow
> > > > > format. Even starting this talk might already be a bad idea
> PR-wise.
> > > > >
> > > >
> > > > I agree we don't want to make breaking changes to the Arrow format.
> But
> > > > several maintainers have already stated they have no interest in
> > > > maintaining both list types with full compute functionality [1][2],
> so I
> > > > think it's very likely one list type or the other will be
> > > > implicitly preferred in the ecosystem if this data type was added.
> If
> > > > that's the case, I'd prefer that we agreed as a community which one
> > > should
> > > > be preferred. Maybe that's not the best path; it's just one way for
> us to
> > > > balance stability, maintenance burden, and relevance.
> > > >
> > > > Can someone help distill down the primary rationale and usecase for
> > > > > adding ArrayView to the Arrow Spec?
> > > > >
> > > >
> > > > Looking back at that old thread, I think one of the main motivations
> is
> > > to
> > > > try to prevent query engine implementers from feeling there is a
> tradeoff
> > > > between having state-of-the-art performance and being Arrow-native.
> For
> > > > some of the new array types, we had both Velox and DuckDB use them,
> so it
> > > > was reasonable to expect they were innovations that might
> proliferate.
> > > I'm
> > > > not sure if the ArrayView is part of that. From Wes earlier [3]:
> > > >
> > > > The idea is that in a world of data and query federation (for
> example,
> > > > > consider [1] where Arrow is being used as a data federation layer
> with
> > > > many
> > > > > query engines), we want to increase the amount of data in-flight
> and
> > > > > in-memory that is in Arrow format. So if query engines are having
> to
> > > > depart
> > > > > substantially from the Arrow format to get performance, then this
> > > > creates a
> > > > > potential lose-lose situation: * Depart from Arrow: get better
> > > > performance
> > > > > but pay serialization costs to read and write Arrow (the
> performance
> > > and
> > > > > resource utilization benefits outweigh the serialization costs).
> This
> > > > puts
> > > > > additional pressure on query engines to build specialized
> components
> > > for
> > > > > solving problems rather than making use of off-the-shelf components
> > > that
> > > > > use Arrow. This has knock-on effects on ecosystem fragmentation. *
> Or
> > > use
> > > > > Arrow, and accept suboptimal query processing performance
> > > > >
> > > >
> > > >
> > > > Will mentions one usecase is Velox consuming python UDF output, which
> > > seems
> > > > > to be mostly about how fast Velox can consume this format, not how
> fast
> > > > it
> > > > > can be written. Are there other usecases?
> > > > >
> > > >
> > > > To be clear, I don't know if that's the use case they want. That's
> just
> > > me
> > > > speculating.
> > > >
> > > > I still have some questions myself:
> > > >
> > > > 1. Is this array type currently only used in Velox? (not DuckDB like
> some
> > > > of the other new types?) What evidence do we have that it will become
> > > used
> > > > outside of Velox?
> > > > 2. 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
> > > >
> > > > [1] https://lists.apache.org/thread/smn13j1rnt23mb3fwx75sw3f877k3nwx
> > > > [2] https://lists.apache.org/thread/cc4w3vs3foj1fmpq9x888k51so60ftr3
> > > > [3] https://lists.apache.org/thread/mk2yn62y6l8qtngcs1vg2qtwlxzbrt8t
> > > >
> > > > On Mon, May 22, 2023 at 3:48 AM Andrew Lamb <al...@influxdata.com>
> > > wrote:
> > > >
> > > > > Can someone help distill down the primary rationale and usecase for
> > > > > adding ArrayView to the Arrow Spec?
> > > > >
> > > > > From the above discussions, the stated rationale seems to be fast
> > > > > (zero-copy) interchange with Velox.
> > > > >
> > > > > This thread has qualitatively enumerated the benefits of
> (offset+len)
> > > > > encoding over the existing Arrow ListArray (offets) approach, but I
> > > > haven't
> > > > > seen any performance measurements that might help us to gauge the
> > > > tradeoff
> > > > > in additional complexity vs runtime overhead.
> > > > >
> > > > > Will mentions one usecase is Velox consuming python UDF output,
> which
> > > > seems
> > > > > to be mostly about how fast Velox can consume this format, not how
> fast
> > > > it
> > > > > can be written. Are there other usecases?
> > > > >
> > > > > Do we have numbers showing how much overhead converting to /from
> > > Velox's
> > > > > internal representation and the existing ListArray adds? Has
> anyone in
> > > > > Velox land considered adding faster support for Arrow style
> ListArray
> > > > > encoding?
> > > > >
> > > > >
> > > > > Andrew
> > > > >
> > > > > On Mon, May 22, 2023 at 4:38 AM Antoine Pitrou <anto...@python.org
> >
> > > > wrote:
> > > > >
> > > > > >
> > > > > > Hi,
> > > > > >
> > > > > > I don't understand why we would start deprecating features in the
> > > Arrow
> > > > > > format. Even starting this talk might already be a bad idea
> PR-wise.
> > > > > >
> > > > > > As for implementing conversions at the I/O boundary, it's a
> > > reasonably
> > > > > > policy, but it still requires work by implementors and it's not
> > > granted
> > > > > > that all consumers of the Arrow format will grow such conversions
> > > > > > if/when we add non-trivial types such as ListView or StringView.
> > > > > >
> > > > > > Regards
> > > > > >
> > > > > > Antoine.
> > > > > >
> > > > > >
> > > > > > Le 22/05/2023 à 00:39, Will Jones a écrit :
> > > > > > > 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
> > > > > > >>>>>>>>>>>>>>
> > > > > > >>>>>>
> > > > > > >>>>
> > > > > > >>>>
> > > > > > >>>
> > > > > > >>
> > > > > > >
> > > > > >
> > > > >
> > > >
> > >
>

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