I think you're right Kenn.
Reuven alluded to the difficulty in inference of what to use between
AtomicType and the rest, in particular Struct<Schema>.
Go has the additional concerns around Pointer vs Non Pointer types which
isn't a concern either Python or Java have, but has implications on
pipeline efficiency that need addressing, in particular, being able to use
them in a useful fashion in the Go SDK.
I agree that long term, having schemas as a default codec would be hugely
beneficial for readability, composability, and allows more processing to be
on the Runner Harness side of a worker. (I'll save the rest of my thoughts
on Schemas in Go for the other thread, and say no more of it here.)
*Regarding my proposal for User Defined Coders:*
To avoid users accidentally preventing themselves from using Schemas in the
future, I need to remove the ability to override the default coder *(4). *Then
instead of JSON coding by default *(5)*, the SDK should be doing Schema
coding. The SDK is already doing the recursive type analysis on types at
pipeline construction time, so it's not a huge stretch to support Schemas
using that information in the future, once Runner & FnAPI support begins to
exist.
*(1)* doesn't seem to need changing, as this is the existing AtomicType
definition Kenn pointed out.
*(2)* is the specific AtomicType override.
*(3) *is the broader Go specific override for Go's unique interface
semantics. This most of the cases *(4)* would have covered anyway, but in a
targeted way.
This should still allow Go users to better control their pipeline, and
associated performance implications (which is my goal in this change),
while not making an overall incompatible choice for powerful beam features
for the common case in the future.
Does that sound right?
On Fri, 4 Jan 2019 at 10:05 Kenneth Knowles <k...@apache.org> wrote:
> On Thu, Jan 3, 2019 at 4:33 PM Reuven Lax <re...@google.com> wrote:
>
>> If a user wants custom encoding for a primitive type, they can create a
>> byte-array field and wrap that field with a Coder
>>
>
> This is the crux of the issue, right?
>
> Roughly, today, we've got:
>
> Schema ::= [ (fieldname, Type) ]
>
> Type ::= AtomicType | Array<Type> | Map<Type, Type> |
> Struct<Schema>
>
> AtomicType ::= bytes | int{16, 32, 64} | datetime | string | ...
>
> To fully replace custom encodings as they exist, you need:
>
> AtomicType ::= bytes<CustomCoder> | ...
>
> At this point, an SDK need not surface the concept of "Coder" to a user at
> all outside the bytes field concept and the wire encoding and efficient
> should be identical or nearly to what we do with coders today. PCollections
> in such an SDK have schemas, not coders, so we have successfully turned it
> completely inside-out relative to how the Java SDK does it. Is that what
> you have in mind?
>
> I really like this, but I agree with Robert that this is a major change
> that takes a bunch of work and a lot more collaborative thinking in design
> docs if we hope to get it right/stable.
>
> Kenn
>
>
>> (this is why I said that todays Coders are simply special cases); this
>> should be very rare though, as users rarely should care how Beam encodes a
>> long or a double.
>>
>>>
>>> Offhand, Schemas seem to be an alternative to pipeline construction,
>>> rather than coders for value serialization, allowing manual field
>>> extraction code to be omitted. They do not appear to be a fundamental
>>> approach to achieve it. For example, the grouping operation still needs to
>>> encode the whole of the object as a value.
>>>
>>
>> Schemas are properties of the data - essentially a Schema is the data
>> type of a PCollection. In Java Schemas are also understood by ParDo, so you
>> can write a ParDo like this:
>>
>> @ProcessElement
>> public void process(@Field("user") String userId, @Field("country")
>> String countryCode) {
>> }
>>
>> These extra functionalities are part of the graph, but they are enabled
>> by schemas.
>>
>>>
>>> As mentioned, I'm hoping to have a solution for existing coders by
>>> January's end, so waiting for your documentation doesn't work on that
>>> timeline.
>>>
>>
>> I don't think we need to wait for all the documentation to be written.
>>
>>
>>>
>>> That said, they aren't incompatible ideas as demonstrated by the Java
>>> implementation. The Go SDK remains in an experimental state. We can change
>>> things should the need arise in the next few months. Further, whenever
>>> Generics
>>> in Go
>>> <https://go.googlesource.com/proposal/+/master/design/go2draft-generics-overview.md>
>>> crop up, the existing user surface and execution stack will need to be
>>> re-written to take advantage of them anyway. That provides an opportunity
>>> to invert Coder vs Schema dependence while getting a nice performance
>>> boost, and cleaner code (and deleting much of my code generator).
>>>
>>> ----
>>>
>>> Were I to implement schemas to get the same syntatic benefits as the
>>> Java API, I'd be leveraging the field annotations Go has. This satisfies
>>> the protocol buffer issue as well, since generated go protos have name &
>>> json annotations. Schemas could be extracted that way. These are also
>>> available to anything using static analysis for more direct generation of
>>> accessors. The reflective approach would also work, which is excellent for
>>> development purposes.
>>>
>>> The rote code that the schemas were replacing would be able to be
>>> cobbled together into efficient DoFn and CombineFns for serialization. At
>>> present, it seems like it could be implemented as a side package that uses
>>> beam, rather than changing portions of the core beam Go packages, The real
>>> trick would be to do so without "apply" since that's not how the Go SDK is
>>> shaped.
>>>
>>>
>>>
>>>
>>> On Thu, 3 Jan 2019 at 15:34 Gleb Kanterov <g...@spotify.com> wrote:
>>>
>>>> Reuven, it sounds great. I see there is a similar thing to Row coders
>>>> happening in Apache Arrow <https://arrow.apache.org>, and there is a
>>>> similarity between Apache Arrow Flight
>>>> <https://www.slideshare.net/wesm/apache-arrow-at-dataengconf-barcelona-2018/23>
>>>> and data exchange service in portability. How do you see these two things
>>>> relate to each other in the long term?
>>>>
>>>> On Fri, Jan 4, 2019 at 12:13 AM Reuven Lax <re...@google.com> wrote:
>>>>
>>>>> The biggest advantage is actually readability and usability. A
>>>>> secondary advantage is that it means that Go will be able to interact
>>>>> seamlessly with BeamSQL, which would be a big win for Go.
>>>>>
>>>>> A schema is basically a way of saying that a record has a specific set
>>>>> of (possibly nested, possibly repeated) fields. So for instance let's say
>>>>> that the user's type is a struct with fields named user, country,
>>>>> purchaseCost. This allows us to provide transforms that operate on field
>>>>> names. Some example (using the Java API):
>>>>>
>>>>> PCollection users = events.apply(Select.fields("user")); // Select
>>>>> out only the user field.
>>>>>
>>>>> PCollection joinedEvents =
>>>>> queries.apply(Join.innerJoin(clicks).byFields("user")); // Join two
>>>>> PCollections by user.
>>>>>
>>>>> // For each country, calculate the total purchase cost as well as the
>>>>> top 10 purchases.
>>>>> // A new schema is created containing fields total_cost and
>>>>> top_purchases, and rows are created with the aggregation results.
>>>>> PCollection purchaseStatistics = events.apply(
>>>>> Group.byFieldNames("country")
>>>>> .aggregateField("purchaseCost", Sum.ofLongs(),
>>>>> "total_cost"))
>>>>> .aggregateField("purchaseCost", Top.largestLongs(10),
>>>>> "top_purchases"))
>>>>>
>>>>>
>>>>> This is far more readable than what we have today, and what unlocks
>>>>> this is that Beam actually knows the structure of the record instead of
>>>>> assuming records are uncrackable blobs.
>>>>>
>>>>> Note that a coder is basically a special case of a schema that has a
>>>>> single field.
>>>>>
>>>>> In BeamJava we have a SchemaRegistry which knows how to turn user
>>>>> types into schemas. We use reflection to analyze many user types (e.g.
>>>>> simple POJO structs, JavaBean classes, Avro records, protocol buffers,
>>>>> etc.) to determine the schema, however this is done only when the graph is
>>>>> initially generated. We do use code generation (in Java we do bytecode
>>>>> generation) to make this somewhat more efficient. I'm willing to bet that
>>>>> the code generator you've written for structs could be very easily
>>>>> modified
>>>>> for schemas instead, so it would not be wasted work if we went with
>>>>> schemas.
>>>>>
>>>>> One of the things I'm working on now is documenting Beam schemas. They
>>>>> are already very powerful and useful, but since there is still nothing in
>>>>> our documentation about them, they are not yet widely used. I expect to
>>>>> finish draft documentation by the end of January.
>>>>>
>>>>> Reuven
>>>>>
>>>>> On Thu, Jan 3, 2019 at 11:32 PM Robert Burke <r...@google.com> wrote:
>>>>>
>>>>>> That's an interesting idea. I must confess I don't rightly know the
>>>>>> difference between a schema and coder, but here's what I've got with a
>>>>>> bit
>>>>>> of searching through memory and the mailing list. Please let me know if
>>>>>> I'm
>>>>>> off track.
>>>>>>
>>>>>> As near as I can tell, a schema, as far as Beam takes it
>>>>>> <https://github.com/apache/beam/blob/f66eb5fe23b2500b396e6f711cdf4aeef6b31ab8/sdks/java/core/src/main/java/org/apache/beam/sdk/schemas/Schema.java>
>>>>>> is
>>>>>> a mechanism to define what data is extracted from a given row of data. So
>>>>>> in principle, there's an opportunity to be more efficient with data with
>>>>>> many columns that aren't being used, and only extract the data that's
>>>>>> meaningful to the pipeline.
>>>>>> The trick then is how to apply the schema to a given serialization
>>>>>> format, which is something I'm missing in my mental model (and then how
>>>>>> to
>>>>>> do it efficiently in Go).
>>>>>>
>>>>>> I do know that the Go client package for BigQuery
>>>>>> <https://godoc.org/cloud.google.com/go/bigquery#hdr-Schemas> does
>>>>>> something like that, using field tags. Similarly, the "encoding/json"
>>>>>> <https://golang.org/doc/articles/json_and_go.html> package in the Go
>>>>>> Standard Library permits annotating fields and it will read out and
>>>>>> deserialize the JSON fields and that's it.
>>>>>>
>>>>>> A concern I have is that Go (at present) would require pre-compile
>>>>>> time code generation for schemas to be efficient, and they would still
>>>>>> mostly boil down to turning []bytes into real structs. Go reflection
>>>>>> doesn't keep up.
>>>>>> Go has no mechanism I'm aware of to Just In Time compile more
>>>>>> efficient processing of values.
>>>>>> It's also not 100% clear how Schema's would play with protocol
>>>>>> buffers or similar.
>>>>>> BigQuery has a mechanism of generating a JSON schema from a proto file
>>>>>> <https://github.com/GoogleCloudPlatform/protoc-gen-bq-schema>, but
>>>>>> that's only the specification half, not the using half.
>>>>>>
>>>>>> As it stands, the code generator I've been building these last months
>>>>>> could (in principle) statically analyze a user's struct, and then
>>>>>> generate
>>>>>> an efficient dedicated coder for it. It just has no where to put them
>>>>>> such
>>>>>> that the Go SDK would use it.
>>>>>>
>>>>>>
>>>>>> On Thu, Jan 3, 2019 at 1:39 PM Reuven Lax <re...@google.com> wrote:
>>>>>>
>>>>>>> I'll make a different suggestion. There's been some chatter that
>>>>>>> schemas are a better tool than coders, and that in Beam 3.0 we should
>>>>>>> make
>>>>>>> schemas the basic semantics instead of coders. Schemas provide
>>>>>>> everything a
>>>>>>> coder provides, but also allows for far more readable code. We can't
>>>>>>> make
>>>>>>> such a change in Beam Java 2.X for compatibility reasons, but maybe in
>>>>>>> Go
>>>>>>> we're better off starting with schemas instead of coders?
>>>>>>>
>>>>>>> Reuven
>>>>>>>
>>>>>>> On Thu, Jan 3, 2019 at 8:45 PM Robert Burke <rob...@frantil.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> One area that the Go SDK currently lacks: is the ability for users
>>>>>>>> to specify their own coders for types.
>>>>>>>>
>>>>>>>> I've written a proposal document,
>>>>>>>> <https://docs.google.com/document/d/1kQwx4Ah6PzG8z2ZMuNsNEXkGsLXm6gADOZaIO7reUOg/edit#>
>>>>>>>> and
>>>>>>>> while I'm confident about the core, there are certainly some edge cases
>>>>>>>> that require discussion before getting on with the implementation.
>>>>>>>>
>>>>>>>> At presently, the SDK only permits primitive value types (all
>>>>>>>> numeric types but complex, strings, and []bytes) which are coded with
>>>>>>>> beam
>>>>>>>> coders, and structs whose exported fields are of those type, which is
>>>>>>>> then
>>>>>>>> encoded as JSON. Protocol buffer support is hacked in to avoid the type
>>>>>>>> anaiyzer, and presents the current work around this issue.
>>>>>>>>
>>>>>>>> The high level proposal is to catch up with Python and Java, and
>>>>>>>> have a coder registry. In addition, arrays, and maps should be
>>>>>>>> permitted as
>>>>>>>> well.
>>>>>>>>
>>>>>>>> If you have alternatives, or other suggestions and opinions, I'd
>>>>>>>> love to hear them! Otherwise my intent is to get a PR ready by the end
>>>>>>>> of
>>>>>>>> January.
>>>>>>>>
>>>>>>>> Thanks!
>>>>>>>> Robert Burke
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>> --
>>>>>> http://go/where-is-rebo
>>>>>>
>>>>>
>>>>
>>>> --
>>>> Cheers,
>>>> Gleb
>>>>
>>>
