On Thu, Jan 3, 2019 at 4:33 PM Reuven Lax <[email protected]> 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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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 <[email protected]>
>>>>>> 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
>>>
>>
