Le 26 avr. 2018 23:13, "Anton Kedin" <ke...@google.com> a écrit :
BeamRecord (Row) has very little in common with JsonObject (I assume you're
talking about javax.json), except maybe some similarities of the API. Few
reasons why JsonObject doesn't work:
- it is a Java EE API:
- Beam SDK is not limited to Java. There are probably similar APIs
for other languages but they might not necessarily carry the
same semantics
/ APIs;
Not a big deal I think. At least not a technical blocker.
- It can change between Java versions;
No, this is javaee ;).
- Current Beam java implementation is an experimental feature to
identify what's needed from such API, in the end we might end up with
something similar to JsonObject API, but likely not
I dont get that point as a blocker
- ;
- represents JSON, which is not an API but an object notation:
- it is defined as unicode string in a certain format. If you choose
to adhere to ECMA-404, then it doesn't sound like JsonObject can
represent
an Avro object, if I'm reading it right;
It is in the generator impl, you can impl an avrogenerator.
- doesn't define a type system (JSON does, but it's lacking):
- for example, JSON doesn't define semantics for numbers;
- doesn't define date/time types;
- doesn't allow extending JSON type system at all;
That is why you need a metada object, or simpler, a schema with that data.
Json or beam record doesnt help here and you end up on the same outcome if
you think about it.
- lacks schemas;
Jsonschema are standard, widely spread and tooled compared to alternative.
You can definitely try loosen the requirements and define everything in
JSON in userland, but the point of Row/Schema is to avoid it and define
everything in Beam model, which can be extended, mapped to JSON, Avro,
BigQuery Schemas, custom binary format etc., with same semantics across
beam SDKs.
This is what jsonp would allow with the benefit of a natural pojo support
through jsonb.
On Thu, Apr 26, 2018 at 12:28 PM Romain Manni-Bucau <rmannibu...@gmail.com>
wrote:
> Just to let it be clear and let me understand: how is BeamRecord different
> from a JsonObject which is an API without implementation (not event a json
> one OOTB)? Advantage of json *api* are indeed natural mapping (jsonb is
> based on jsonp so no new binding to reinvent) and simple serialization
> (json+gzip for ex, or avro if you want to be geeky).
>
> I fail to see the point to rebuild an ecosystem ATM.
>
> Le 26 avr. 2018 19:12, "Reuven Lax" <re...@google.com> a écrit :
>
>> Exactly what JB said. We will write a generic conversion from Avro (or
>> json) to Beam schemas, which will make them work transparently with SQL.
>> The plan is also to migrate Anton's work so that POJOs works generically
>> for any schema.
>>
>> Reuven
>>
>> On Thu, Apr 26, 2018 at 1:17 AM Jean-Baptiste Onofré <j...@nanthrax.net>
>> wrote:
>>
>>> For now we have a generic schema interface. Json-b can be an impl, avro
>>> could be another one.
>>>
>>> Regards
>>> JB
>>> Le 26 avr. 2018, à 12:08, Romain Manni-Bucau <rmannibu...@gmail.com> a
>>> écrit:
>>>>
>>>> Hmm,
>>>>
>>>> avro has still the pitfalls to have an uncontrolled stack which brings
>>>> way too much dependencies to be part of any API,
>>>> this is why I proposed a JSON-P based API (JsonObject) with a custom
>>>> beam entry for some metadata (headers "à la Camel").
>>>>
>>>>
>>>> Romain Manni-Bucau
>>>> @rmannibucau <https://twitter.com/rmannibucau> | Blog
>>>> <https://rmannibucau.metawerx.net/> | Old Blog
>>>> <http://rmannibucau.wordpress.com> | Github
>>>> <https://github.com/rmannibucau> | LinkedIn
>>>> <https://www.linkedin.com/in/rmannibucau> | Book
>>>> <https://www.packtpub.com/application-development/java-ee-8-high-performance>
>>>>
>>>> 2018-04-26 9:59 GMT+02:00 Jean-Baptiste Onofré <j...@nanthrax.net>:
>>>>
>>>>> Hi Ismael
>>>>>
>>>>> You mean directly in Beam SQL ?
>>>>>
>>>>> That will be part of schema support: generic record could be one of
>>>>> the payload with across schema.
>>>>>
>>>>> Regards
>>>>> JB
>>>>> Le 26 avr. 2018, à 11:39, "Ismaël Mejía" < ieme...@gmail.com> a
>>>>> écrit:
>>>>>>
>>>>>> Hello Anton,
>>>>>>
>>>>>> Thanks for the descriptive email and the really useful work. Any plans
>>>>>> to tackle PCollections of GenericRecord/IndexedRecords? it seems Avro
>>>>>> is a natural fit for this approach too.
>>>>>>
>>>>>> Regards,
>>>>>> Ismaël
>>>>>>
>>>>>> On Wed, Apr 25, 2018 at 9:04 PM, Anton Kedin <ke...@google.com> wrote:
>>>>>>
>>>>>>
>>>>>>> Hi,
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> I want to highlight a couple of improvements to Beam SQL we have been
>>>>>>>
>>>>>>> working on recently which are targeted to make Beam SQL API easier to
>>>>>>> use.
>>>>>>>
>>>>>>> Specifically these features simplify conversion of Java Beans and JSON
>>>>>>>
>>>>>>> strings to Rows.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Feel free to try this and send any bugs/comments/PRs my way.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> **Caveat: this is still work in progress, and has known bugs and
>>>>>>> incomplete
>>>>>>>
>>>>>>> features, see below for details.**
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Background
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Beam SQL queries can only be applied to PCollection<Row>. This means
>>>>>>> that
>>>>>>>
>>>>>>> users need to convert whatever PCollection elements they have to Rows
>>>>>>> before
>>>>>>>
>>>>>>> querying them with SQL. This usually requires manually creating a
>>>>>>> Schema and
>>>>>>>
>>>>>>> implementing a custom conversion PTransform<PCollection<
>>>>>>> Element>,
>>>>>>>
>>>>>>> PCollection<Row>> (see Beam SQL Guide).
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> The improvements described here are an attempt to reduce this overhead
>>>>>>> for
>>>>>>>
>>>>>>> few common cases, as a start.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Status
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Introduced a InferredRowCoder to automatically generate rows from
>>>>>>> beans.
>>>>>>>
>>>>>>> Removes the need to manually define a Schema and Row conversion logic;
>>>>>>>
>>>>>>> Introduced JsonToRow transform to automatically parse JSON objects to
>>>>>>> Rows.
>>>>>>>
>>>>>>> Removes the need to manually implement a conversion logic;
>>>>>>>
>>>>>>> This is still experimental work in progress, APIs will likely change;
>>>>>>>
>>>>>>> There are known bugs/unsolved problems;
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Java Beans
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Introduced a coder which facilitates Rows generation from Java Beans.
>>>>>>>
>>>>>>> Reduces the overhead to:
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>> /** Some user-defined Java Bean */
>>>>>>>>
>>>>>>>> class JavaBeanObject implements Serializable {
>>>>>>>>
>>>>>>>> String getName() { ... }
>>>>>>>>
>>>>>>>> }
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> // Obtain the objects:
>>>>>>>>
>>>>>>>> PCollection<JavaBeanObject> javaBeans = ...;
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> // Convert to Rows and apply a SQL query:
>>>>>>>>
>>>>>>>> PCollection<Row> queryResult =
>>>>>>>>
>>>>>>>> javaBeans
>>>>>>>>
>>>>>>>> .setCoder(InferredRowCoder.
>>>>>>>> ofSerializable(JavaBeanObject.
>>>>>>>> class))
>>>>>>>>
>>>>>>>> .apply(BeamSql.query("SELECT name FROM PCOLLECTION"));
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Notice, there is no more manual Schema definition or custom conversion
>>>>>>>
>>>>>>> logic.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Links
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> example;
>>>>>>>
>>>>>>> InferredRowCoder;
>>>>>>>
>>>>>>> test;
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> JSON
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Introduced JsonToRow transform. It is possible to query a
>>>>>>>
>>>>>>> PCollection<String> that contains JSON objects like this:
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>> // Assuming JSON objects look like this:
>>>>>>>>
>>>>>>>> // { "type" : "foo", "size" : 333 }
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> // Define a Schema:
>>>>>>>>
>>>>>>>> Schema jsonSchema =
>>>>>>>>
>>>>>>>> Schema
>>>>>>>>
>>>>>>>> .builder()
>>>>>>>>
>>>>>>>> .addStringField("type")
>>>>>>>>
>>>>>>>> .addInt32Field("size")
>>>>>>>>
>>>>>>>> .build();
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> // Obtain PCollection of the objects in JSON format:
>>>>>>>>
>>>>>>>> PCollection<String> jsonObjects = ...
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> // Convert to Rows and apply a SQL query:
>>>>>>>>
>>>>>>>> PCollection<Row> queryResults =
>>>>>>>>
>>>>>>>> jsonObjects
>>>>>>>>
>>>>>>>> .apply(JsonToRow.withSchema(
>>>>>>>> jsonSchema))
>>>>>>>>
>>>>>>>> .apply(BeamSql.query("SELECT type, AVG(size) FROM PCOLLECTION GROUP BY
>>>>>>>>
>>>>>>>> type"));
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Notice, JSON to Row conversion is done by JsonToRow transform. It is
>>>>>>>
>>>>>>> currently required to supply a Schema.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Links
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> JsonToRow;
>>>>>>>
>>>>>>> test/example;
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Going Forward
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> fix bugs (BEAM-4163, BEAM-4161 ...)
>>>>>>>
>>>>>>> implement more features (BEAM-4167, more types of objects);
>>>>>>>
>>>>>>> wire this up with sources/sinks to further simplify SQL API;
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Thank you,
>>>>>>>
>>>>>>> Anton
>>>>>>>
>>>>>>>
>>>>>>>
>>>>
