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Re: Schema Aware PCollections


Yes, this should be possible eventually. In fact, limited version of this functionality is already supported for Beans (e.g. see this test), but it's still experimental and there are no good end-to-end examples yet.

Regards,
Anton

On Wed, Aug 8, 2018 at 5:45 AM Akanksha Sharma B <akanksha.b.sharma@xxxxxxxxxxxx> wrote:

Hi,


(changed the email-subject to make it generic)


It is mentioned in Schema-Aware PCollections design doc (https://docs.google.com/document/d/1tnG2DPHZYbsomvihIpXruUmQ12pHGK0QIvXS1FOTgRc)


"There are a number of existing data types from which schemas can be inferred. Protocol buffers, Avro objects, Json objects, POJOs, primitive Java types - all of these have schemas that can be inferred from the type itself at pipeline-construction time. We should be able to automatically infer these schemas with a minimum of involvement from the programmer. "


Can I assume that the following usecase will be possible sometime in future :-
"read parquet (along with inferred schema) into something like dataframe or Beam Rows. And vice versa for write i.e. get rows and write parquet based on Row's schema.""

Regards,
Akanksha


From: Chamikara Jayalath <chamikara@xxxxxxxxxx>
Sent: Wednesday, August 1, 2018 3:57 PM
To: user@xxxxxxxxxxxxxxx
Cc: dev@xxxxxxxxxxxxxxx
Subject: Re: pipeline with parquet and sql
 


On Wed, Aug 1, 2018 at 1:12 AM Akanksha Sharma B <akanksha.b.sharma@xxxxxxxxxxxx> wrote:

Hi,


Thanks. I understood the Parquet point. I will wait for couple of days on this topic. Even if this scenario cannot be achieved now, any design document or future plans towards this direction will also be helpful to me.


To summarize, I do not understand beam well enough, can someone please help me and comment whether the following fits with beam's model and future direction :-

"read parquet (along with inferred schema) into something like dataframe or Beam Rows.
And vice versa for write i.e. get rows and write parquet based on Row's schema."

Beam currently does not have a standard message format. A Beam pipeline consists of PCollections and transforms (that converts PCollections to other PCollections). You can transform the PCollection read from Parquet using a ParDo and writing the resulting transform back to Parquet format. I think Schema aware PCollections [1] might be close to what you need but not sure if it fulfills your exact requirement.

Thanks,
Cham

 



Regards,

Akanksha



From: Łukasz Gajowy <lukasz.gajowy@xxxxxxxxx>
Sent: Tuesday, July 31, 2018 12:43:32 PM
To: user@xxxxxxxxxxxxxxx
Cc: dev@xxxxxxxxxxxxxxx
Subject: Re: pipeline with parquet and sql
 
In terms of schema and ParquetIO source/sink, there was an answer in some previous thread: 

Currently (without introducing any change in ParquetIO) there is no way to not pass the avro schema. It will probably be replaced with Beam's schema in the future () 

[1] https://lists.apache.org/thread.html/a466ddeb55e47fd780be3bcd8eec9d6b6eaf1dfd566ae5278b5fb9e8@%3Cuser.beam.apache.org%3E


wt., 31 lip 2018 o 10:19 Akanksha Sharma B <akanksha.b.sharma@xxxxxxxxxxxx> napisał(a):

Hi,


I am hoping to get some hints/pointers from the experts here.

I hope the scenario described below was understandable. I hope it is a valid use-case. Please let me know if I need to explain the scenario better.


Regards,

Akanksha



From: Akanksha Sharma B
Sent: Friday, July 27, 2018 9:44 AM
To: dev@xxxxxxxxxxxxxxx
Subject: Re: pipeline with parquet and sql
 

Hi,


Please consider following pipeline:-


Source is Parquet file, having hundreds of columns.

Sink is Parquet. Multiple output parquet files are generated after applying some sql joins. Sql joins to be applied differ for each output parquet file. Lets assume we have a sql queries generator or some configuration file with the needed info.


Can this be implemented generically, such that there is no need of the schema of the parquet files involved or any intermediate POJO or beam schema.

i.e. the way spark can handle it - read parquet into dataframe, create temp view and apply sql queries to it, and write it back to parquet.


As I understand, beam SQL needs (Beam Schema or POJOs) and parquetIO needs avro schemas. Ideally we dont want to see POJOs or schemas.
If there is a way we can achieve this with beam, please do help.

Regards,
Akanksha


From: Akanksha Sharma B
Sent: Tuesday, July 24, 2018 4:47:25 PM
To: user@xxxxxxxxxxxxxxx
Subject: pipeline with parquet and sql
 

Hi,


Please consider following pipeline:-


Source is Parquet file, having hundreds of columns.

Sink is Parquet. Multiple output parquet files are generated after applying some sql joins. Sql joins to be applied differ for each output parquet file. Lets assume we have a sql queries generator or some configuration file with the needed info.


Can this be implemented generically, such that there is no need of the schema of the parquet files involved or any intermediate POJO or beam schema.

i.e. the way spark can handle it - read parquet into dataframe, create temp view and apply sql queries to it, and write it back to parquet.


As I understand, beam SQL needs (Beam Schema or POJOs) and parquetIO needs avro schemas. Ideally we dont want to see POJOs or schemas.
If there is a way we can achieve this with beam, please do help.

Regards,
Akanksha