Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Ismaël Mejía]

Vincent, I will be out in the sense that I cannot really engage myself into more
activities because I have apart of your review two more pending + other work to
finish so I prefer not to add more work I cannot finish. I am still available
for the review however so let’s get this finally finished there. Thanks for
pointing this because it made me realize that I missed one important part in my
last message that was oriented towards a better solution but ignoring the
ongoing work.

Even if it has limitations it seems that the ReadAll based on PCollection
approach has clear benefits and Vincent’s use case is one more instance, so I
would like to propose that for the in-progress PRs we keep it as proposed until
we find a better solution. Notice however that in every case ReadAll is a new
feature and should be marked still as @Experimental so we can still improve it /
change course.

On Wed, Jul 15, 2020 at 1:02 AM Vincent Marquez
 wrote:
>
> Hi everyone, i've been working on 
> https://issues.apache.org/jira/browse/BEAM-9008 for quite some time now, 
> trying to contribute back the much improved Cassandra connector.  I 
> originally had been passing around a 'config' object to the readAll, but 
> after much discussion with Ismaël we decided it was best if I refactor to the 
> readAll taking a Read as a parameter to be more uniform with some of the 
> other Connectors.
>
> I don't see a use case for using Read as a key itself, especially for the 
> CassandraIO's Read given it itself contains functions (Equality and functions 
> just seem like a weird thing to even try to deal with).
>
> For Ismaël and others, I would like to get this merged in sometime soon, as I 
> believe it has all of the requested functionality.  If Ismaël is leaving for 
> a month, is there someone else who could help me with this?
>
>
> ~Vincent
>
>
> On Tue, Jul 14, 2020 at 2:56 PM Ismaël Mejía  wrote:
>>
>> It has been really interesting to read all the perspectives in this thread 
>> and I
>> have even switched sides back and forth given the advantages / issues exposed
>> here, so it means we have clear pros/cons.
>>
>> One ‘not so nice‘ discovery related to this discussion for me was BEAM-10375 
>> [1]
>> tldr; Reads use java serialization so they don’t have a default deterministic
>> coder and if they are used as keys they break on GbK because Java’s
>> implementation requires keys to be deterministic [2] (is this the case in all
>> the other languages?). We can workaround this by having an alternative Coder 
>> for
>> Reads but somehow it does not feel natural and adds extra maintenance.
>>
>> I really like Kenn’s idea that we should rethink from scratch or write a
>> proposal of how we can have designed this with the present awareness about 
>> DoFn
>> based composition, code reuse and schema friendliness. Maybe worth to 
>> enumerate
>> what are the essentials we want to have (or not) first. I will be OOO for the
>> next month so I cannot actively work on this, but I will be interested on
>> reviewing/contributing in case someone wants to take the lead on a better
>> solution or we can in the meantime keep bringing ideas to this thread.
>>
>> Configuration based on functions translates hardly across languages so I 
>> wonder
>> if we should have also a mechanism to map those. Notice that an important use
>> case of this is the detailed configuration of clients for IOs which we have
>> started to expose in some IOs to avoid filling IOs API with ‘knobs‘ and 
>> better
>> let the user do their tuning by providing a client via a function.
>>
>> [1] https://issues.apache.org/jira/browse/BEAM-10375
>> [2] 
>> https://github.com/apache/beam/blob/a9d70fed9069c4f4e9a12860ef711652f5f9c21a/sdks/java/core/src/main/java/org/apache/beam/sdk/transforms/GroupByKey.java#L232-L237
>>
>> On Thu, Jul 9, 2020 at 5:52 AM Kenneth Knowles  wrote:
>> >
>> > If we are forced to create a fresh class due to a breaking change, let's 
>> > migrate to the "what we would do from scratch" approach, please.
>> >
>> > Kenn
>> >
>> > On Wed, Jul 8, 2020 at 5:15 PM Robert Bradshaw  wrote:
>> >>
>> >> OK, I'm +0 on this change. Using the PTransform as an element is
>> >> probably better than duplicating the full API on another interface,
>> >> and think it's worth getting this ublocked. This will require a Read2
>> >> if we have to add options in a upgrade-compatible way.
>> >>
>> >> On Tue, Jul 7, 2020 at 3:19 PM Luke Cwik  wrote:
>> >> >
>> >> > Robert, you're correct in your understanding that the Read PTransform 
>> >> > would be encoded via the schema coder.
>> >> >
>> >> > Kenn, different serializers are ok as long as the output coder can 
>> >> > encode/decode the output type. Different watermark fns are also ok 
>> >> > since it is about computing the watermark for each individual source 
>> >> > and won't impact the watermark computed by other sources. Watermark 
>> >> > advancement will still be held back by the source that is furthest 
>> >> > behind and 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Ismaël Mejía]

It has been really interesting to read all the perspectives in this thread and I
have even switched sides back and forth given the advantages / issues exposed
here, so it means we have clear pros/cons.

One ‘not so nice‘ discovery related to this discussion for me was BEAM-10375 [1]
tldr; Reads use java serialization so they don’t have a default deterministic
coder and if they are used as keys they break on GbK because Java’s
implementation requires keys to be deterministic [2] (is this the case in all
the other languages?). We can workaround this by having an alternative Coder for
Reads but somehow it does not feel natural and adds extra maintenance.

I really like Kenn’s idea that we should rethink from scratch or write a
proposal of how we can have designed this with the present awareness about DoFn
based composition, code reuse and schema friendliness. Maybe worth to enumerate
what are the essentials we want to have (or not) first. I will be OOO for the
next month so I cannot actively work on this, but I will be interested on
reviewing/contributing in case someone wants to take the lead on a better
solution or we can in the meantime keep bringing ideas to this thread.

Configuration based on functions translates hardly across languages so I wonder
if we should have also a mechanism to map those. Notice that an important use
case of this is the detailed configuration of clients for IOs which we have
started to expose in some IOs to avoid filling IOs API with ‘knobs‘ and better
let the user do their tuning by providing a client via a function.

[1] https://issues.apache.org/jira/browse/BEAM-10375
[2] 
https://github.com/apache/beam/blob/a9d70fed9069c4f4e9a12860ef711652f5f9c21a/sdks/java/core/src/main/java/org/apache/beam/sdk/transforms/GroupByKey.java#L232-L237

On Thu, Jul 9, 2020 at 5:52 AM Kenneth Knowles  wrote:
>
> If we are forced to create a fresh class due to a breaking change, let's 
> migrate to the "what we would do from scratch" approach, please.
>
> Kenn
>
> On Wed, Jul 8, 2020 at 5:15 PM Robert Bradshaw  wrote:
>>
>> OK, I'm +0 on this change. Using the PTransform as an element is
>> probably better than duplicating the full API on another interface,
>> and think it's worth getting this ublocked. This will require a Read2
>> if we have to add options in a upgrade-compatible way.
>>
>> On Tue, Jul 7, 2020 at 3:19 PM Luke Cwik  wrote:
>> >
>> > Robert, you're correct in your understanding that the Read PTransform 
>> > would be encoded via the schema coder.
>> >
>> > Kenn, different serializers are ok as long as the output coder can 
>> > encode/decode the output type. Different watermark fns are also ok since 
>> > it is about computing the watermark for each individual source and won't 
>> > impact the watermark computed by other sources. Watermark advancement will 
>> > still be held back by the source that is furthest behind and still has the 
>> > same problems when a user chooses a watermark fn that was incompatible 
>> > with the windowing strategy for producing output (e.g. global window + 
>> > default trigger + streaming pipeline).
>> >
>> > Both are pretty close so if we started from scratch then it could go 
>> > either way but we aren't starting from scratch (I don't think a Beam 3.0 
>> > is likely to happen in the next few years as there isn't enough stuff that 
>> > we want to remove vs the amount of stuff we would gain).
>> >
>> > On Tue, Jul 7, 2020 at 2:57 PM Kenneth Knowles  wrote:
>> >>
>> >> On Tue, Jul 7, 2020 at 2:24 PM Robert Bradshaw  
>> >> wrote:
>> >>>
>> >>> On Tue, Jul 7, 2020 at 2:06 PM Luke Cwik  wrote:
>> >>> >
>> >>> > Robert, the intent is that the Read object would use a schema coder 
>> >>> > and for XLang purposes would be no different then a POJO.
>> >>>
>> >>> Just to clarify, you're saying that the Read PTransform would be
>> >>> encoded via the schema coder? That still feels a bit odd (and
>> >>> specificically if we were designing IO from scratch rather than
>> >>> adapting to what already exists would we choose to use PTransforms as
>> >>> elements?) but would solve the cross language issue.
>> >>
>> >>
>> >> I like this question. If we were designing from scratch, what would we 
>> >> do? Would we encourage users to feed Create.of(SourceDescriptor) into 
>> >> ReadAll? We would probably provide a friendly wrapper for reading one 
>> >> static thing, and call it Read. But it would probably have an API like 
>> >> Read.from(SourceDescriptor), thus eliminating duplicate documentation and 
>> >> boilerplate that Luke described while keeping the separation that Brian 
>> >> described and clarity around xlang environments. But I'm +0 on whatever 
>> >> has momentum. I think the main downside is the weirdness around 
>> >> serializers/watermarkFn/etc on Read. I am not sure how much this will 
>> >> cause users problems. It would be very ambitious of them to produce a 
>> >> PCollection where they had different fns per element...
>> >>
>> >> Kenn
>> >>

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Robert Bradshaw]

OK, I'm +0 on this change. Using the PTransform as an element is
probably better than duplicating the full API on another interface,
and think it's worth getting this ublocked. This will require a Read2
if we have to add options in a upgrade-compatible way.

On Tue, Jul 7, 2020 at 3:19 PM Luke Cwik  wrote:
>
> Robert, you're correct in your understanding that the Read PTransform would 
> be encoded via the schema coder.
>
> Kenn, different serializers are ok as long as the output coder can 
> encode/decode the output type. Different watermark fns are also ok since it 
> is about computing the watermark for each individual source and won't impact 
> the watermark computed by other sources. Watermark advancement will still be 
> held back by the source that is furthest behind and still has the same 
> problems when a user chooses a watermark fn that was incompatible with the 
> windowing strategy for producing output (e.g. global window + default trigger 
> + streaming pipeline).
>
> Both are pretty close so if we started from scratch then it could go either 
> way but we aren't starting from scratch (I don't think a Beam 3.0 is likely 
> to happen in the next few years as there isn't enough stuff that we want to 
> remove vs the amount of stuff we would gain).
>
> On Tue, Jul 7, 2020 at 2:57 PM Kenneth Knowles  wrote:
>>
>> On Tue, Jul 7, 2020 at 2:24 PM Robert Bradshaw  wrote:
>>>
>>> On Tue, Jul 7, 2020 at 2:06 PM Luke Cwik  wrote:
>>> >
>>> > Robert, the intent is that the Read object would use a schema coder and 
>>> > for XLang purposes would be no different then a POJO.
>>>
>>> Just to clarify, you're saying that the Read PTransform would be
>>> encoded via the schema coder? That still feels a bit odd (and
>>> specificically if we were designing IO from scratch rather than
>>> adapting to what already exists would we choose to use PTransforms as
>>> elements?) but would solve the cross language issue.
>>
>>
>> I like this question. If we were designing from scratch, what would we do? 
>> Would we encourage users to feed Create.of(SourceDescriptor) into ReadAll? 
>> We would probably provide a friendly wrapper for reading one static thing, 
>> and call it Read. But it would probably have an API like 
>> Read.from(SourceDescriptor), thus eliminating duplicate documentation and 
>> boilerplate that Luke described while keeping the separation that Brian 
>> described and clarity around xlang environments. But I'm +0 on whatever has 
>> momentum. I think the main downside is the weirdness around 
>> serializers/watermarkFn/etc on Read. I am not sure how much this will cause 
>> users problems. It would be very ambitious of them to produce a 
>> PCollection where they had different fns per element...
>>
>> Kenn
>>
>>>
>>> > The issue of how to deal with closures applies to both equally and that 
>>> > is why I suggested to favor using data over closures. Once there is an 
>>> > implementation for how to deal with UDFs in an XLang world, this guidance 
>>> > can change.
>>> >
>>> > Kenn, I did mean specifying an enum that the XLang expansion service 
>>> > would return a serialized blob of code. The XLang expansion service is 
>>> > responsible for returning an environment that contains all the necessary 
>>> > dependencies to execute the transforms and the serialized blob of code 
>>> > and hence would be a non-issue for the caller.
>>> >
>>> > From reviewing the SDF Kafka PR, the reduction in maintenance is 
>>> > definitely there (100s of lines of duplicated boilerplate and 
>>> > documentation).
>>> >
>>> > What are the next steps to get a resolution on this?
>>> >
>>> > On Thu, Jul 2, 2020 at 10:38 AM Robert Bradshaw  
>>> > wrote:
>>> >>
>>> >> On Thu, Jul 2, 2020 at 10:26 AM Kenneth Knowles  wrote:
>>> >>>
>>> >>>
>>> >>> On Wed, Jul 1, 2020 at 4:17 PM Eugene Kirpichov  
>>> >>> wrote:
>>> 
>>>  Kenn - I don't mean an enum of common closures, I mean expressing 
>>>  closures in a restricted sub-language such as the language of SQL 
>>>  expressions.
>>> >>>
>>> >>>
>>> >>> My lack of clarity: enums was my phrasing of Luke's item 1). I 
>>> >>> understood what you meant. I think either a set of well-known closures 
>>> >>> or a tiny sublanguage could add value.
>>> >>>
>>> 
>>>  That would only work if there is a portable way to interpret SQL 
>>>  expressions, but if there isn't, maybe there should be - for the sake 
>>>  of, well, expressing closures portably. Of course these would be 
>>>  closures that only work with rows - but that seems powerful enough for 
>>>  many if not most purposes.
>>> >>>
>>> >>>
>>> >>> You can choose a SQL dialect or choose the tiniest subset just for this 
>>> >>> purpose and go with it. But when the data type going in or out of the 
>>> >>> lambda are e.g. some Java or Python object then what? One idea is to 
>>> >>> always require these to be rows. But if you can really get away with a 
>>> >>> dependency-free context-free 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Robert Bradshaw]

On Tue, Jul 7, 2020 at 2:06 PM Luke Cwik  wrote:
>
> Robert, the intent is that the Read object would use a schema coder and for 
> XLang purposes would be no different then a POJO.

Just to clarify, you're saying that the Read PTransform would be
encoded via the schema coder? That still feels a bit odd (and
specificically if we were designing IO from scratch rather than
adapting to what already exists would we choose to use PTransforms as
elements?) but would solve the cross language issue.

> The issue of how to deal with closures applies to both equally and that is 
> why I suggested to favor using data over closures. Once there is an 
> implementation for how to deal with UDFs in an XLang world, this guidance can 
> change.
>
> Kenn, I did mean specifying an enum that the XLang expansion service would 
> return a serialized blob of code. The XLang expansion service is responsible 
> for returning an environment that contains all the necessary dependencies to 
> execute the transforms and the serialized blob of code and hence would be a 
> non-issue for the caller.
>
> From reviewing the SDF Kafka PR, the reduction in maintenance is definitely 
> there (100s of lines of duplicated boilerplate and documentation).
>
> What are the next steps to get a resolution on this?
>
> On Thu, Jul 2, 2020 at 10:38 AM Robert Bradshaw  wrote:
>>
>> On Thu, Jul 2, 2020 at 10:26 AM Kenneth Knowles  wrote:
>>>
>>>
>>> On Wed, Jul 1, 2020 at 4:17 PM Eugene Kirpichov  
>>> wrote:

 Kenn - I don't mean an enum of common closures, I mean expressing closures 
 in a restricted sub-language such as the language of SQL expressions.
>>>
>>>
>>> My lack of clarity: enums was my phrasing of Luke's item 1). I understood 
>>> what you meant. I think either a set of well-known closures or a tiny 
>>> sublanguage could add value.
>>>

 That would only work if there is a portable way to interpret SQL 
 expressions, but if there isn't, maybe there should be - for the sake of, 
 well, expressing closures portably. Of course these would be closures that 
 only work with rows - but that seems powerful enough for many if not most 
 purposes.
>>>
>>>
>>> You can choose a SQL dialect or choose the tiniest subset just for this 
>>> purpose and go with it. But when the data type going in or out of the 
>>> lambda are e.g. some Java or Python object then what? One idea is to always 
>>> require these to be rows. But if you can really get away with a 
>>> dependency-free context-free lambda, then Javascript or Python is as doable 
>>> as SQL in terms of having a tiny restricted language for just this purpose. 
>>> I would expect once it got used, folks would start to ask to include the 
>>> rest of what the language has to offer - its ecosystem. This is always the 
>>> main design point I am interested in for "lightweight" embedded UDF 
>>> proposals.
>>
>>
>> This is getting off the topic of ReadAll, but I think being able to do 
>> arbitrary computation in preceding/succeeding transform plus a (quite) 
>> restricted language in the transform itself can go a long way. (For example, 
>> one could have a dynamic destinations write that takes a KV 
>> where dest is a format string like "foo-{{shard_num}}.txt" to plug in the 
>> truly dynamic pieces, but the dest string itself can be computed (e.g. based 
>> on the element) using arbitrary code in the caller language.)
>>
>>>
>>>
>>> Kenn
>>>

 For example, maybe the Java example:

  PCollection transactions = ...;
  transactions.apply(FileIO.writeDynamic()
  .by(Transaction::getType)
  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be 
 written to CSVSink
   type -> new CSVSink(type.getFieldNames()))
  .to(".../path/to/")
  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));

 could be written in Python as:

 transactions | fileio.write_dynamic(
   by="it.type",  # "it" is implicitly available in these SQL expressions 
 as the same thing as the Java lambda argument
   format="it.fields",
   sink="CSV_SINK(it.type.field_names)",  # A bunch of preset sinks 
 supported in every language?
   to=".../path/to/",
   naming="DEFAULT_NAMING(CONCAT(it, '-transactions'), '.csv')")

 Again, to be clear, I'm not suggesting to block what Ismael is proposing 
 on getting this done - getting this done wouldn't be a short term effort, 
 but seems potentially really nice.


 On Wed, Jul 1, 2020 at 3:19 PM Robert Burke  wrote:
>
> From the Go side of the table, the Go language doesn't provide a 
> mechanism to serialize or access closure data, which means DoFns can't be 
> functional closures.This combined with the move to have the "Structural 
> DoFns" be serialized using Beam Schemas, has the net result that if Go 
> transforms are used for Cross Language, they will be configurable with a 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Luke Cwik]

Robert, the intent is that the Read object would use a schema coder and for
XLang purposes would be no different then a POJO. The issue of how to deal
with closures applies to both equally and that is why I suggested to favor
using data over closures. Once there is an implementation for how to deal
with UDFs in an XLang world, this guidance can change.

Kenn, I did mean specifying an enum that the XLang expansion service would
return a serialized blob of code. The XLang expansion service is
responsible for returning an environment that contains all the necessary
dependencies to execute the transforms and the serialized blob of code and
hence would be a non-issue for the caller.

>From reviewing the SDF Kafka PR, the reduction in maintenance is definitely
there (100s of lines of duplicated boilerplate and documentation).

What are the next steps to get a resolution on this?

On Thu, Jul 2, 2020 at 10:38 AM Robert Bradshaw  wrote:

> On Thu, Jul 2, 2020 at 10:26 AM Kenneth Knowles  wrote:
>
>>
>> On Wed, Jul 1, 2020 at 4:17 PM Eugene Kirpichov 
>> wrote:
>>
>>> Kenn - I don't mean an enum of common closures, I mean expressing
>>> closures in a restricted sub-language such as the language of SQL
>>> expressions.
>>>
>>
>> My lack of clarity: enums was my phrasing of Luke's item 1). I understood
>> what you meant. I think either a set of well-known closures or a tiny
>> sublanguage could add value.
>>
>>
>>> That would only work if there is a portable way to interpret SQL
>>> expressions, but if there isn't, maybe there should be - for the sake of,
>>> well, expressing closures portably. Of course these would be closures that
>>> only work with rows - but that seems powerful enough for many if not most
>>> purposes.
>>>
>>
>> You can choose a SQL dialect or choose the tiniest subset just for this
>> purpose and go with it. But when the data type going in or out of the
>> lambda are e.g. some Java or Python object then what? One idea is to always
>> require these to be rows. But if you can really get away with a
>> dependency-free context-free lambda, then Javascript or Python is as doable
>> as SQL in terms of having a tiny restricted language for just this purpose.
>> I would expect once it got used, folks would start to ask to include the
>> rest of what the language has to offer - its ecosystem. This is always the
>> main design point I am interested in for "lightweight" embedded UDF
>> proposals.
>>
>
> This is getting off the topic of ReadAll, but I think being able to do
> arbitrary computation in preceding/succeeding transform plus a (quite)
> restricted language in the transform itself can go a long way. (For
> example, one could have a dynamic destinations write that takes a
> KV where dest is a format string like
> "foo-{{shard_num}}.txt" to plug in the truly dynamic pieces, but the dest
> string itself can be computed (e.g. based on the element) using arbitrary
> code in the caller language.)
>
>
>>
>> Kenn
>>
>>
>>> For example, maybe the Java example:
>>>
>>>  PCollection transactions = ...;
>>>  transactions.apply(FileIO.writeDynamic()
>>>  .by(Transaction::getType)
>>>  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
>>> written to CSVSink
>>>   type -> new CSVSink(type.getFieldNames()))
>>>  .to(".../path/to/")
>>>  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));
>>>
>>> could be written in Python as:
>>>
>>> transactions | fileio.write_dynamic(
>>>   by="it.type",  # "it" is implicitly available in these SQL expressions
>>> as the same thing as the Java lambda argument
>>>   format="it.fields",
>>>   sink="CSV_SINK(it.type.field_names)",  # A bunch of preset sinks
>>> supported in every language?
>>>   to=".../path/to/",
>>>   naming="DEFAULT_NAMING(CONCAT(it, '-transactions'), '.csv')")
>>>
>>> Again, to be clear, I'm not suggesting to block what Ismael is proposing
>>> on getting this done - getting this done wouldn't be a short term effort,
>>> but seems potentially really nice.
>>>
>>>
>>> On Wed, Jul 1, 2020 at 3:19 PM Robert Burke  wrote:
>>>
 From the Go side of the table, the Go language doesn't provide a
 mechanism to serialize or access closure data, which means DoFns can't be
 functional closures.This combined with the move to have the "Structural
 DoFns" be serialized using Beam Schemas, has the net result that if Go
 transforms are used for Cross Language, they will be configurable with a
 Schema of the configuration data.

 Of course, this just means that each language will probably provide
 whichever mechanisms it likes for use of it's cross language transforms.

 On Tue, 30 Jun 2020 at 16:07, Kenneth Knowles  wrote:

> I don't think an enum of most common closures will work. The input
> types are typically generics that are made concrete by the caller who also
> provides the closures. I think Luke's (2) is the same idea as my "Java
> still assembles it 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Robert Bradshaw]

On Thu, Jul 2, 2020 at 10:26 AM Kenneth Knowles  wrote:

>
> On Wed, Jul 1, 2020 at 4:17 PM Eugene Kirpichov 
> wrote:
>
>> Kenn - I don't mean an enum of common closures, I mean expressing
>> closures in a restricted sub-language such as the language of SQL
>> expressions.
>>
>
> My lack of clarity: enums was my phrasing of Luke's item 1). I understood
> what you meant. I think either a set of well-known closures or a tiny
> sublanguage could add value.
>
>
>> That would only work if there is a portable way to interpret SQL
>> expressions, but if there isn't, maybe there should be - for the sake of,
>> well, expressing closures portably. Of course these would be closures that
>> only work with rows - but that seems powerful enough for many if not most
>> purposes.
>>
>
> You can choose a SQL dialect or choose the tiniest subset just for this
> purpose and go with it. But when the data type going in or out of the
> lambda are e.g. some Java or Python object then what? One idea is to always
> require these to be rows. But if you can really get away with a
> dependency-free context-free lambda, then Javascript or Python is as doable
> as SQL in terms of having a tiny restricted language for just this purpose.
> I would expect once it got used, folks would start to ask to include the
> rest of what the language has to offer - its ecosystem. This is always the
> main design point I am interested in for "lightweight" embedded UDF
> proposals.
>

This is getting off the topic of ReadAll, but I think being able to do
arbitrary computation in preceding/succeeding transform plus a (quite)
restricted language in the transform itself can go a long way. (For
example, one could have a dynamic destinations write that takes a
KV where dest is a format string like
"foo-{{shard_num}}.txt" to plug in the truly dynamic pieces, but the dest
string itself can be computed (e.g. based on the element) using arbitrary
code in the caller language.)


>
> Kenn
>
>
>> For example, maybe the Java example:
>>
>>  PCollection transactions = ...;
>>  transactions.apply(FileIO.writeDynamic()
>>  .by(Transaction::getType)
>>  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
>> written to CSVSink
>>   type -> new CSVSink(type.getFieldNames()))
>>  .to(".../path/to/")
>>  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));
>>
>> could be written in Python as:
>>
>> transactions | fileio.write_dynamic(
>>   by="it.type",  # "it" is implicitly available in these SQL expressions
>> as the same thing as the Java lambda argument
>>   format="it.fields",
>>   sink="CSV_SINK(it.type.field_names)",  # A bunch of preset sinks
>> supported in every language?
>>   to=".../path/to/",
>>   naming="DEFAULT_NAMING(CONCAT(it, '-transactions'), '.csv')")
>>
>> Again, to be clear, I'm not suggesting to block what Ismael is proposing
>> on getting this done - getting this done wouldn't be a short term effort,
>> but seems potentially really nice.
>>
>>
>> On Wed, Jul 1, 2020 at 3:19 PM Robert Burke  wrote:
>>
>>> From the Go side of the table, the Go language doesn't provide a
>>> mechanism to serialize or access closure data, which means DoFns can't be
>>> functional closures.This combined with the move to have the "Structural
>>> DoFns" be serialized using Beam Schemas, has the net result that if Go
>>> transforms are used for Cross Language, they will be configurable with a
>>> Schema of the configuration data.
>>>
>>> Of course, this just means that each language will probably provide
>>> whichever mechanisms it likes for use of it's cross language transforms.
>>>
>>> On Tue, 30 Jun 2020 at 16:07, Kenneth Knowles  wrote:
>>>
 I don't think an enum of most common closures will work. The input
 types are typically generics that are made concrete by the caller who also
 provides the closures. I think Luke's (2) is the same idea as my "Java
 still assembles it [using opaque Python closures/transforms]". It seems
 like an approach to (3). Passing over actual code could address some cases,
 but libraries become the issue.

 I think it is fair to say that "WriteAll" style would involve entering
 unexplored territory.

 On the main topic, I think Brian has a pretty strong point and his
 example of type conversion lambdas is a good example. I did a quick survey
 and every other property I could find does seem like it fits on the Read,
 and most IOs have a few of these closures for example also extracting
 timestamps. So maybe just a resolution convention of putting them on the
 ReadAll and that taking precedence. Then you would be deserializing a Read
 transform with insta-crash methods or some such?

 Kenn

 On Tue, Jun 30, 2020 at 10:24 AM Eugene Kirpichov 
 wrote:

> Yeah, mainly I just feel like dynamic reads and dynamic writes (and
> perhaps not-yet-invented similar transforms of other kinds) are tightly

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Kenneth Knowles]

On Wed, Jul 1, 2020 at 4:17 PM Eugene Kirpichov 
wrote:

> Kenn - I don't mean an enum of common closures, I mean expressing closures
> in a restricted sub-language such as the language of SQL expressions.
>

My lack of clarity: enums was my phrasing of Luke's item 1). I understood
what you meant. I think either a set of well-known closures or a tiny
sublanguage could add value.


> That would only work if there is a portable way to interpret SQL
> expressions, but if there isn't, maybe there should be - for the sake of,
> well, expressing closures portably. Of course these would be closures that
> only work with rows - but that seems powerful enough for many if not most
> purposes.
>

You can choose a SQL dialect or choose the tiniest subset just for this
purpose and go with it. But when the data type going in or out of the
lambda are e.g. some Java or Python object then what? One idea is to always
require these to be rows. But if you can really get away with a
dependency-free context-free lambda, then Javascript or Python is as doable
as SQL in terms of having a tiny restricted language for just this purpose.
I would expect once it got used, folks would start to ask to include the
rest of what the language has to offer - its ecosystem. This is always the
main design point I am interested in for "lightweight" embedded UDF
proposals.

Kenn


> For example, maybe the Java example:
>
>  PCollection transactions = ...;
>  transactions.apply(FileIO.writeDynamic()
>  .by(Transaction::getType)
>  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
> written to CSVSink
>   type -> new CSVSink(type.getFieldNames()))
>  .to(".../path/to/")
>  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));
>
> could be written in Python as:
>
> transactions | fileio.write_dynamic(
>   by="it.type",  # "it" is implicitly available in these SQL expressions
> as the same thing as the Java lambda argument
>   format="it.fields",
>   sink="CSV_SINK(it.type.field_names)",  # A bunch of preset sinks
> supported in every language?
>   to=".../path/to/",
>   naming="DEFAULT_NAMING(CONCAT(it, '-transactions'), '.csv')")
>
> Again, to be clear, I'm not suggesting to block what Ismael is proposing
> on getting this done - getting this done wouldn't be a short term effort,
> but seems potentially really nice.
>
>
> On Wed, Jul 1, 2020 at 3:19 PM Robert Burke  wrote:
>
>> From the Go side of the table, the Go language doesn't provide a
>> mechanism to serialize or access closure data, which means DoFns can't be
>> functional closures.This combined with the move to have the "Structural
>> DoFns" be serialized using Beam Schemas, has the net result that if Go
>> transforms are used for Cross Language, they will be configurable with a
>> Schema of the configuration data.
>>
>> Of course, this just means that each language will probably provide
>> whichever mechanisms it likes for use of it's cross language transforms.
>>
>> On Tue, 30 Jun 2020 at 16:07, Kenneth Knowles  wrote:
>>
>>> I don't think an enum of most common closures will work. The input types
>>> are typically generics that are made concrete by the caller who also
>>> provides the closures. I think Luke's (2) is the same idea as my "Java
>>> still assembles it [using opaque Python closures/transforms]". It seems
>>> like an approach to (3). Passing over actual code could address some cases,
>>> but libraries become the issue.
>>>
>>> I think it is fair to say that "WriteAll" style would involve entering
>>> unexplored territory.
>>>
>>> On the main topic, I think Brian has a pretty strong point and his
>>> example of type conversion lambdas is a good example. I did a quick survey
>>> and every other property I could find does seem like it fits on the Read,
>>> and most IOs have a few of these closures for example also extracting
>>> timestamps. So maybe just a resolution convention of putting them on the
>>> ReadAll and that taking precedence. Then you would be deserializing a Read
>>> transform with insta-crash methods or some such?
>>>
>>> Kenn
>>>
>>> On Tue, Jun 30, 2020 at 10:24 AM Eugene Kirpichov 
>>> wrote:
>>>
 Yeah, mainly I just feel like dynamic reads and dynamic writes (and
 perhaps not-yet-invented similar transforms of other kinds) are tightly
 related - they are either very similar, or are duals of each other - so
 they should use the same approach. If they are using different approaches,
 it is a sign that either one of them is being done wrong or that we are
 running into a fundamental limitation of Beam (e.g. difficulty of encoding
 closures compared to encoding elements).

 But I agree with Luke that we shouldn't give up on closures. Especially
 with the work that has been done on schemas and SQL, I see no reason why we
 couldn't express closures in a portable restricted sub-language. If we can
 express SQL, we can express many or most use cases of dynamic 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Robert Bradshaw]

I, too, have a general preference for using a POJO (and cross-language)
compatible config object for ReadAll rather than having the Read elements
themselves as PCollection elements. It seem the motivation is that the Read
object already has all the builder methods (plus some other configuration
that may not make sense per-element), but if we're going for minimizing
redundancy I think it would be better to have a ReadAllFromKafka that
consumes PCollection and a ReadFromKafka that's parameterized
by a KafkaConfig than a ReadAllFromKafka that consumes a
PCollection. I think there are open questions as to how to
make a KafkaConfig that can be extended in a forward compatible way.

I also think, unless the conversion is trivial, that conveniences like a
TextIO.readAll() that consumes a PCollection of filenames as strings are
also very useful.

I do, however, see the motivation of a generic ReadAll that consumes a
PCollection. (Care needs to be taken here to think about
updates--SerializeableCoder could be used but special care needs to be
taken if the class ever gets updated...). Such transforms to not lend
themselves well to cross language without extra work on the Java side.


On Wed, Jul 1, 2020 at 4:17 PM Eugene Kirpichov 
wrote:

> Kenn - I don't mean an enum of common closures, I mean expressing closures
> in a restricted sub-language such as the language of SQL expressions. That
> would only work if there is a portable way to interpret SQL expressions,
> but if there isn't, maybe there should be - for the sake of, well,
> expressing closures portably. Of course these would be closures that only
> work with rows - but that seems powerful enough for many if not most
> purposes.
>
> For example, maybe the Java example:
>
>  PCollection transactions = ...;
>  transactions.apply(FileIO.writeDynamic()
>  .by(Transaction::getType)
>  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
> written to CSVSink
>   type -> new CSVSink(type.getFieldNames()))
>  .to(".../path/to/")
>  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));
>
> could be written in Python as:
>
> transactions | fileio.write_dynamic(
>   by="it.type",  # "it" is implicitly available in these SQL expressions
> as the same thing as the Java lambda argument
>   format="it.fields",
>   sink="CSV_SINK(it.type.field_names)",  # A bunch of preset sinks
> supported in every language?
>   to=".../path/to/",
>   naming="DEFAULT_NAMING(CONCAT(it, '-transactions'), '.csv')")
>
> Again, to be clear, I'm not suggesting to block what Ismael is proposing
> on getting this done - getting this done wouldn't be a short term effort,
> but seems potentially really nice.
>
>
> On Wed, Jul 1, 2020 at 3:19 PM Robert Burke  wrote:
>
>> From the Go side of the table, the Go language doesn't provide a
>> mechanism to serialize or access closure data, which means DoFns can't be
>> functional closures.This combined with the move to have the "Structural
>> DoFns" be serialized using Beam Schemas, has the net result that if Go
>> transforms are used for Cross Language, they will be configurable with a
>> Schema of the configuration data.
>>
>> Of course, this just means that each language will probably provide
>> whichever mechanisms it likes for use of it's cross language transforms.
>>
>> On Tue, 30 Jun 2020 at 16:07, Kenneth Knowles  wrote:
>>
>>> I don't think an enum of most common closures will work. The input types
>>> are typically generics that are made concrete by the caller who also
>>> provides the closures. I think Luke's (2) is the same idea as my "Java
>>> still assembles it [using opaque Python closures/transforms]". It seems
>>> like an approach to (3). Passing over actual code could address some cases,
>>> but libraries become the issue.
>>>
>>> I think it is fair to say that "WriteAll" style would involve entering
>>> unexplored territory.
>>>
>>> On the main topic, I think Brian has a pretty strong point and his
>>> example of type conversion lambdas is a good example. I did a quick survey
>>> and every other property I could find does seem like it fits on the Read,
>>> and most IOs have a few of these closures for example also extracting
>>> timestamps. So maybe just a resolution convention of putting them on the
>>> ReadAll and that taking precedence. Then you would be deserializing a Read
>>> transform with insta-crash methods or some such?
>>>
>>> Kenn
>>>
>>> On Tue, Jun 30, 2020 at 10:24 AM Eugene Kirpichov 
>>> wrote:
>>>
 Yeah, mainly I just feel like dynamic reads and dynamic writes (and
 perhaps not-yet-invented similar transforms of other kinds) are tightly
 related - they are either very similar, or are duals of each other - so
 they should use the same approach. If they are using different approaches,
 it is a sign that either one of them is being done wrong or that we are
 running into a fundamental limitation of Beam (e.g. difficulty of encoding
 closures 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Eugene Kirpichov]

Kenn - I don't mean an enum of common closures, I mean expressing closures
in a restricted sub-language such as the language of SQL expressions. That
would only work if there is a portable way to interpret SQL expressions,
but if there isn't, maybe there should be - for the sake of, well,
expressing closures portably. Of course these would be closures that only
work with rows - but that seems powerful enough for many if not most
purposes.

For example, maybe the Java example:

 PCollection transactions = ...;
 transactions.apply(FileIO.writeDynamic()
 .by(Transaction::getType)
 .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
written to CSVSink
  type -> new CSVSink(type.getFieldNames()))
 .to(".../path/to/")
 .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));

could be written in Python as:

transactions | fileio.write_dynamic(
  by="it.type",  # "it" is implicitly available in these SQL expressions as
the same thing as the Java lambda argument
  format="it.fields",
  sink="CSV_SINK(it.type.field_names)",  # A bunch of preset sinks
supported in every language?
  to=".../path/to/",
  naming="DEFAULT_NAMING(CONCAT(it, '-transactions'), '.csv')")

Again, to be clear, I'm not suggesting to block what Ismael is proposing on
getting this done - getting this done wouldn't be a short term effort, but
seems potentially really nice.


On Wed, Jul 1, 2020 at 3:19 PM Robert Burke  wrote:

> From the Go side of the table, the Go language doesn't provide a mechanism
> to serialize or access closure data, which means DoFns can't be functional
> closures.This combined with the move to have the "Structural DoFns" be
> serialized using Beam Schemas, has the net result that if Go transforms are
> used for Cross Language, they will be configurable with a Schema of the
> configuration data.
>
> Of course, this just means that each language will probably provide
> whichever mechanisms it likes for use of it's cross language transforms.
>
> On Tue, 30 Jun 2020 at 16:07, Kenneth Knowles  wrote:
>
>> I don't think an enum of most common closures will work. The input types
>> are typically generics that are made concrete by the caller who also
>> provides the closures. I think Luke's (2) is the same idea as my "Java
>> still assembles it [using opaque Python closures/transforms]". It seems
>> like an approach to (3). Passing over actual code could address some cases,
>> but libraries become the issue.
>>
>> I think it is fair to say that "WriteAll" style would involve entering
>> unexplored territory.
>>
>> On the main topic, I think Brian has a pretty strong point and his
>> example of type conversion lambdas is a good example. I did a quick survey
>> and every other property I could find does seem like it fits on the Read,
>> and most IOs have a few of these closures for example also extracting
>> timestamps. So maybe just a resolution convention of putting them on the
>> ReadAll and that taking precedence. Then you would be deserializing a Read
>> transform with insta-crash methods or some such?
>>
>> Kenn
>>
>> On Tue, Jun 30, 2020 at 10:24 AM Eugene Kirpichov 
>> wrote:
>>
>>> Yeah, mainly I just feel like dynamic reads and dynamic writes (and
>>> perhaps not-yet-invented similar transforms of other kinds) are tightly
>>> related - they are either very similar, or are duals of each other - so
>>> they should use the same approach. If they are using different approaches,
>>> it is a sign that either one of them is being done wrong or that we are
>>> running into a fundamental limitation of Beam (e.g. difficulty of encoding
>>> closures compared to encoding elements).
>>>
>>> But I agree with Luke that we shouldn't give up on closures. Especially
>>> with the work that has been done on schemas and SQL, I see no reason why we
>>> couldn't express closures in a portable restricted sub-language. If we can
>>> express SQL, we can express many or most use cases of dynamic reads/writes
>>> - I don't mean that we should actually use SQL (though we *could* -
>>> e.g. SQL scalar expressions seem powerful enough to express the closures
>>> appearing in most use cases of FileIO.writeDynamic), I just mean that SQL
>>> is an existence proof.
>>>
>>> (I don't want to rock the boat too much, just thought I'd chime in as
>>> this topic is dear to my heart)
>>>
>>> On Tue, Jun 30, 2020 at 9:59 AM Luke Cwik  wrote:
>>>
 Kenn, I'm not too worried about closures since:
 1) the expansion service for a transform could have a well set of
 defined closures by name that are returned as serialized objects that don't
 need to be interpretable by the caller
 2) the language could store serialized functions of another language as
 constants
 3) generic XLang function support will eventually be needed
 but I do agree that closures do make things difficult to express vs
 data which is why primarily why we should prefer data over closures when
 possible and use 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Robert Burke]

>From the Go side of the table, the Go language doesn't provide a mechanism
to serialize or access closure data, which means DoFns can't be functional
closures.This combined with the move to have the "Structural DoFns" be
serialized using Beam Schemas, has the net result that if Go transforms are
used for Cross Language, they will be configurable with a Schema of the
configuration data.

Of course, this just means that each language will probably provide
whichever mechanisms it likes for use of it's cross language transforms.

On Tue, 30 Jun 2020 at 16:07, Kenneth Knowles  wrote:

> I don't think an enum of most common closures will work. The input types
> are typically generics that are made concrete by the caller who also
> provides the closures. I think Luke's (2) is the same idea as my "Java
> still assembles it [using opaque Python closures/transforms]". It seems
> like an approach to (3). Passing over actual code could address some cases,
> but libraries become the issue.
>
> I think it is fair to say that "WriteAll" style would involve entering
> unexplored territory.
>
> On the main topic, I think Brian has a pretty strong point and his example
> of type conversion lambdas is a good example. I did a quick survey and
> every other property I could find does seem like it fits on the Read, and
> most IOs have a few of these closures for example also extracting
> timestamps. So maybe just a resolution convention of putting them on the
> ReadAll and that taking precedence. Then you would be deserializing a Read
> transform with insta-crash methods or some such?
>
> Kenn
>
> On Tue, Jun 30, 2020 at 10:24 AM Eugene Kirpichov 
> wrote:
>
>> Yeah, mainly I just feel like dynamic reads and dynamic writes (and
>> perhaps not-yet-invented similar transforms of other kinds) are tightly
>> related - they are either very similar, or are duals of each other - so
>> they should use the same approach. If they are using different approaches,
>> it is a sign that either one of them is being done wrong or that we are
>> running into a fundamental limitation of Beam (e.g. difficulty of encoding
>> closures compared to encoding elements).
>>
>> But I agree with Luke that we shouldn't give up on closures. Especially
>> with the work that has been done on schemas and SQL, I see no reason why we
>> couldn't express closures in a portable restricted sub-language. If we can
>> express SQL, we can express many or most use cases of dynamic reads/writes
>> - I don't mean that we should actually use SQL (though we *could* - e.g.
>> SQL scalar expressions seem powerful enough to express the closures
>> appearing in most use cases of FileIO.writeDynamic), I just mean that SQL
>> is an existence proof.
>>
>> (I don't want to rock the boat too much, just thought I'd chime in as
>> this topic is dear to my heart)
>>
>> On Tue, Jun 30, 2020 at 9:59 AM Luke Cwik  wrote:
>>
>>> Kenn, I'm not too worried about closures since:
>>> 1) the expansion service for a transform could have a well set of
>>> defined closures by name that are returned as serialized objects that don't
>>> need to be interpretable by the caller
>>> 2) the language could store serialized functions of another language as
>>> constants
>>> 3) generic XLang function support will eventually be needed
>>> but I do agree that closures do make things difficult to express vs data
>>> which is why primarily why we should prefer data over closures when
>>> possible and use closures when expressing it with data would be too
>>> cumbersome.
>>>
>>> Brian, so far the cases that have been migrated have shown that the
>>> source descriptor and the Read transform are almost the same (some
>>> parameters that only impact pipeline construction such as coders differ).
>>>
>>> On Mon, Jun 29, 2020 at 2:33 PM Brian Hulette 
>>> wrote:
>>>
 Sorry for jumping into this late and casting a vote against the
 consensus... but I think I'd prefer standardizing on a pattern like
 PCollection rather than PCollection. That
 approach clearly separates the parameters that are allowed to vary across a
 ReadAll (the ones defined in KafkaSourceDescriptor) from the parameters
 that should be constant (other parameters in the Read object, like
 SerializedFunctions for type conversions, parameters for different
 operating modes, etc...). I think it's helpful to think of the parameters
 that are allowed to vary as some "location descriptor", but I imagine IO
 authors may want other parameters to vary across a ReadAll as well.

 To me it seems safer to let an IO author "opt-in" to a parameter being
 dynamic at execution time.

 Brian

 On Mon, Jun 29, 2020 at 9:26 AM Eugene Kirpichov 
 wrote:

> I'd like to raise one more time the question of consistency between
> dynamic reads and dynamic writes, per my email at the beginning of the
> thread.
> If the community prefers ReadAll to read from Read, then should
> 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Kenneth Knowles]

I don't think an enum of most common closures will work. The input types
are typically generics that are made concrete by the caller who also
provides the closures. I think Luke's (2) is the same idea as my "Java
still assembles it [using opaque Python closures/transforms]". It seems
like an approach to (3). Passing over actual code could address some cases,
but libraries become the issue.

I think it is fair to say that "WriteAll" style would involve entering
unexplored territory.

On the main topic, I think Brian has a pretty strong point and his example
of type conversion lambdas is a good example. I did a quick survey and
every other property I could find does seem like it fits on the Read, and
most IOs have a few of these closures for example also extracting
timestamps. So maybe just a resolution convention of putting them on the
ReadAll and that taking precedence. Then you would be deserializing a Read
transform with insta-crash methods or some such?

Kenn

On Tue, Jun 30, 2020 at 10:24 AM Eugene Kirpichov 
wrote:

> Yeah, mainly I just feel like dynamic reads and dynamic writes (and
> perhaps not-yet-invented similar transforms of other kinds) are tightly
> related - they are either very similar, or are duals of each other - so
> they should use the same approach. If they are using different approaches,
> it is a sign that either one of them is being done wrong or that we are
> running into a fundamental limitation of Beam (e.g. difficulty of encoding
> closures compared to encoding elements).
>
> But I agree with Luke that we shouldn't give up on closures. Especially
> with the work that has been done on schemas and SQL, I see no reason why we
> couldn't express closures in a portable restricted sub-language. If we can
> express SQL, we can express many or most use cases of dynamic reads/writes
> - I don't mean that we should actually use SQL (though we *could* - e.g.
> SQL scalar expressions seem powerful enough to express the closures
> appearing in most use cases of FileIO.writeDynamic), I just mean that SQL
> is an existence proof.
>
> (I don't want to rock the boat too much, just thought I'd chime in as this
> topic is dear to my heart)
>
> On Tue, Jun 30, 2020 at 9:59 AM Luke Cwik  wrote:
>
>> Kenn, I'm not too worried about closures since:
>> 1) the expansion service for a transform could have a well set of defined
>> closures by name that are returned as serialized objects that don't need to
>> be interpretable by the caller
>> 2) the language could store serialized functions of another language as
>> constants
>> 3) generic XLang function support will eventually be needed
>> but I do agree that closures do make things difficult to express vs data
>> which is why primarily why we should prefer data over closures when
>> possible and use closures when expressing it with data would be too
>> cumbersome.
>>
>> Brian, so far the cases that have been migrated have shown that the
>> source descriptor and the Read transform are almost the same (some
>> parameters that only impact pipeline construction such as coders differ).
>>
>> On Mon, Jun 29, 2020 at 2:33 PM Brian Hulette 
>> wrote:
>>
>>> Sorry for jumping into this late and casting a vote against the
>>> consensus... but I think I'd prefer standardizing on a pattern like
>>> PCollection rather than PCollection. That
>>> approach clearly separates the parameters that are allowed to vary across a
>>> ReadAll (the ones defined in KafkaSourceDescriptor) from the parameters
>>> that should be constant (other parameters in the Read object, like
>>> SerializedFunctions for type conversions, parameters for different
>>> operating modes, etc...). I think it's helpful to think of the parameters
>>> that are allowed to vary as some "location descriptor", but I imagine IO
>>> authors may want other parameters to vary across a ReadAll as well.
>>>
>>> To me it seems safer to let an IO author "opt-in" to a parameter being
>>> dynamic at execution time.
>>>
>>> Brian
>>>
>>> On Mon, Jun 29, 2020 at 9:26 AM Eugene Kirpichov 
>>> wrote:
>>>
 I'd like to raise one more time the question of consistency between
 dynamic reads and dynamic writes, per my email at the beginning of the
 thread.
 If the community prefers ReadAll to read from Read, then should
 dynamicWrite's write to Write?

 On Mon, Jun 29, 2020 at 8:57 AM Boyuan Zhang 
 wrote:

> It seems like most of us agree on the idea that ReadAll should read
> from Read. I'm going to update the Kafka ReadAll with the same pattern.
> Thanks for all your help!
>
> On Fri, Jun 26, 2020 at 12:12 PM Chamikara Jayalath <
> chamik...@google.com> wrote:
>
>>
>>
>> On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:
>>
>>> I would also like to suggest that transforms that implement ReadAll
>>> via Read should also provide methods like:
>>>
>>> // Uses the specified values if unspecified in the input element
>>> from the 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Eugene Kirpichov]

Yeah, mainly I just feel like dynamic reads and dynamic writes (and perhaps
not-yet-invented similar transforms of other kinds) are tightly related -
they are either very similar, or are duals of each other - so they should
use the same approach. If they are using different approaches, it is a sign
that either one of them is being done wrong or that we are running into a
fundamental limitation of Beam (e.g. difficulty of encoding closures
compared to encoding elements).

But I agree with Luke that we shouldn't give up on closures. Especially
with the work that has been done on schemas and SQL, I see no reason why we
couldn't express closures in a portable restricted sub-language. If we can
express SQL, we can express many or most use cases of dynamic reads/writes
- I don't mean that we should actually use SQL (though we *could* - e.g.
SQL scalar expressions seem powerful enough to express the closures
appearing in most use cases of FileIO.writeDynamic), I just mean that SQL
is an existence proof.

(I don't want to rock the boat too much, just thought I'd chime in as this
topic is dear to my heart)

On Tue, Jun 30, 2020 at 9:59 AM Luke Cwik  wrote:

> Kenn, I'm not too worried about closures since:
> 1) the expansion service for a transform could have a well set of defined
> closures by name that are returned as serialized objects that don't need to
> be interpretable by the caller
> 2) the language could store serialized functions of another language as
> constants
> 3) generic XLang function support will eventually be needed
> but I do agree that closures do make things difficult to express vs data
> which is why primarily why we should prefer data over closures when
> possible and use closures when expressing it with data would be too
> cumbersome.
>
> Brian, so far the cases that have been migrated have shown that the source
> descriptor and the Read transform are almost the same (some parameters that
> only impact pipeline construction such as coders differ).
>
> On Mon, Jun 29, 2020 at 2:33 PM Brian Hulette  wrote:
>
>> Sorry for jumping into this late and casting a vote against the
>> consensus... but I think I'd prefer standardizing on a pattern like
>> PCollection rather than PCollection. That
>> approach clearly separates the parameters that are allowed to vary across a
>> ReadAll (the ones defined in KafkaSourceDescriptor) from the parameters
>> that should be constant (other parameters in the Read object, like
>> SerializedFunctions for type conversions, parameters for different
>> operating modes, etc...). I think it's helpful to think of the parameters
>> that are allowed to vary as some "location descriptor", but I imagine IO
>> authors may want other parameters to vary across a ReadAll as well.
>>
>> To me it seems safer to let an IO author "opt-in" to a parameter being
>> dynamic at execution time.
>>
>> Brian
>>
>> On Mon, Jun 29, 2020 at 9:26 AM Eugene Kirpichov 
>> wrote:
>>
>>> I'd like to raise one more time the question of consistency between
>>> dynamic reads and dynamic writes, per my email at the beginning of the
>>> thread.
>>> If the community prefers ReadAll to read from Read, then should
>>> dynamicWrite's write to Write?
>>>
>>> On Mon, Jun 29, 2020 at 8:57 AM Boyuan Zhang  wrote:
>>>
 It seems like most of us agree on the idea that ReadAll should read
 from Read. I'm going to update the Kafka ReadAll with the same pattern.
 Thanks for all your help!

 On Fri, Jun 26, 2020 at 12:12 PM Chamikara Jayalath <
 chamik...@google.com> wrote:

>
>
> On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:
>
>> I would also like to suggest that transforms that implement ReadAll
>> via Read should also provide methods like:
>>
>> // Uses the specified values if unspecified in the input element from
>> the PCollection.
>> withDefaults(Read read);
>> // Uses the specified values regardless of what the input element
>> from the PCollection specifies.
>> withOverrides(Read read);
>>
>> and only adds methods that are required at construction time (e.g.
>> coders). This way the majority of documentation sits on the Read 
>> transform.
>>
>
> +0 from me. Sounds like benefits outweigh the drawbacks here and some
> of the drawbacks related to cross-language can be overcome through future
> advancements.
> Thanks for bringing this up Ismaël.
>
> - Cham
>
>
>>
>> On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:
>>
>>> Ismael, it is good to hear that using Read as the input didn't have
>>> a bunch of parameters that were being skipped/ignored. Also, for the
>>> polymorphism issue you have to rely on the user correctly telling you 
>>> the
>>> type in such a way where it is a common ancestor of all the runtime 
>>> types
>>> that will ever be used. This usually boils down to something like
>>> Serializable or DynamicMessage 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Luke Cwik]

Kenn, I'm not too worried about closures since:
1) the expansion service for a transform could have a well set of defined
closures by name that are returned as serialized objects that don't need to
be interpretable by the caller
2) the language could store serialized functions of another language as
constants
3) generic XLang function support will eventually be needed
but I do agree that closures do make things difficult to express vs data
which is why primarily why we should prefer data over closures when
possible and use closures when expressing it with data would be too
cumbersome.

Brian, so far the cases that have been migrated have shown that the source
descriptor and the Read transform are almost the same (some parameters that
only impact pipeline construction such as coders differ).

On Mon, Jun 29, 2020 at 2:33 PM Brian Hulette  wrote:

> Sorry for jumping into this late and casting a vote against the
> consensus... but I think I'd prefer standardizing on a pattern like
> PCollection rather than PCollection. That
> approach clearly separates the parameters that are allowed to vary across a
> ReadAll (the ones defined in KafkaSourceDescriptor) from the parameters
> that should be constant (other parameters in the Read object, like
> SerializedFunctions for type conversions, parameters for different
> operating modes, etc...). I think it's helpful to think of the parameters
> that are allowed to vary as some "location descriptor", but I imagine IO
> authors may want other parameters to vary across a ReadAll as well.
>
> To me it seems safer to let an IO author "opt-in" to a parameter being
> dynamic at execution time.
>
> Brian
>
> On Mon, Jun 29, 2020 at 9:26 AM Eugene Kirpichov 
> wrote:
>
>> I'd like to raise one more time the question of consistency between
>> dynamic reads and dynamic writes, per my email at the beginning of the
>> thread.
>> If the community prefers ReadAll to read from Read, then should
>> dynamicWrite's write to Write?
>>
>> On Mon, Jun 29, 2020 at 8:57 AM Boyuan Zhang  wrote:
>>
>>> It seems like most of us agree on the idea that ReadAll should read from
>>> Read. I'm going to update the Kafka ReadAll with the same pattern.
>>> Thanks for all your help!
>>>
>>> On Fri, Jun 26, 2020 at 12:12 PM Chamikara Jayalath <
>>> chamik...@google.com> wrote:
>>>


 On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:

> I would also like to suggest that transforms that implement ReadAll
> via Read should also provide methods like:
>
> // Uses the specified values if unspecified in the input element from
> the PCollection.
> withDefaults(Read read);
> // Uses the specified values regardless of what the input element from
> the PCollection specifies.
> withOverrides(Read read);
>
> and only adds methods that are required at construction time (e.g.
> coders). This way the majority of documentation sits on the Read 
> transform.
>

 +0 from me. Sounds like benefits outweigh the drawbacks here and some
 of the drawbacks related to cross-language can be overcome through future
 advancements.
 Thanks for bringing this up Ismaël.

 - Cham


>
> On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:
>
>> Ismael, it is good to hear that using Read as the input didn't have a
>> bunch of parameters that were being skipped/ignored. Also, for the
>> polymorphism issue you have to rely on the user correctly telling you the
>> type in such a way where it is a common ancestor of all the runtime types
>> that will ever be used. This usually boils down to something like
>> Serializable or DynamicMessage such that the coder that is chosen works 
>> for
>> all the runtime types. Using multiple types is a valid use case and would
>> allow for a simpler graph with less flattens merging the output from
>> multiple sources.
>>
>> Boyuan, as you have mentioned we can have a coder for KafkaIO.Read
>> which uses schemas even if some of the parameters can't be represented 
>> in a
>> meaningful way beyond "bytes". This would be helpful for cross language 
>> as
>> well since every parameter would become available if a language could
>> support it (e.g. it could serialize a java function up front and keep it
>> saved as raw bytes within said language). Even if we figure out a better
>> way to do this in the future, we'll have to change the schema for the new
>> way anyway. This would mean that the external version of the transform
>> adopts Row to Read and we drop KafkaSourceDescriptor. The conversion from
>> Row to Read could validate that the parameters make sense (e.g. the bytes
>> are valid serialized functions). The addition of an
>> endReadTime/endReadOffset would make sense for KafkaIO.Read as well and
>> this would enable having a bounded version that could be used for 
>> backfills
>> 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Brian Hulette]

Sorry for jumping into this late and casting a vote against the
consensus... but I think I'd prefer standardizing on a pattern like
PCollection rather than PCollection. That
approach clearly separates the parameters that are allowed to vary across a
ReadAll (the ones defined in KafkaSourceDescriptor) from the parameters
that should be constant (other parameters in the Read object, like
SerializedFunctions for type conversions, parameters for different
operating modes, etc...). I think it's helpful to think of the parameters
that are allowed to vary as some "location descriptor", but I imagine IO
authors may want other parameters to vary across a ReadAll as well.

To me it seems safer to let an IO author "opt-in" to a parameter being
dynamic at execution time.

Brian

On Mon, Jun 29, 2020 at 9:26 AM Eugene Kirpichov 
wrote:

> I'd like to raise one more time the question of consistency between
> dynamic reads and dynamic writes, per my email at the beginning of the
> thread.
> If the community prefers ReadAll to read from Read, then should
> dynamicWrite's write to Write?
>
> On Mon, Jun 29, 2020 at 8:57 AM Boyuan Zhang  wrote:
>
>> It seems like most of us agree on the idea that ReadAll should read from
>> Read. I'm going to update the Kafka ReadAll with the same pattern.
>> Thanks for all your help!
>>
>> On Fri, Jun 26, 2020 at 12:12 PM Chamikara Jayalath 
>> wrote:
>>
>>>
>>>
>>> On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:
>>>
 I would also like to suggest that transforms that implement ReadAll via
 Read should also provide methods like:

 // Uses the specified values if unspecified in the input element from
 the PCollection.
 withDefaults(Read read);
 // Uses the specified values regardless of what the input element from
 the PCollection specifies.
 withOverrides(Read read);

 and only adds methods that are required at construction time (e.g.
 coders). This way the majority of documentation sits on the Read transform.

>>>
>>> +0 from me. Sounds like benefits outweigh the drawbacks here and some of
>>> the drawbacks related to cross-language can be overcome through future
>>> advancements.
>>> Thanks for bringing this up Ismaël.
>>>
>>> - Cham
>>>
>>>

 On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:

> Ismael, it is good to hear that using Read as the input didn't have a
> bunch of parameters that were being skipped/ignored. Also, for the
> polymorphism issue you have to rely on the user correctly telling you the
> type in such a way where it is a common ancestor of all the runtime types
> that will ever be used. This usually boils down to something like
> Serializable or DynamicMessage such that the coder that is chosen works 
> for
> all the runtime types. Using multiple types is a valid use case and would
> allow for a simpler graph with less flattens merging the output from
> multiple sources.
>
> Boyuan, as you have mentioned we can have a coder for KafkaIO.Read
> which uses schemas even if some of the parameters can't be represented in 
> a
> meaningful way beyond "bytes". This would be helpful for cross language as
> well since every parameter would become available if a language could
> support it (e.g. it could serialize a java function up front and keep it
> saved as raw bytes within said language). Even if we figure out a better
> way to do this in the future, we'll have to change the schema for the new
> way anyway. This would mean that the external version of the transform
> adopts Row to Read and we drop KafkaSourceDescriptor. The conversion from
> Row to Read could validate that the parameters make sense (e.g. the bytes
> are valid serialized functions). The addition of an
> endReadTime/endReadOffset would make sense for KafkaIO.Read as well and
> this would enable having a bounded version that could be used for 
> backfills
> (this doesn't have to be done as part of any current ongoing PR).
> Essentially any parameter that could be added for a single instance of a
> Kafka element+restriction would also make sense to the KafkaIO.Read
> transform since it too is a single instance. There are parameters that
> would apply to the ReadAll that wouldn't apply to a read and these would 
> be
> global parameters across all element+restriction pairs such as config
> overrides or default values.
>
> I am convinced that we should do as Ismael is suggesting and use
> KafkaIO.Read as the type.
>
>
> On Thu, Jun 25, 2020 at 6:00 PM Chamikara Jayalath <
> chamik...@google.com> wrote:
>
>> Discussion regarding cross-language transforms is a slight tangent
>> here. But I think, in general, it's great if we can use existing 
>> transforms
>> (for example, IO connectors) as cross-language transforms without having 
>> to
>> build more 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Kenneth Knowles]

Eugene, let me see if I understand correctly. Your initial email suggested
we consider adopting the "dynamic write" style for ReadAll transforms.
Supposing Read had three fields x, y, and z, and you have a
PCollection with all the info you need.

(Ismaël's) "Read" way: Use a PTransform to transform each Bar into a
Read.withX(...).withY(...).withZ(...) and pass that result to ReadAll.
(Eugene's) "dynamic write" way: Pass the PCollection of Bar into
ReadAll.withX(input -> compute x).withY(input -> compute y).withZ(input ->
compute z)

Is that right? Ismaël's way has the benefit that the logic from Bar to Read
can be written in any language easily, so there is no issue passing
closures from Python to Java, etc. IIUC the Read could serde using a schema
for its config, so that "Read" and "ReadConfig" are synonymous and rows
that can be easily passed cross-language and even support pipeline update
and evolution in the event they get stored in state.

This latest email of yours seems to take into account preference for the
"Read" way and suggest the reverse of your first: make things consistent by
making dynamic writes look more like ReadAll. So assuming Write has also x,
y, and z. BTW I think the parameterization of FileIO by TransactionType and
Transaction is actually more about it FileIO's genericity.

The goal of being able to use a row-with-schema as a configuration object
that automatically shares everything with the vanilla Write makes sense to
me, and avoiding cross-language closure issues.

"dynamic write" way: Use a PTransform to transform PCollection into
PCollection> (where Dest and ElemType are concrete) and
feed this into Write.withDynamicDestinations() that has .withX(dest -> x)
but also some of .withY(...) and .withZ(...) maybe are not parameterized.
Mixes "data" and closures in a way that might be funky to separate cleanly
for xlang. Others have thought this through more than I have, I'm sure.

"WriteAll" way: Not sure how exactly this would look. The Dest serves both
to partition and configure. But the full Write is more about configure, not
partition. I think there is an impedance mismatch between high
Read-to-element ratio versus high element-to-Dest ratio. You would probably
not want to be able to map two Bar objects to the same Dest with different
Write configurations. Maybe something like: Use a PTransform to transform
PCollection into PCollection> for partitioning and
then MapKeys to expand Dest -> Write. I don't think this improves the
cross-language closure issue. What you want is for Java to own the expand()
method but be able to insert transforms provided by Python as a prefix of
it. Java still assembles it (mapping Bar to Dest and separately mapping
Dest to Write) so that Python cannot mess up, but without incurring
additional language crossings or passing repeated configuration over grpc.

Kenn

On Mon, Jun 29, 2020 at 9:26 AM Eugene Kirpichov 
wrote:

> I'd like to raise one more time the question of consistency between
> dynamic reads and dynamic writes, per my email at the beginning of the
> thread.
> If the community prefers ReadAll to read from Read, then should
> dynamicWrite's write to Write?
>
> On Mon, Jun 29, 2020 at 8:57 AM Boyuan Zhang  wrote:
>
>> It seems like most of us agree on the idea that ReadAll should read from
>> Read. I'm going to update the Kafka ReadAll with the same pattern.
>> Thanks for all your help!
>>
>> On Fri, Jun 26, 2020 at 12:12 PM Chamikara Jayalath 
>> wrote:
>>
>>>
>>>
>>> On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:
>>>
 I would also like to suggest that transforms that implement ReadAll via
 Read should also provide methods like:

 // Uses the specified values if unspecified in the input element from
 the PCollection.
 withDefaults(Read read);
 // Uses the specified values regardless of what the input element from
 the PCollection specifies.
 withOverrides(Read read);

 and only adds methods that are required at construction time (e.g.
 coders). This way the majority of documentation sits on the Read transform.

>>>
>>> +0 from me. Sounds like benefits outweigh the drawbacks here and some of
>>> the drawbacks related to cross-language can be overcome through future
>>> advancements.
>>> Thanks for bringing this up Ismaël.
>>>
>>> - Cham
>>>
>>>

 On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:

> Ismael, it is good to hear that using Read as the input didn't have a
> bunch of parameters that were being skipped/ignored. Also, for the
> polymorphism issue you have to rely on the user correctly telling you the
> type in such a way where it is a common ancestor of all the runtime types
> that will ever be used. This usually boils down to something like
> Serializable or DynamicMessage such that the coder that is chosen works 
> for
> all the runtime types. Using multiple types is a valid use case and would
> allow for a simpler graph with 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Eugene Kirpichov]

I'd like to raise one more time the question of consistency between dynamic
reads and dynamic writes, per my email at the beginning of the thread.
If the community prefers ReadAll to read from Read, then should
dynamicWrite's write to Write?

On Mon, Jun 29, 2020 at 8:57 AM Boyuan Zhang  wrote:

> It seems like most of us agree on the idea that ReadAll should read from
> Read. I'm going to update the Kafka ReadAll with the same pattern.
> Thanks for all your help!
>
> On Fri, Jun 26, 2020 at 12:12 PM Chamikara Jayalath 
> wrote:
>
>>
>>
>> On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:
>>
>>> I would also like to suggest that transforms that implement ReadAll via
>>> Read should also provide methods like:
>>>
>>> // Uses the specified values if unspecified in the input element from
>>> the PCollection.
>>> withDefaults(Read read);
>>> // Uses the specified values regardless of what the input element from
>>> the PCollection specifies.
>>> withOverrides(Read read);
>>>
>>> and only adds methods that are required at construction time (e.g.
>>> coders). This way the majority of documentation sits on the Read transform.
>>>
>>
>> +0 from me. Sounds like benefits outweigh the drawbacks here and some of
>> the drawbacks related to cross-language can be overcome through future
>> advancements.
>> Thanks for bringing this up Ismaël.
>>
>> - Cham
>>
>>
>>>
>>> On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:
>>>
 Ismael, it is good to hear that using Read as the input didn't have a
 bunch of parameters that were being skipped/ignored. Also, for the
 polymorphism issue you have to rely on the user correctly telling you the
 type in such a way where it is a common ancestor of all the runtime types
 that will ever be used. This usually boils down to something like
 Serializable or DynamicMessage such that the coder that is chosen works for
 all the runtime types. Using multiple types is a valid use case and would
 allow for a simpler graph with less flattens merging the output from
 multiple sources.

 Boyuan, as you have mentioned we can have a coder for KafkaIO.Read
 which uses schemas even if some of the parameters can't be represented in a
 meaningful way beyond "bytes". This would be helpful for cross language as
 well since every parameter would become available if a language could
 support it (e.g. it could serialize a java function up front and keep it
 saved as raw bytes within said language). Even if we figure out a better
 way to do this in the future, we'll have to change the schema for the new
 way anyway. This would mean that the external version of the transform
 adopts Row to Read and we drop KafkaSourceDescriptor. The conversion from
 Row to Read could validate that the parameters make sense (e.g. the bytes
 are valid serialized functions). The addition of an
 endReadTime/endReadOffset would make sense for KafkaIO.Read as well and
 this would enable having a bounded version that could be used for backfills
 (this doesn't have to be done as part of any current ongoing PR).
 Essentially any parameter that could be added for a single instance of a
 Kafka element+restriction would also make sense to the KafkaIO.Read
 transform since it too is a single instance. There are parameters that
 would apply to the ReadAll that wouldn't apply to a read and these would be
 global parameters across all element+restriction pairs such as config
 overrides or default values.

 I am convinced that we should do as Ismael is suggesting and use
 KafkaIO.Read as the type.


 On Thu, Jun 25, 2020 at 6:00 PM Chamikara Jayalath <
 chamik...@google.com> wrote:

> Discussion regarding cross-language transforms is a slight tangent
> here. But I think, in general, it's great if we can use existing 
> transforms
> (for example, IO connectors) as cross-language transforms without having 
> to
> build more composites (irrespective of whether in 
> ExternalTransformBuilders
> or a user pipelines) just to make them cross-language compatible. A future
> cross-language compatible SchemaCoder might help (assuming that works for
> Read transform) but I'm not sure we have a good idea when we'll get to 
> that
> state.
>
> Thanks,
> Cham
>
> On Thu, Jun 25, 2020 at 3:13 PM Boyuan Zhang 
> wrote:
>
>> For unbounded SDF in Kafka, we also consider the
>> upgrading/downgrading compatibility in the pipeline update scenario(For
>> detailed discussion, please refer to
>> https://lists.apache.org/thread.html/raf073b8741317244339eb5b2bce844c0f9e0d700c3e4de392fc648d6%40%3Cdev.beam.apache.org%3E).
>> In order to obtain the compatibility, it requires the input of the read 
>> SDF
>> is schema-aware.
>>
>> Thus the major constraint of mapping KafkaSourceDescriptor to
>> PCollection is, 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Boyuan Zhang]

It seems like most of us agree on the idea that ReadAll should read from
Read. I'm going to update the Kafka ReadAll with the same pattern.
Thanks for all your help!

On Fri, Jun 26, 2020 at 12:12 PM Chamikara Jayalath 
wrote:

>
>
> On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:
>
>> I would also like to suggest that transforms that implement ReadAll via
>> Read should also provide methods like:
>>
>> // Uses the specified values if unspecified in the input element from the
>> PCollection.
>> withDefaults(Read read);
>> // Uses the specified values regardless of what the input element from
>> the PCollection specifies.
>> withOverrides(Read read);
>>
>> and only adds methods that are required at construction time (e.g.
>> coders). This way the majority of documentation sits on the Read transform.
>>
>
> +0 from me. Sounds like benefits outweigh the drawbacks here and some of
> the drawbacks related to cross-language can be overcome through future
> advancements.
> Thanks for bringing this up Ismaël.
>
> - Cham
>
>
>>
>> On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:
>>
>>> Ismael, it is good to hear that using Read as the input didn't have a
>>> bunch of parameters that were being skipped/ignored. Also, for the
>>> polymorphism issue you have to rely on the user correctly telling you the
>>> type in such a way where it is a common ancestor of all the runtime types
>>> that will ever be used. This usually boils down to something like
>>> Serializable or DynamicMessage such that the coder that is chosen works for
>>> all the runtime types. Using multiple types is a valid use case and would
>>> allow for a simpler graph with less flattens merging the output from
>>> multiple sources.
>>>
>>> Boyuan, as you have mentioned we can have a coder for KafkaIO.Read which
>>> uses schemas even if some of the parameters can't be represented in a
>>> meaningful way beyond "bytes". This would be helpful for cross language as
>>> well since every parameter would become available if a language could
>>> support it (e.g. it could serialize a java function up front and keep it
>>> saved as raw bytes within said language). Even if we figure out a better
>>> way to do this in the future, we'll have to change the schema for the new
>>> way anyway. This would mean that the external version of the transform
>>> adopts Row to Read and we drop KafkaSourceDescriptor. The conversion from
>>> Row to Read could validate that the parameters make sense (e.g. the bytes
>>> are valid serialized functions). The addition of an
>>> endReadTime/endReadOffset would make sense for KafkaIO.Read as well and
>>> this would enable having a bounded version that could be used for backfills
>>> (this doesn't have to be done as part of any current ongoing PR).
>>> Essentially any parameter that could be added for a single instance of a
>>> Kafka element+restriction would also make sense to the KafkaIO.Read
>>> transform since it too is a single instance. There are parameters that
>>> would apply to the ReadAll that wouldn't apply to a read and these would be
>>> global parameters across all element+restriction pairs such as config
>>> overrides or default values.
>>>
>>> I am convinced that we should do as Ismael is suggesting and use
>>> KafkaIO.Read as the type.
>>>
>>>
>>> On Thu, Jun 25, 2020 at 6:00 PM Chamikara Jayalath 
>>> wrote:
>>>
 Discussion regarding cross-language transforms is a slight tangent
 here. But I think, in general, it's great if we can use existing transforms
 (for example, IO connectors) as cross-language transforms without having to
 build more composites (irrespective of whether in ExternalTransformBuilders
 or a user pipelines) just to make them cross-language compatible. A future
 cross-language compatible SchemaCoder might help (assuming that works for
 Read transform) but I'm not sure we have a good idea when we'll get to that
 state.

 Thanks,
 Cham

 On Thu, Jun 25, 2020 at 3:13 PM Boyuan Zhang 
 wrote:

> For unbounded SDF in Kafka, we also consider the upgrading/downgrading
> compatibility in the pipeline update scenario(For detailed discussion,
> please refer to
> https://lists.apache.org/thread.html/raf073b8741317244339eb5b2bce844c0f9e0d700c3e4de392fc648d6%40%3Cdev.beam.apache.org%3E).
> In order to obtain the compatibility, it requires the input of the read 
> SDF
> is schema-aware.
>
> Thus the major constraint of mapping KafkaSourceDescriptor to
> PCollection is, the KafkaIO.Read also needs to be schema-aware,
> otherwise pipeline updates might fail unnecessarily. If looking into
> KafkaIO.Read, not all necessary fields are compatible with schema, for
> example, SerializedFunction.
>
> I'm kind of confused by why ReadAll is a common pattern
> for SDF based IO. The Read can be a common pattern because the input is
> always a PBegin. But for an SDF based IO, the input can be 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Chamikara Jayalath]

On Fri, Jun 26, 2020 at 11:49 AM Luke Cwik  wrote:

> I would also like to suggest that transforms that implement ReadAll via
> Read should also provide methods like:
>
> // Uses the specified values if unspecified in the input element from the
> PCollection.
> withDefaults(Read read);
> // Uses the specified values regardless of what the input element from the
> PCollection specifies.
> withOverrides(Read read);
>
> and only adds methods that are required at construction time (e.g.
> coders). This way the majority of documentation sits on the Read transform.
>

+0 from me. Sounds like benefits outweigh the drawbacks here and some of
the drawbacks related to cross-language can be overcome through future
advancements.
Thanks for bringing this up Ismaël.

- Cham


>
> On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:
>
>> Ismael, it is good to hear that using Read as the input didn't have a
>> bunch of parameters that were being skipped/ignored. Also, for the
>> polymorphism issue you have to rely on the user correctly telling you the
>> type in such a way where it is a common ancestor of all the runtime types
>> that will ever be used. This usually boils down to something like
>> Serializable or DynamicMessage such that the coder that is chosen works for
>> all the runtime types. Using multiple types is a valid use case and would
>> allow for a simpler graph with less flattens merging the output from
>> multiple sources.
>>
>> Boyuan, as you have mentioned we can have a coder for KafkaIO.Read which
>> uses schemas even if some of the parameters can't be represented in a
>> meaningful way beyond "bytes". This would be helpful for cross language as
>> well since every parameter would become available if a language could
>> support it (e.g. it could serialize a java function up front and keep it
>> saved as raw bytes within said language). Even if we figure out a better
>> way to do this in the future, we'll have to change the schema for the new
>> way anyway. This would mean that the external version of the transform
>> adopts Row to Read and we drop KafkaSourceDescriptor. The conversion from
>> Row to Read could validate that the parameters make sense (e.g. the bytes
>> are valid serialized functions). The addition of an
>> endReadTime/endReadOffset would make sense for KafkaIO.Read as well and
>> this would enable having a bounded version that could be used for backfills
>> (this doesn't have to be done as part of any current ongoing PR).
>> Essentially any parameter that could be added for a single instance of a
>> Kafka element+restriction would also make sense to the KafkaIO.Read
>> transform since it too is a single instance. There are parameters that
>> would apply to the ReadAll that wouldn't apply to a read and these would be
>> global parameters across all element+restriction pairs such as config
>> overrides or default values.
>>
>> I am convinced that we should do as Ismael is suggesting and use
>> KafkaIO.Read as the type.
>>
>>
>> On Thu, Jun 25, 2020 at 6:00 PM Chamikara Jayalath 
>> wrote:
>>
>>> Discussion regarding cross-language transforms is a slight tangent here.
>>> But I think, in general, it's great if we can use existing transforms (for
>>> example, IO connectors) as cross-language transforms without having to
>>> build more composites (irrespective of whether in ExternalTransformBuilders
>>> or a user pipelines) just to make them cross-language compatible. A future
>>> cross-language compatible SchemaCoder might help (assuming that works for
>>> Read transform) but I'm not sure we have a good idea when we'll get to that
>>> state.
>>>
>>> Thanks,
>>> Cham
>>>
>>> On Thu, Jun 25, 2020 at 3:13 PM Boyuan Zhang  wrote:
>>>
 For unbounded SDF in Kafka, we also consider the upgrading/downgrading
 compatibility in the pipeline update scenario(For detailed discussion,
 please refer to
 https://lists.apache.org/thread.html/raf073b8741317244339eb5b2bce844c0f9e0d700c3e4de392fc648d6%40%3Cdev.beam.apache.org%3E).
 In order to obtain the compatibility, it requires the input of the read SDF
 is schema-aware.

 Thus the major constraint of mapping KafkaSourceDescriptor to
 PCollection is, the KafkaIO.Read also needs to be schema-aware,
 otherwise pipeline updates might fail unnecessarily. If looking into
 KafkaIO.Read, not all necessary fields are compatible with schema, for
 example, SerializedFunction.

 I'm kind of confused by why ReadAll is a common pattern
 for SDF based IO. The Read can be a common pattern because the input is
 always a PBegin. But for an SDF based IO, the input can be anything. By
 using Read as input, we will still have the maintenance cost when SDF IO
 supports a new field but Read doesn't consume it. For example, we are
 discussing adding endOffset and endReadTime to KafkaSourceDescriptior,
 which is not used in KafkaIO.Read.

 On Thu, Jun 25, 2020 at 2:19 PM Ismaël Mejía  wrote:

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Luke Cwik]

I would also like to suggest that transforms that implement ReadAll via
Read should also provide methods like:

// Uses the specified values if unspecified in the input element from the
PCollection.
withDefaults(Read read);
// Uses the specified values regardless of what the input element from the
PCollection specifies.
withOverrides(Read read);

and only adds methods that are required at construction time (e.g. coders).
This way the majority of documentation sits on the Read transform.

On Fri, Jun 26, 2020 at 9:58 AM Luke Cwik  wrote:

> Ismael, it is good to hear that using Read as the input didn't have a
> bunch of parameters that were being skipped/ignored. Also, for the
> polymorphism issue you have to rely on the user correctly telling you the
> type in such a way where it is a common ancestor of all the runtime types
> that will ever be used. This usually boils down to something like
> Serializable or DynamicMessage such that the coder that is chosen works for
> all the runtime types. Using multiple types is a valid use case and would
> allow for a simpler graph with less flattens merging the output from
> multiple sources.
>
> Boyuan, as you have mentioned we can have a coder for KafkaIO.Read which
> uses schemas even if some of the parameters can't be represented in a
> meaningful way beyond "bytes". This would be helpful for cross language as
> well since every parameter would become available if a language could
> support it (e.g. it could serialize a java function up front and keep it
> saved as raw bytes within said language). Even if we figure out a better
> way to do this in the future, we'll have to change the schema for the new
> way anyway. This would mean that the external version of the transform
> adopts Row to Read and we drop KafkaSourceDescriptor. The conversion from
> Row to Read could validate that the parameters make sense (e.g. the bytes
> are valid serialized functions). The addition of an
> endReadTime/endReadOffset would make sense for KafkaIO.Read as well and
> this would enable having a bounded version that could be used for backfills
> (this doesn't have to be done as part of any current ongoing PR).
> Essentially any parameter that could be added for a single instance of a
> Kafka element+restriction would also make sense to the KafkaIO.Read
> transform since it too is a single instance. There are parameters that
> would apply to the ReadAll that wouldn't apply to a read and these would be
> global parameters across all element+restriction pairs such as config
> overrides or default values.
>
> I am convinced that we should do as Ismael is suggesting and use
> KafkaIO.Read as the type.
>
>
> On Thu, Jun 25, 2020 at 6:00 PM Chamikara Jayalath 
> wrote:
>
>> Discussion regarding cross-language transforms is a slight tangent here.
>> But I think, in general, it's great if we can use existing transforms (for
>> example, IO connectors) as cross-language transforms without having to
>> build more composites (irrespective of whether in ExternalTransformBuilders
>> or a user pipelines) just to make them cross-language compatible. A future
>> cross-language compatible SchemaCoder might help (assuming that works for
>> Read transform) but I'm not sure we have a good idea when we'll get to that
>> state.
>>
>> Thanks,
>> Cham
>>
>> On Thu, Jun 25, 2020 at 3:13 PM Boyuan Zhang  wrote:
>>
>>> For unbounded SDF in Kafka, we also consider the upgrading/downgrading
>>> compatibility in the pipeline update scenario(For detailed discussion,
>>> please refer to
>>> https://lists.apache.org/thread.html/raf073b8741317244339eb5b2bce844c0f9e0d700c3e4de392fc648d6%40%3Cdev.beam.apache.org%3E).
>>> In order to obtain the compatibility, it requires the input of the read SDF
>>> is schema-aware.
>>>
>>> Thus the major constraint of mapping KafkaSourceDescriptor to
>>> PCollection is, the KafkaIO.Read also needs to be schema-aware,
>>> otherwise pipeline updates might fail unnecessarily. If looking into
>>> KafkaIO.Read, not all necessary fields are compatible with schema, for
>>> example, SerializedFunction.
>>>
>>> I'm kind of confused by why ReadAll is a common pattern
>>> for SDF based IO. The Read can be a common pattern because the input is
>>> always a PBegin. But for an SDF based IO, the input can be anything. By
>>> using Read as input, we will still have the maintenance cost when SDF IO
>>> supports a new field but Read doesn't consume it. For example, we are
>>> discussing adding endOffset and endReadTime to KafkaSourceDescriptior,
>>> which is not used in KafkaIO.Read.
>>>
>>> On Thu, Jun 25, 2020 at 2:19 PM Ismaël Mejía  wrote:
>>>
 We forgot to mention (5) External.Config used in cross-lang, see KafkaIO
 ExternalTransformBuilder. This approach is the predecessor of (4) and
 probably a
 really good candidate to be replaced by the Row based Configuration
 Boyuan is
 envisioning (so good to be aware of this).

 Thanks for the clear explanation Luke you 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Luke Cwik]

Ismael, it is good to hear that using Read as the input didn't have a bunch
of parameters that were being skipped/ignored. Also, for the polymorphism
issue you have to rely on the user correctly telling you the type in such a
way where it is a common ancestor of all the runtime types that will
ever be used. This usually boils down to something like Serializable or
DynamicMessage such that the coder that is chosen works for all the runtime
types. Using multiple types is a valid use case and would allow for a
simpler graph with less flattens merging the output from multiple sources.

Boyuan, as you have mentioned we can have a coder for KafkaIO.Read which
uses schemas even if some of the parameters can't be represented in a
meaningful way beyond "bytes". This would be helpful for cross language as
well since every parameter would become available if a language could
support it (e.g. it could serialize a java function up front and keep it
saved as raw bytes within said language). Even if we figure out a better
way to do this in the future, we'll have to change the schema for the new
way anyway. This would mean that the external version of the transform
adopts Row to Read and we drop KafkaSourceDescriptor. The conversion from
Row to Read could validate that the parameters make sense (e.g. the bytes
are valid serialized functions). The addition of an
endReadTime/endReadOffset would make sense for KafkaIO.Read as well and
this would enable having a bounded version that could be used for backfills
(this doesn't have to be done as part of any current ongoing PR).
Essentially any parameter that could be added for a single instance of a
Kafka element+restriction would also make sense to the KafkaIO.Read
transform since it too is a single instance. There are parameters that
would apply to the ReadAll that wouldn't apply to a read and these would be
global parameters across all element+restriction pairs such as config
overrides or default values.

I am convinced that we should do as Ismael is suggesting and use
KafkaIO.Read as the type.


On Thu, Jun 25, 2020 at 6:00 PM Chamikara Jayalath 
wrote:

> Discussion regarding cross-language transforms is a slight tangent here.
> But I think, in general, it's great if we can use existing transforms (for
> example, IO connectors) as cross-language transforms without having to
> build more composites (irrespective of whether in ExternalTransformBuilders
> or a user pipelines) just to make them cross-language compatible. A future
> cross-language compatible SchemaCoder might help (assuming that works for
> Read transform) but I'm not sure we have a good idea when we'll get to that
> state.
>
> Thanks,
> Cham
>
> On Thu, Jun 25, 2020 at 3:13 PM Boyuan Zhang  wrote:
>
>> For unbounded SDF in Kafka, we also consider the upgrading/downgrading
>> compatibility in the pipeline update scenario(For detailed discussion,
>> please refer to
>> https://lists.apache.org/thread.html/raf073b8741317244339eb5b2bce844c0f9e0d700c3e4de392fc648d6%40%3Cdev.beam.apache.org%3E).
>> In order to obtain the compatibility, it requires the input of the read SDF
>> is schema-aware.
>>
>> Thus the major constraint of mapping KafkaSourceDescriptor to
>> PCollection is, the KafkaIO.Read also needs to be schema-aware,
>> otherwise pipeline updates might fail unnecessarily. If looking into
>> KafkaIO.Read, not all necessary fields are compatible with schema, for
>> example, SerializedFunction.
>>
>> I'm kind of confused by why ReadAll is a common pattern
>> for SDF based IO. The Read can be a common pattern because the input is
>> always a PBegin. But for an SDF based IO, the input can be anything. By
>> using Read as input, we will still have the maintenance cost when SDF IO
>> supports a new field but Read doesn't consume it. For example, we are
>> discussing adding endOffset and endReadTime to KafkaSourceDescriptior,
>> which is not used in KafkaIO.Read.
>>
>> On Thu, Jun 25, 2020 at 2:19 PM Ismaël Mejía  wrote:
>>
>>> We forgot to mention (5) External.Config used in cross-lang, see KafkaIO
>>> ExternalTransformBuilder. This approach is the predecessor of (4) and
>>> probably a
>>> really good candidate to be replaced by the Row based Configuration
>>> Boyuan is
>>> envisioning (so good to be aware of this).
>>>
>>> Thanks for the clear explanation Luke you mention the real issue(s). All
>>> the
>>> approaches discussed so far in the end could be easily transformed to
>>> produce a
>>> PCollection and those Read Elements could be read by the generic
>>> ReadAll
>>> transform. Notice that this can be internal in some IOs e.g. KafkaIO if
>>> they
>>> decide not to expose it. I am not saying that we should force every IO to
>>> support ReadAll in its public API but if we do it is probably a good
>>> idea to be
>>> consistent with naming the transform that expects an input
>>> PCollection in
>>> the same way. Also notice that using it will save us of the maintenance
>>> issues
>>> discussed in my previous email.

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Chamikara Jayalath]

Discussion regarding cross-language transforms is a slight tangent here.
But I think, in general, it's great if we can use existing transforms (for
example, IO connectors) as cross-language transforms without having to
build more composites (irrespective of whether in ExternalTransformBuilders
or a user pipelines) just to make them cross-language compatible. A future
cross-language compatible SchemaCoder might help (assuming that works for
Read transform) but I'm not sure we have a good idea when we'll get to that
state.

Thanks,
Cham

On Thu, Jun 25, 2020 at 3:13 PM Boyuan Zhang  wrote:

> For unbounded SDF in Kafka, we also consider the upgrading/downgrading
> compatibility in the pipeline update scenario(For detailed discussion,
> please refer to
> https://lists.apache.org/thread.html/raf073b8741317244339eb5b2bce844c0f9e0d700c3e4de392fc648d6%40%3Cdev.beam.apache.org%3E).
> In order to obtain the compatibility, it requires the input of the read SDF
> is schema-aware.
>
> Thus the major constraint of mapping KafkaSourceDescriptor to
> PCollection is, the KafkaIO.Read also needs to be schema-aware,
> otherwise pipeline updates might fail unnecessarily. If looking into
> KafkaIO.Read, not all necessary fields are compatible with schema, for
> example, SerializedFunction.
>
> I'm kind of confused by why ReadAll is a common pattern for
> SDF based IO. The Read can be a common pattern because the input is always
> a PBegin. But for an SDF based IO, the input can be anything. By using Read
> as input, we will still have the maintenance cost when SDF IO supports a
> new field but Read doesn't consume it. For example, we are discussing
> adding endOffset and endReadTime to KafkaSourceDescriptior, which is not
> used in KafkaIO.Read.
>
> On Thu, Jun 25, 2020 at 2:19 PM Ismaël Mejía  wrote:
>
>> We forgot to mention (5) External.Config used in cross-lang, see KafkaIO
>> ExternalTransformBuilder. This approach is the predecessor of (4) and
>> probably a
>> really good candidate to be replaced by the Row based Configuration
>> Boyuan is
>> envisioning (so good to be aware of this).
>>
>> Thanks for the clear explanation Luke you mention the real issue(s). All
>> the
>> approaches discussed so far in the end could be easily transformed to
>> produce a
>> PCollection and those Read Elements could be read by the generic
>> ReadAll
>> transform. Notice that this can be internal in some IOs e.g. KafkaIO if
>> they
>> decide not to expose it. I am not saying that we should force every IO to
>> support ReadAll in its public API but if we do it is probably a good idea
>> to be
>> consistent with naming the transform that expects an input
>> PCollection in
>> the same way. Also notice that using it will save us of the maintenance
>> issues
>> discussed in my previous email.
>>
>> Back to the main concern: the consequences of expansion based on Read: So
>> far I
>> have not seen consequences for the Splitting part which maps really nice
>> assuming the Partition info / Restriction is available as part of Read.
>> So far
>> there are not Serialization because Beam is already enforcing this.
>> Notice that
>> ReadAll expansion is almost ‘equivalent’ to a poor man SDF at least for
>> the
>> Bounded case (see the code in my previous email). For the other points:
>>
>> > a) Do all properties set on a Read apply to the ReadAll? For example,
>> the
>> > Kafka Read implementation allows you to set the key and value
>> deserializers
>> > which are also used to dictate the output PCollection type. It also
>> allows you
>> > to set how the watermark should be computed. Technically a user may
>> want the
>> > watermark computation to be configurable per Read and they may also
>> want an
>> > output type which is polymorphic (e.g. Pcollection).
>>
>> Most of the times they do but for parametric types we cannot support
>> different
>> types in the outputs of the Read or at least I did not find how to do so
>> (is
>> there a way to use multiple output Coders on Beam?), we saw this in
>> CassandraIO
>> and we were discussing adding explicitly these Coders or Serializer
>> specific methods to the ReadAll transform. This is less nice because it
>> will
>> imply some repeated methods, but it is still a compromise to gain the
>> other
>> advantages. I suppose the watermark case you mention is similar because
>> you may
>> want the watermark to behave differently in each Read and we probably
>> don’t
>> support this, so it corresponds to the polymorphic category.
>>
>> > b) Read extends PTransform which brings its own object modelling
>> concerns.
>>
>> > During the implementations of ReadAll(PCollection), was it
>> discovered
>> > that some properties became runtime errors or were ignored if they were
>> set?
>> > If no, then the code deduplication is likely worth it because we also
>> get a
>> > lot of javadoc deduplication, but if yes is this an acceptable user
>> > experience?
>>
>> No, not so far. This is an interesting part, notice that the 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Boyuan Zhang]

For unbounded SDF in Kafka, we also consider the upgrading/downgrading
compatibility in the pipeline update scenario(For detailed discussion,
please refer to
https://lists.apache.org/thread.html/raf073b8741317244339eb5b2bce844c0f9e0d700c3e4de392fc648d6%40%3Cdev.beam.apache.org%3E).
In order to obtain the compatibility, it requires the input of the read SDF
is schema-aware.

Thus the major constraint of mapping KafkaSourceDescriptor to
PCollection is, the KafkaIO.Read also needs to be schema-aware,
otherwise pipeline updates might fail unnecessarily. If looking into
KafkaIO.Read, not all necessary fields are compatible with schema, for
example, SerializedFunction.

I'm kind of confused by why ReadAll is a common pattern for
SDF based IO. The Read can be a common pattern because the input is always
a PBegin. But for an SDF based IO, the input can be anything. By using Read
as input, we will still have the maintenance cost when SDF IO supports a
new field but Read doesn't consume it. For example, we are discussing
adding endOffset and endReadTime to KafkaSourceDescriptior, which is not
used in KafkaIO.Read.

On Thu, Jun 25, 2020 at 2:19 PM Ismaël Mejía  wrote:

> We forgot to mention (5) External.Config used in cross-lang, see KafkaIO
> ExternalTransformBuilder. This approach is the predecessor of (4) and
> probably a
> really good candidate to be replaced by the Row based Configuration Boyuan
> is
> envisioning (so good to be aware of this).
>
> Thanks for the clear explanation Luke you mention the real issue(s). All
> the
> approaches discussed so far in the end could be easily transformed to
> produce a
> PCollection and those Read Elements could be read by the generic
> ReadAll
> transform. Notice that this can be internal in some IOs e.g. KafkaIO if
> they
> decide not to expose it. I am not saying that we should force every IO to
> support ReadAll in its public API but if we do it is probably a good idea
> to be
> consistent with naming the transform that expects an input
> PCollection in
> the same way. Also notice that using it will save us of the maintenance
> issues
> discussed in my previous email.
>
> Back to the main concern: the consequences of expansion based on Read: So
> far I
> have not seen consequences for the Splitting part which maps really nice
> assuming the Partition info / Restriction is available as part of Read. So
> far
> there are not Serialization because Beam is already enforcing this. Notice
> that
> ReadAll expansion is almost ‘equivalent’ to a poor man SDF at least for the
> Bounded case (see the code in my previous email). For the other points:
>
> > a) Do all properties set on a Read apply to the ReadAll? For example, the
> > Kafka Read implementation allows you to set the key and value
> deserializers
> > which are also used to dictate the output PCollection type. It also
> allows you
> > to set how the watermark should be computed. Technically a user may want
> the
> > watermark computation to be configurable per Read and they may also want
> an
> > output type which is polymorphic (e.g. Pcollection).
>
> Most of the times they do but for parametric types we cannot support
> different
> types in the outputs of the Read or at least I did not find how to do so
> (is
> there a way to use multiple output Coders on Beam?), we saw this in
> CassandraIO
> and we were discussing adding explicitly these Coders or Serializer
> specific methods to the ReadAll transform. This is less nice because it
> will
> imply some repeated methods, but it is still a compromise to gain the other
> advantages. I suppose the watermark case you mention is similar because
> you may
> want the watermark to behave differently in each Read and we probably don’t
> support this, so it corresponds to the polymorphic category.
>
> > b) Read extends PTransform which brings its own object modelling
> concerns.
>
> > During the implementations of ReadAll(PCollection), was it
> discovered
> > that some properties became runtime errors or were ignored if they were
> set?
> > If no, then the code deduplication is likely worth it because we also
> get a
> > lot of javadoc deduplication, but if yes is this an acceptable user
> > experience?
>
> No, not so far. This is an interesting part, notice that the Read
> translation
> ends up delegating the read bits to the ReadFn part of ReadAll so the
> ReadFn is
> the real read and must be aware and use all the parameters.
>
> @Override
> public PCollection expand(PBegin input) {
>   return input.apply("Create", Create.of(this)).apply("ReadAll",
> readAll());
> }
>
> I might be missing something for the Unbounded SDF case which is the only
> case
> we have not explored so far. I think one easy way to see the limitations
> would
> be in the ongoing KafkaIO SDF based implementation to try to map
> KafkaSourceDescriptor to do the extra PCollection and the Read logic
> on
> the ReadAll with the SDF to see which constraints we hit, the polymorphic
> ones
> 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Ismaël Mejía]

We forgot to mention (5) External.Config used in cross-lang, see KafkaIO
ExternalTransformBuilder. This approach is the predecessor of (4) and probably a
really good candidate to be replaced by the Row based Configuration Boyuan is
envisioning (so good to be aware of this).

Thanks for the clear explanation Luke you mention the real issue(s). All the
approaches discussed so far in the end could be easily transformed to produce a
PCollection and those Read Elements could be read by the generic ReadAll
transform. Notice that this can be internal in some IOs e.g. KafkaIO if they
decide not to expose it. I am not saying that we should force every IO to
support ReadAll in its public API but if we do it is probably a good idea to be
consistent with naming the transform that expects an input PCollection in
the same way. Also notice that using it will save us of the maintenance issues
discussed in my previous email.

Back to the main concern: the consequences of expansion based on Read: So far I
have not seen consequences for the Splitting part which maps really nice
assuming the Partition info / Restriction is available as part of Read. So far
there are not Serialization because Beam is already enforcing this. Notice that
ReadAll expansion is almost ‘equivalent’ to a poor man SDF at least for the
Bounded case (see the code in my previous email). For the other points:

> a) Do all properties set on a Read apply to the ReadAll? For example, the
> Kafka Read implementation allows you to set the key and value deserializers
> which are also used to dictate the output PCollection type. It also allows you
> to set how the watermark should be computed. Technically a user may want the
> watermark computation to be configurable per Read and they may also want an
> output type which is polymorphic (e.g. Pcollection).

Most of the times they do but for parametric types we cannot support different
types in the outputs of the Read or at least I did not find how to do so (is
there a way to use multiple output Coders on Beam?), we saw this in CassandraIO
and we were discussing adding explicitly these Coders or Serializer
specific methods to the ReadAll transform. This is less nice because it will
imply some repeated methods, but it is still a compromise to gain the other
advantages. I suppose the watermark case you mention is similar because you may
want the watermark to behave differently in each Read and we probably don’t
support this, so it corresponds to the polymorphic category.

> b) Read extends PTransform which brings its own object modelling concerns.

> During the implementations of ReadAll(PCollection), was it discovered
> that some properties became runtime errors or were ignored if they were set?
> If no, then the code deduplication is likely worth it because we also get a
> lot of javadoc deduplication, but if yes is this an acceptable user
> experience?

No, not so far. This is an interesting part, notice that the Read translation
ends up delegating the read bits to the ReadFn part of ReadAll so the ReadFn is
the real read and must be aware and use all the parameters.

@Override
public PCollection expand(PBegin input) {
  return input.apply("Create", Create.of(this)).apply("ReadAll", readAll());
}

I might be missing something for the Unbounded SDF case which is the only case
we have not explored so far. I think one easy way to see the limitations would
be in the ongoing KafkaIO SDF based implementation to try to map
KafkaSourceDescriptor to do the extra PCollection and the Read logic on
the ReadAll with the SDF to see which constraints we hit, the polymorphic ones
will be there for sure, maybe others will appear (not sure). However it would be
interesting to see if we have a real gain in the maintenance points, but well
let’s not forget also that KafkaIO has a LOT of knobs so probably the generic
implementation could be relatively complex.



On Thu, Jun 25, 2020 at 6:30 PM Luke Cwik  wrote:
>
> I had mentioned that approach 1 and approach 2 work for cross language. The 
> difference being that the cross language transform would take a well known 
> definition and convert it to the Read transform. A normal user would have a 
> pipeline that would look like:
> 1: PCollection -> PTransform(ReadAll) -> PCollection
> 2: PCollection -> PTransform(ReadAll) -> PCollection
>
> And in the cross language case this would look like:
> 1: PCollection -> PTransform(Convert Row to Read) -> 
> PCollection -> PTransform(ReadAll) -> PCollection
> 2: PCollection -> PTransform(Convert Row to 
> SourceDescriptor) -> PCollection -> PTransform(ReadAll) -> 
> PCollection*
> * note that PTransform(Convert Row to SourceDescriptor) only exists since we 
> haven't solved how to use schemas with language bound types in a cross 
> language way. SchemaCoder isn't portable but RowCoder is which is why the 
> conversion step exists. We could have a solution for this at some point in 
> time.
>
> My concern with using Read was 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Luke Cwik]

I had mentioned that approach 1 and approach 2 work for cross language. The
difference being that the cross language transform would take a well known
definition and convert it to the Read transform. A normal user would have a
pipeline that would look like:
1: PCollection -> PTransform(ReadAll) -> PCollection
2: PCollection -> PTransform(ReadAll) ->
PCollection

And in the cross language case this would look like:
1: PCollection -> PTransform(Convert Row to Read)
-> PCollection -> PTransform(ReadAll) -> PCollection
2: PCollection -> PTransform(Convert Row to
SourceDescriptor) -> PCollection -> PTransform(ReadAll)
-> PCollection*
* note that PTransform(Convert Row to SourceDescriptor) only exists since
we haven't solved how to use schemas with language bound types in a cross
language way. SchemaCoder isn't portable but RowCoder is which is why the
conversion step exists. We could have a solution for this at some point in
time.

My concern with using Read was around:
a) Do all properties set on a Read apply to the ReadAll? For example, the
Kafka Read implementation allows you to set the key and value deserializers
which are also used to dictate the output PCollection type. It also allows
you to set how the watermark should be computed. Technically a user may
want the watermark computation to be configurable per Read and they may
also want an output type which is polymorphic (e.g.
PCollection).
b) Read extends PTransform which brings its own object modelling concerns.

During the implementations of ReadAll(PCollection), was it discovered
that some properties became runtime errors or were ignored if they were
set? If no, then the code deduplication is likely worth it because we also
get a lot of javadoc deduplication, but if yes is this an acceptable user
experience?


On Thu, Jun 25, 2020 at 7:55 AM Alexey Romanenko 
wrote:

> I believe that the initial goal of unifying ReadAll as a general
> "PTransform, PCollection>” was to reduce the
> amount of code duplication and error-prone approach related to this. It
> makes much sense since usually we have all needed configuration set in Read
> objects and, as Ismaeil mentioned, ReadAll will consist mostly of only
> Split-Shuffle-Read stages.  So this case usually can be unified by
> using PCollection as input.
>
> On the other hand, we have another need to use Java IOs as cross-language
> transforms (as Luke described) which seems only partly in common with
> previous pattern of ReadAll using.
>
> I’d be more in favour to have only one concept of read configuration for
> all needs but seems it’s not easy and I’d be more in favour with Luke and
> Boyuan approach with schema. Though, maybe ReadAll is not a very suitable
> name in this case because it will can bring some confusions related to
> previous pattern of ReadAll uses.
>
> On 25 Jun 2020, at 05:00, Boyuan Zhang  wrote:
>
> Sorry for the typo. I mean I think we can go with *(3)* and (4): use the
> data type that is schema-aware as the input of ReadAll.
>
> On Wed, Jun 24, 2020 at 7:42 PM Boyuan Zhang  wrote:
>
>> Thanks for the summary, Cham!
>>
>> I think we can go with (2) and (4): use the data type that is
>> schema-aware as the input of ReadAll.
>>
>> Converting Read into ReadAll helps us to stick with SDF-like IO. But only
>> having  (3) is not enough to solve the problem of using ReadAll in x-lang
>> case.
>>
>> The key point of ReadAll is that the input type of ReadAll should be able
>> to cross language boundaries and have compatibilities of
>> updating/downgrading. After investigating some possibilities(pure java pojo
>> with custom coder, protobuf, row/schema) in Kafka usage, we find that
>> row/schema fits our needs most. Here comes (4). I believe that using Read
>> as input of ReadAll makes sense in some cases, but I also think not all IOs
>> have the same need. I would treat Read as a special type as long as the
>> Read is schema-aware.
>>
>> On Wed, Jun 24, 2020 at 6:34 PM Chamikara Jayalath 
>> wrote:
>>
>>> I see. So it seems like there are three options discussed so far when it
>>> comes to defining source descriptors for ReadAll type transforms
>>>
>>> (1) Use Read PTransform as the element type of the input PCollection
>>> (2) Use a POJO that describes the source as the data element of the
>>> input PCollection
>>> (3) Provide a converter as a function to the Read transform which
>>> essentially will convert it to a ReadAll (what Eugene mentioned)
>>>
>>> I feel like (3) is more suitable for a related set of source
>>> descriptions such as files.
>>> (1) will allow most code-reuse but seems like will make it hard to use
>>> the ReadAll transform as a cross-language transform and will break the
>>> separation of construction time and runtime constructs
>>> (2) could result to less code reuse if not careful but will make the
>>> transform easier to be used as a cross-language transform without
>>> additional modifications
>>>
>>> Also, with SDF, we can create ReadAll-like transforms that are 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Alexey Romanenko]

I believe that the initial goal of unifying ReadAll as a general 
"PTransform, PCollection>” was to reduce the 
amount of code duplication and error-prone approach related to this. It makes 
much sense since usually we have all needed configuration set in Read objects 
and, as Ismaeil mentioned, ReadAll will consist mostly of only 
Split-Shuffle-Read stages.  So this case usually can be unified by using 
PCollection as input.

On the other hand, we have another need to use Java IOs as cross-language 
transforms (as Luke described) which seems only partly in common with previous 
pattern of ReadAll using. 

I’d be more in favour to have only one concept of read configuration for all 
needs but seems it’s not easy and I’d be more in favour with Luke and Boyuan 
approach with schema. Though, maybe ReadAll is not a very suitable name in this 
case because it will can bring some confusions related to previous pattern of 
ReadAll uses.

> On 25 Jun 2020, at 05:00, Boyuan Zhang  wrote:
> 
> Sorry for the typo. I mean I think we can go with (3) and (4): use the data 
> type that is schema-aware as the input of ReadAll.
> 
> On Wed, Jun 24, 2020 at 7:42 PM Boyuan Zhang  > wrote:
> Thanks for the summary, Cham!
> 
> I think we can go with (2) and (4): use the data type that is schema-aware as 
> the input of ReadAll.
> 
> Converting Read into ReadAll helps us to stick with SDF-like IO. But only 
> having  (3) is not enough to solve the problem of using ReadAll in x-lang 
> case. 
> 
> The key point of ReadAll is that the input type of ReadAll should be able to 
> cross language boundaries and have compatibilities of updating/downgrading. 
> After investigating some possibilities(pure java pojo with custom coder, 
> protobuf, row/schema) in Kafka usage, we find that row/schema fits our needs 
> most. Here comes (4). I believe that using Read as input of ReadAll makes 
> sense in some cases, but I also think not all IOs have the same need. I would 
> treat Read as a special type as long as the Read is schema-aware. 
> 
> On Wed, Jun 24, 2020 at 6:34 PM Chamikara Jayalath  > wrote:
> I see. So it seems like there are three options discussed so far when it 
> comes to defining source descriptors for ReadAll type transforms
> 
> (1) Use Read PTransform as the element type of the input PCollection 
> (2) Use a POJO that describes the source as the data element of the input 
> PCollection
> (3) Provide a converter as a function to the Read transform which essentially 
> will convert it to a ReadAll (what Eugene mentioned)
> 
> I feel like (3) is more suitable for a related set of source descriptions 
> such as files.
> (1) will allow most code-reuse but seems like will make it hard to use the 
> ReadAll transform as a cross-language transform and will break the separation 
> of construction time and runtime constructs
> (2) could result to less code reuse if not careful but will make the 
> transform easier to be used as a cross-language transform without additional 
> modifications
> 
> Also, with SDF, we can create ReadAll-like transforms that are more 
> efficient. So we might be able to just define all sources in that format and 
> make Read transforms just an easy to use composite built on top of that (by 
> adding a preceding Create transform).
> 
> Thanks,
> Cham
> 
> On Wed, Jun 24, 2020 at 11:10 AM Luke Cwik  > wrote:
> I believe we do require PTransforms to be serializable since anonymous DoFns 
> typically capture the enclosing PTransform.
> 
> On Wed, Jun 24, 2020 at 10:52 AM Chamikara Jayalath  > wrote:
> Seems like Read in PCollection refers to a transform, at least here: 
> https://github.com/apache/beam/blob/master/sdks/java/io/hbase/src/main/java/org/apache/beam/sdk/io/hbase/HBaseIO.java#L353
>  
> 
> 
> I'm in favour of separating construction time transforms from execution time 
> data objects that we store in PCollections as Luke mentioned. Also, we don't 
> guarantee that PTransform is serializable so users have the additional 
> complexity of providing a corder whenever a PTransform is used as a data 
> object.
> Also, agree with Boyuan that using simple Java objects that are convertible 
> to Beam Rows allow us to make these transforms available to other SDKs 
> through the cross-language transforms. Using transforms or complex sources as 
> data objects will probably make this difficult.
> 
> Thanks,
> Cham
> 
> 
> 
> On Wed, Jun 24, 2020 at 10:32 AM Boyuan Zhang  > wrote:
> Hi Ismael,
> 
> I think the ReadAll in the IO connector refers to the IO with SDF 
> implementation despite the type of input, where Read refers to 
> UnboundedSource.  One major pushback of using KafkaIO.Read as source 
> description is that not all configurations of 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Boyuan Zhang]

Sorry for the typo. I mean I think we can go with *(3)* and (4): use the
data type that is schema-aware as the input of ReadAll.

On Wed, Jun 24, 2020 at 7:42 PM Boyuan Zhang  wrote:

> Thanks for the summary, Cham!
>
> I think we can go with (2) and (4): use the data type that is schema-aware
> as the input of ReadAll.
>
> Converting Read into ReadAll helps us to stick with SDF-like IO. But only
> having  (3) is not enough to solve the problem of using ReadAll in x-lang
> case.
>
> The key point of ReadAll is that the input type of ReadAll should be able
> to cross language boundaries and have compatibilities of
> updating/downgrading. After investigating some possibilities(pure java pojo
> with custom coder, protobuf, row/schema) in Kafka usage, we find that
> row/schema fits our needs most. Here comes (4). I believe that using Read
> as input of ReadAll makes sense in some cases, but I also think not all IOs
> have the same need. I would treat Read as a special type as long as the
> Read is schema-aware.
>
> On Wed, Jun 24, 2020 at 6:34 PM Chamikara Jayalath 
> wrote:
>
>> I see. So it seems like there are three options discussed so far when it
>> comes to defining source descriptors for ReadAll type transforms
>>
>> (1) Use Read PTransform as the element type of the input PCollection
>> (2) Use a POJO that describes the source as the data element of the input
>> PCollection
>> (3) Provide a converter as a function to the Read transform which
>> essentially will convert it to a ReadAll (what Eugene mentioned)
>>
>> I feel like (3) is more suitable for a related set of source descriptions
>> such as files.
>> (1) will allow most code-reuse but seems like will make it hard to use
>> the ReadAll transform as a cross-language transform and will break the
>> separation of construction time and runtime constructs
>> (2) could result to less code reuse if not careful but will make the
>> transform easier to be used as a cross-language transform without
>> additional modifications
>>
>> Also, with SDF, we can create ReadAll-like transforms that are more
>> efficient. So we might be able to just define all sources in that format
>> and make Read transforms just an easy to use composite built on top of that
>> (by adding a preceding Create transform).
>>
>> Thanks,
>> Cham
>>
>> On Wed, Jun 24, 2020 at 11:10 AM Luke Cwik  wrote:
>>
>>> I believe we do require PTransforms to be serializable since anonymous
>>> DoFns typically capture the enclosing PTransform.
>>>
>>> On Wed, Jun 24, 2020 at 10:52 AM Chamikara Jayalath <
>>> chamik...@google.com> wrote:
>>>
 Seems like Read in PCollection refers to a transform, at least
 here:
 https://github.com/apache/beam/blob/master/sdks/java/io/hbase/src/main/java/org/apache/beam/sdk/io/hbase/HBaseIO.java#L353

 I'm in favour of separating construction time transforms from execution
 time data objects that we store in PCollections as Luke mentioned. Also, we
 don't guarantee that PTransform is serializable so users have the
 additional complexity of providing a corder whenever a PTransform is used
 as a data object.
 Also, agree with Boyuan that using simple Java objects that are
 convertible to Beam Rows allow us to make these transforms available to
 other SDKs through the cross-language transforms. Using transforms or
 complex sources as data objects will probably make this difficult.

 Thanks,
 Cham



 On Wed, Jun 24, 2020 at 10:32 AM Boyuan Zhang 
 wrote:

> Hi Ismael,
>
> I think the ReadAll in the IO connector refers to the IO with SDF
> implementation despite the type of input, where Read refers to
> UnboundedSource.  One major pushback of using KafkaIO.Read as source
> description is that not all configurations of KafkaIO.Read are meaningful
> to populate during execution time. Also when thinking about x-lang useage,
> making source description across language boundaries is also necessary.  
> As
> Luke mentioned, it's quite easy to infer a Schema from an AutoValue 
> object:
> KafkaSourceDescription.java
> .
> Then the coder of this schema-aware object will be a SchemaCoder
> .
> When crossing language boundaries, it's also easy to convert a Row into 
> the
> source description: Convert.fromRows
> 
> .
>
>
> On Wed, Jun 24, 2020 at 9:51 AM Luke Cwik  wrote:
>
>> To provide additional context, the KafkaIO ReadAll transform takes a
>> PCollection. This KafkaSourceDescriptor is a 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Boyuan Zhang]

Thanks for the summary, Cham!

I think we can go with (2) and (4): use the data type that is schema-aware
as the input of ReadAll.

Converting Read into ReadAll helps us to stick with SDF-like IO. But only
having  (3) is not enough to solve the problem of using ReadAll in x-lang
case.

The key point of ReadAll is that the input type of ReadAll should be able
to cross language boundaries and have compatibilities of
updating/downgrading. After investigating some possibilities(pure java pojo
with custom coder, protobuf, row/schema) in Kafka usage, we find that
row/schema fits our needs most. Here comes (4). I believe that using Read
as input of ReadAll makes sense in some cases, but I also think not all IOs
have the same need. I would treat Read as a special type as long as the
Read is schema-aware.

On Wed, Jun 24, 2020 at 6:34 PM Chamikara Jayalath 
wrote:

> I see. So it seems like there are three options discussed so far when it
> comes to defining source descriptors for ReadAll type transforms
>
> (1) Use Read PTransform as the element type of the input PCollection
> (2) Use a POJO that describes the source as the data element of the input
> PCollection
> (3) Provide a converter as a function to the Read transform which
> essentially will convert it to a ReadAll (what Eugene mentioned)
>
> I feel like (3) is more suitable for a related set of source descriptions
> such as files.
> (1) will allow most code-reuse but seems like will make it hard to use the
> ReadAll transform as a cross-language transform and will break the
> separation of construction time and runtime constructs
> (2) could result to less code reuse if not careful but will make the
> transform easier to be used as a cross-language transform without
> additional modifications
>
> Also, with SDF, we can create ReadAll-like transforms that are more
> efficient. So we might be able to just define all sources in that format
> and make Read transforms just an easy to use composite built on top of that
> (by adding a preceding Create transform).
>
> Thanks,
> Cham
>
> On Wed, Jun 24, 2020 at 11:10 AM Luke Cwik  wrote:
>
>> I believe we do require PTransforms to be serializable since anonymous
>> DoFns typically capture the enclosing PTransform.
>>
>> On Wed, Jun 24, 2020 at 10:52 AM Chamikara Jayalath 
>> wrote:
>>
>>> Seems like Read in PCollection refers to a transform, at least
>>> here:
>>> https://github.com/apache/beam/blob/master/sdks/java/io/hbase/src/main/java/org/apache/beam/sdk/io/hbase/HBaseIO.java#L353
>>>
>>> I'm in favour of separating construction time transforms from execution
>>> time data objects that we store in PCollections as Luke mentioned. Also, we
>>> don't guarantee that PTransform is serializable so users have the
>>> additional complexity of providing a corder whenever a PTransform is used
>>> as a data object.
>>> Also, agree with Boyuan that using simple Java objects that are
>>> convertible to Beam Rows allow us to make these transforms available to
>>> other SDKs through the cross-language transforms. Using transforms or
>>> complex sources as data objects will probably make this difficult.
>>>
>>> Thanks,
>>> Cham
>>>
>>>
>>>
>>> On Wed, Jun 24, 2020 at 10:32 AM Boyuan Zhang 
>>> wrote:
>>>
 Hi Ismael,

 I think the ReadAll in the IO connector refers to the IO with SDF
 implementation despite the type of input, where Read refers to
 UnboundedSource.  One major pushback of using KafkaIO.Read as source
 description is that not all configurations of KafkaIO.Read are meaningful
 to populate during execution time. Also when thinking about x-lang useage,
 making source description across language boundaries is also necessary.  As
 Luke mentioned, it's quite easy to infer a Schema from an AutoValue object:
 KafkaSourceDescription.java
 .
 Then the coder of this schema-aware object will be a SchemaCoder
 .
 When crossing language boundaries, it's also easy to convert a Row into the
 source description: Convert.fromRows
 
 .


 On Wed, Jun 24, 2020 at 9:51 AM Luke Cwik  wrote:

> To provide additional context, the KafkaIO ReadAll transform takes a
> PCollection. This KafkaSourceDescriptor is a POJO
> that contains the configurable parameters for reading from Kafka. This is
> different from the pattern that Ismael listed because they take
> PCollection as input and the Read is the same as the Read PTransform
> class used for the non read all case.
>
> The KafkaSourceDescriptor does lead to duplication since 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Chamikara Jayalath]

I see. So it seems like there are three options discussed so far when it
comes to defining source descriptors for ReadAll type transforms

(1) Use Read PTransform as the element type of the input PCollection
(2) Use a POJO that describes the source as the data element of the input
PCollection
(3) Provide a converter as a function to the Read transform which
essentially will convert it to a ReadAll (what Eugene mentioned)

I feel like (3) is more suitable for a related set of source descriptions
such as files.
(1) will allow most code-reuse but seems like will make it hard to use the
ReadAll transform as a cross-language transform and will break the
separation of construction time and runtime constructs
(2) could result to less code reuse if not careful but will make the
transform easier to be used as a cross-language transform without
additional modifications

Also, with SDF, we can create ReadAll-like transforms that are more
efficient. So we might be able to just define all sources in that format
and make Read transforms just an easy to use composite built on top of that
(by adding a preceding Create transform).

Thanks,
Cham

On Wed, Jun 24, 2020 at 11:10 AM Luke Cwik  wrote:

> I believe we do require PTransforms to be serializable since anonymous
> DoFns typically capture the enclosing PTransform.
>
> On Wed, Jun 24, 2020 at 10:52 AM Chamikara Jayalath 
> wrote:
>
>> Seems like Read in PCollection refers to a transform, at least
>> here:
>> https://github.com/apache/beam/blob/master/sdks/java/io/hbase/src/main/java/org/apache/beam/sdk/io/hbase/HBaseIO.java#L353
>>
>> I'm in favour of separating construction time transforms from execution
>> time data objects that we store in PCollections as Luke mentioned. Also, we
>> don't guarantee that PTransform is serializable so users have the
>> additional complexity of providing a corder whenever a PTransform is used
>> as a data object.
>> Also, agree with Boyuan that using simple Java objects that are
>> convertible to Beam Rows allow us to make these transforms available to
>> other SDKs through the cross-language transforms. Using transforms or
>> complex sources as data objects will probably make this difficult.
>>
>> Thanks,
>> Cham
>>
>>
>>
>> On Wed, Jun 24, 2020 at 10:32 AM Boyuan Zhang  wrote:
>>
>>> Hi Ismael,
>>>
>>> I think the ReadAll in the IO connector refers to the IO with SDF
>>> implementation despite the type of input, where Read refers to
>>> UnboundedSource.  One major pushback of using KafkaIO.Read as source
>>> description is that not all configurations of KafkaIO.Read are meaningful
>>> to populate during execution time. Also when thinking about x-lang useage,
>>> making source description across language boundaries is also necessary.  As
>>> Luke mentioned, it's quite easy to infer a Schema from an AutoValue object:
>>> KafkaSourceDescription.java
>>> .
>>> Then the coder of this schema-aware object will be a SchemaCoder
>>> .
>>> When crossing language boundaries, it's also easy to convert a Row into the
>>> source description: Convert.fromRows
>>> 
>>> .
>>>
>>>
>>> On Wed, Jun 24, 2020 at 9:51 AM Luke Cwik  wrote:
>>>
 To provide additional context, the KafkaIO ReadAll transform takes a
 PCollection. This KafkaSourceDescriptor is a POJO
 that contains the configurable parameters for reading from Kafka. This is
 different from the pattern that Ismael listed because they take
 PCollection as input and the Read is the same as the Read PTransform
 class used for the non read all case.

 The KafkaSourceDescriptor does lead to duplication since parameters
 used to configure the transform have to be copied over to the source
 descriptor but decouples how a transform is specified from the object that
 describes what needs to be done. I believe Ismael's point is that we
 wouldn't need such a decoupling.

 Another area that hasn't been discussed and I believe is a non-issue is
 that the Beam Java SDK has the most IO connectors and we would want to use
 the IO implementations within Beam Go and Beam Python. This brings in its
 own set of issues related to versioning and compatibility for the wire
 format and how one parameterizes such transforms. The wire format issue can
 be solved with either approach by making sure that the cross language
 expansion always takes the well known format (whatever it may be) and
 converts it into Read/KafkaSourceDescriptor/... object that is then passed
 to the ReadAll transform. Boyuan has been looking to make the
 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Luke Cwik]

I believe we do require PTransforms to be serializable since anonymous
DoFns typically capture the enclosing PTransform.

On Wed, Jun 24, 2020 at 10:52 AM Chamikara Jayalath 
wrote:

> Seems like Read in PCollection refers to a transform, at least here:
> https://github.com/apache/beam/blob/master/sdks/java/io/hbase/src/main/java/org/apache/beam/sdk/io/hbase/HBaseIO.java#L353
>
> I'm in favour of separating construction time transforms from execution
> time data objects that we store in PCollections as Luke mentioned. Also, we
> don't guarantee that PTransform is serializable so users have the
> additional complexity of providing a corder whenever a PTransform is used
> as a data object.
> Also, agree with Boyuan that using simple Java objects that are
> convertible to Beam Rows allow us to make these transforms available to
> other SDKs through the cross-language transforms. Using transforms or
> complex sources as data objects will probably make this difficult.
>
> Thanks,
> Cham
>
>
>
> On Wed, Jun 24, 2020 at 10:32 AM Boyuan Zhang  wrote:
>
>> Hi Ismael,
>>
>> I think the ReadAll in the IO connector refers to the IO with SDF
>> implementation despite the type of input, where Read refers to
>> UnboundedSource.  One major pushback of using KafkaIO.Read as source
>> description is that not all configurations of KafkaIO.Read are meaningful
>> to populate during execution time. Also when thinking about x-lang useage,
>> making source description across language boundaries is also necessary.  As
>> Luke mentioned, it's quite easy to infer a Schema from an AutoValue object:
>> KafkaSourceDescription.java
>> .
>> Then the coder of this schema-aware object will be a SchemaCoder
>> .
>> When crossing language boundaries, it's also easy to convert a Row into the
>> source description: Convert.fromRows
>> 
>> .
>>
>>
>> On Wed, Jun 24, 2020 at 9:51 AM Luke Cwik  wrote:
>>
>>> To provide additional context, the KafkaIO ReadAll transform takes a
>>> PCollection. This KafkaSourceDescriptor is a POJO
>>> that contains the configurable parameters for reading from Kafka. This is
>>> different from the pattern that Ismael listed because they take
>>> PCollection as input and the Read is the same as the Read PTransform
>>> class used for the non read all case.
>>>
>>> The KafkaSourceDescriptor does lead to duplication since parameters used
>>> to configure the transform have to be copied over to the source descriptor
>>> but decouples how a transform is specified from the object that describes
>>> what needs to be done. I believe Ismael's point is that we wouldn't need
>>> such a decoupling.
>>>
>>> Another area that hasn't been discussed and I believe is a non-issue is
>>> that the Beam Java SDK has the most IO connectors and we would want to use
>>> the IO implementations within Beam Go and Beam Python. This brings in its
>>> own set of issues related to versioning and compatibility for the wire
>>> format and how one parameterizes such transforms. The wire format issue can
>>> be solved with either approach by making sure that the cross language
>>> expansion always takes the well known format (whatever it may be) and
>>> converts it into Read/KafkaSourceDescriptor/... object that is then passed
>>> to the ReadAll transform. Boyuan has been looking to make the
>>> KafkaSourceDescriptor have a schema so it can be represented as a row and
>>> this can be done easily using the AutoValue integration (I don't believe
>>> there is anything preventing someone from writing a schema row -> Read ->
>>> row adapter or also using the AutoValue configuration if the transform is
>>> also an AutoValue).
>>>
>>> I would be more for the code duplication and separation of concerns
>>> provided by using a different object to represent the contents of the
>>> PCollection from the pipeline construction time PTransform.
>>>
>>> On Wed, Jun 24, 2020 at 9:09 AM Eugene Kirpichov 
>>> wrote:
>>>
 Hi Ismael,

 Thanks for taking this on. Have you considered an approach similar (or
 dual) to FileIO.write(), where we in a sense also have to configure a
 dynamic number different IO transforms of the same type (file writes)?

 E.g. how in this example we configure many aspects of many file writes:

 transactions.apply(FileIO.writeDynamic()
  .by(Transaction::getType)
  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
 written to CSVSink
   type -> new CSVSink(type.getFieldNames()))
  .to(".../path/to/")
  .withNaming(type -> defaultNaming(type + 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Chamikara Jayalath]

Seems like Read in PCollection refers to a transform, at least here:
https://github.com/apache/beam/blob/master/sdks/java/io/hbase/src/main/java/org/apache/beam/sdk/io/hbase/HBaseIO.java#L353

I'm in favour of separating construction time transforms from execution
time data objects that we store in PCollections as Luke mentioned. Also, we
don't guarantee that PTransform is serializable so users have the
additional complexity of providing a corder whenever a PTransform is used
as a data object.
Also, agree with Boyuan that using simple Java objects that are
convertible to Beam Rows allow us to make these transforms available to
other SDKs through the cross-language transforms. Using transforms or
complex sources as data objects will probably make this difficult.

Thanks,
Cham



On Wed, Jun 24, 2020 at 10:32 AM Boyuan Zhang  wrote:

> Hi Ismael,
>
> I think the ReadAll in the IO connector refers to the IO with SDF
> implementation despite the type of input, where Read refers to
> UnboundedSource.  One major pushback of using KafkaIO.Read as source
> description is that not all configurations of KafkaIO.Read are meaningful
> to populate during execution time. Also when thinking about x-lang useage,
> making source description across language boundaries is also necessary.  As
> Luke mentioned, it's quite easy to infer a Schema from an AutoValue object:
> KafkaSourceDescription.java
> .
> Then the coder of this schema-aware object will be a SchemaCoder
> .
> When crossing language boundaries, it's also easy to convert a Row into the
> source description: Convert.fromRows
> 
> .
>
>
> On Wed, Jun 24, 2020 at 9:51 AM Luke Cwik  wrote:
>
>> To provide additional context, the KafkaIO ReadAll transform takes a
>> PCollection. This KafkaSourceDescriptor is a POJO
>> that contains the configurable parameters for reading from Kafka. This is
>> different from the pattern that Ismael listed because they take
>> PCollection as input and the Read is the same as the Read PTransform
>> class used for the non read all case.
>>
>> The KafkaSourceDescriptor does lead to duplication since parameters used
>> to configure the transform have to be copied over to the source descriptor
>> but decouples how a transform is specified from the object that describes
>> what needs to be done. I believe Ismael's point is that we wouldn't need
>> such a decoupling.
>>
>> Another area that hasn't been discussed and I believe is a non-issue is
>> that the Beam Java SDK has the most IO connectors and we would want to use
>> the IO implementations within Beam Go and Beam Python. This brings in its
>> own set of issues related to versioning and compatibility for the wire
>> format and how one parameterizes such transforms. The wire format issue can
>> be solved with either approach by making sure that the cross language
>> expansion always takes the well known format (whatever it may be) and
>> converts it into Read/KafkaSourceDescriptor/... object that is then passed
>> to the ReadAll transform. Boyuan has been looking to make the
>> KafkaSourceDescriptor have a schema so it can be represented as a row and
>> this can be done easily using the AutoValue integration (I don't believe
>> there is anything preventing someone from writing a schema row -> Read ->
>> row adapter or also using the AutoValue configuration if the transform is
>> also an AutoValue).
>>
>> I would be more for the code duplication and separation of concerns
>> provided by using a different object to represent the contents of the
>> PCollection from the pipeline construction time PTransform.
>>
>> On Wed, Jun 24, 2020 at 9:09 AM Eugene Kirpichov 
>> wrote:
>>
>>> Hi Ismael,
>>>
>>> Thanks for taking this on. Have you considered an approach similar (or
>>> dual) to FileIO.write(), where we in a sense also have to configure a
>>> dynamic number different IO transforms of the same type (file writes)?
>>>
>>> E.g. how in this example we configure many aspects of many file writes:
>>>
>>> transactions.apply(FileIO.writeDynamic()
>>>  .by(Transaction::getType)
>>>  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
>>> written to CSVSink
>>>   type -> new CSVSink(type.getFieldNames()))
>>>  .to(".../path/to/")
>>>  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));
>>>
>>> we could do something similar for many JdbcIO reads:
>>>
>>> PCollection bars;  // user-specific type from which all the read
>>> parameters can be inferred
>>> PCollection moos = bars.apply(JdbcIO.readAll()
>>>   .fromQuery(bar -> ...compute query for this 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Boyuan Zhang]

Hi Ismael,

I think the ReadAll in the IO connector refers to the IO with SDF
implementation despite the type of input, where Read refers to
UnboundedSource.  One major pushback of using KafkaIO.Read as source
description is that not all configurations of KafkaIO.Read are meaningful
to populate during execution time. Also when thinking about x-lang useage,
making source description across language boundaries is also necessary.  As
Luke mentioned, it's quite easy to infer a Schema from an AutoValue object:
KafkaSourceDescription.java
.
Then the coder of this schema-aware object will be a SchemaCoder
.
When crossing language boundaries, it's also easy to convert a Row into the
source description: Convert.fromRows

.


On Wed, Jun 24, 2020 at 9:51 AM Luke Cwik  wrote:

> To provide additional context, the KafkaIO ReadAll transform takes a
> PCollection. This KafkaSourceDescriptor is a POJO
> that contains the configurable parameters for reading from Kafka. This is
> different from the pattern that Ismael listed because they take
> PCollection as input and the Read is the same as the Read PTransform
> class used for the non read all case.
>
> The KafkaSourceDescriptor does lead to duplication since parameters used
> to configure the transform have to be copied over to the source descriptor
> but decouples how a transform is specified from the object that describes
> what needs to be done. I believe Ismael's point is that we wouldn't need
> such a decoupling.
>
> Another area that hasn't been discussed and I believe is a non-issue is
> that the Beam Java SDK has the most IO connectors and we would want to use
> the IO implementations within Beam Go and Beam Python. This brings in its
> own set of issues related to versioning and compatibility for the wire
> format and how one parameterizes such transforms. The wire format issue can
> be solved with either approach by making sure that the cross language
> expansion always takes the well known format (whatever it may be) and
> converts it into Read/KafkaSourceDescriptor/... object that is then passed
> to the ReadAll transform. Boyuan has been looking to make the
> KafkaSourceDescriptor have a schema so it can be represented as a row and
> this can be done easily using the AutoValue integration (I don't believe
> there is anything preventing someone from writing a schema row -> Read ->
> row adapter or also using the AutoValue configuration if the transform is
> also an AutoValue).
>
> I would be more for the code duplication and separation of concerns
> provided by using a different object to represent the contents of the
> PCollection from the pipeline construction time PTransform.
>
> On Wed, Jun 24, 2020 at 9:09 AM Eugene Kirpichov 
> wrote:
>
>> Hi Ismael,
>>
>> Thanks for taking this on. Have you considered an approach similar (or
>> dual) to FileIO.write(), where we in a sense also have to configure a
>> dynamic number different IO transforms of the same type (file writes)?
>>
>> E.g. how in this example we configure many aspects of many file writes:
>>
>> transactions.apply(FileIO.writeDynamic()
>>  .by(Transaction::getType)
>>  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
>> written to CSVSink
>>   type -> new CSVSink(type.getFieldNames()))
>>  .to(".../path/to/")
>>  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));
>>
>> we could do something similar for many JdbcIO reads:
>>
>> PCollection bars;  // user-specific type from which all the read
>> parameters can be inferred
>> PCollection moos = bars.apply(JdbcIO.readAll()
>>   .fromQuery(bar -> ...compute query for this bar...)
>>   .withMapper((bar, resultSet) -> new Moo(...))
>>   .withBatchSize(bar -> ...compute batch size for this bar...)
>>   ...etc);
>>
>>
>> On Wed, Jun 24, 2020 at 6:53 AM Ismaël Mejía  wrote:
>>
>>> Hello,
>>>
>>> (my excuses for the long email but this requires context)
>>>
>>> As part of the move from Source based IOs to DoFn based ones. One pattern
>>> emerged due to the composable nature of DoFn. The idea is to have a
>>> different
>>> kind of composable reads where we take a PCollection of different sorts
>>> of
>>> intermediate specifications e.g. tables, queries, etc, for example:
>>>
>>> JdbcIO:
>>> ReadAll extends
>>> PTransform, PCollection>
>>>
>>> RedisIO:
>>> ReadAll extends PTransform, PCollection>> String>>>
>>>
>>> HBaseIO:
>>> ReadAll extends PTransform, PCollection>
>>>
>>> These patterns enabled richer use cases like doing multiple queries in
>>> the same
>>> Pipeline, querying based on key patterns or 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Luke Cwik]

To provide additional context, the KafkaIO ReadAll transform takes a
PCollection. This KafkaSourceDescriptor is a POJO
that contains the configurable parameters for reading from Kafka. This is
different from the pattern that Ismael listed because they take
PCollection as input and the Read is the same as the Read PTransform
class used for the non read all case.

The KafkaSourceDescriptor does lead to duplication since parameters used to
configure the transform have to be copied over to the source descriptor but
decouples how a transform is specified from the object that describes what
needs to be done. I believe Ismael's point is that we wouldn't need such a
decoupling.

Another area that hasn't been discussed and I believe is a non-issue is
that the Beam Java SDK has the most IO connectors and we would want to use
the IO implementations within Beam Go and Beam Python. This brings in its
own set of issues related to versioning and compatibility for the wire
format and how one parameterizes such transforms. The wire format issue can
be solved with either approach by making sure that the cross language
expansion always takes the well known format (whatever it may be) and
converts it into Read/KafkaSourceDescriptor/... object that is then passed
to the ReadAll transform. Boyuan has been looking to make the
KafkaSourceDescriptor have a schema so it can be represented as a row and
this can be done easily using the AutoValue integration (I don't believe
there is anything preventing someone from writing a schema row -> Read ->
row adapter or also using the AutoValue configuration if the transform is
also an AutoValue).

I would be more for the code duplication and separation of concerns
provided by using a different object to represent the contents of the
PCollection from the pipeline construction time PTransform.

On Wed, Jun 24, 2020 at 9:09 AM Eugene Kirpichov 
wrote:

> Hi Ismael,
>
> Thanks for taking this on. Have you considered an approach similar (or
> dual) to FileIO.write(), where we in a sense also have to configure a
> dynamic number different IO transforms of the same type (file writes)?
>
> E.g. how in this example we configure many aspects of many file writes:
>
> transactions.apply(FileIO.writeDynamic()
>  .by(Transaction::getType)
>  .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
> written to CSVSink
>   type -> new CSVSink(type.getFieldNames()))
>  .to(".../path/to/")
>  .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));
>
> we could do something similar for many JdbcIO reads:
>
> PCollection bars;  // user-specific type from which all the read
> parameters can be inferred
> PCollection moos = bars.apply(JdbcIO.readAll()
>   .fromQuery(bar -> ...compute query for this bar...)
>   .withMapper((bar, resultSet) -> new Moo(...))
>   .withBatchSize(bar -> ...compute batch size for this bar...)
>   ...etc);
>
>
> On Wed, Jun 24, 2020 at 6:53 AM Ismaël Mejía  wrote:
>
>> Hello,
>>
>> (my excuses for the long email but this requires context)
>>
>> As part of the move from Source based IOs to DoFn based ones. One pattern
>> emerged due to the composable nature of DoFn. The idea is to have a
>> different
>> kind of composable reads where we take a PCollection of different sorts of
>> intermediate specifications e.g. tables, queries, etc, for example:
>>
>> JdbcIO:
>> ReadAll extends
>> PTransform, PCollection>
>>
>> RedisIO:
>> ReadAll extends PTransform, PCollection> String>>>
>>
>> HBaseIO:
>> ReadAll extends PTransform, PCollection>
>>
>> These patterns enabled richer use cases like doing multiple queries in
>> the same
>> Pipeline, querying based on key patterns or querying from multiple tables
>> at the
>> same time but came with some maintenance issues:
>>
>> - We ended up needing to add to the ReadAll transforms the parameters for
>>   missing information so we ended up with lots of duplicated with methods
>> and
>>   error-prone code from the Read transforms into the ReadAll transforms.
>>
>> - When you require new parameters you have to expand the input parameters
>> of the
>>   intermediary specification into something that resembles the full `Read`
>>   definition for example imagine you want to read from multiple tables or
>>   servers as part of the same pipeline but this was not in the
>> intermediate
>>   specification you end up adding those extra methods (duplicating more
>> code)
>>   just o get close to the be like the Read full spec.
>>
>> - If new parameters are added to the Read method we end up adding them
>>   systematically to the ReadAll transform too so they are taken into
>> account.
>>
>> Due to these issues I recently did a change to test a new approach that is
>> simpler, more complete and maintainable. The code became:
>>
>> HBaseIO:
>> ReadAll extends PTransform, PCollection>
>>
>> With this approach users gain benefits of improvements on parameters of
>> normal
>> Read because they count with the full Read 

Re: [DISCUSS] ReadAll pattern and consistent use in IO connectors

[Eugene Kirpichov]

Hi Ismael,

Thanks for taking this on. Have you considered an approach similar (or
dual) to FileIO.write(), where we in a sense also have to configure a
dynamic number different IO transforms of the same type (file writes)?

E.g. how in this example we configure many aspects of many file writes:

transactions.apply(FileIO.writeDynamic()
 .by(Transaction::getType)
 .via(tx -> tx.getType().toFields(tx),  // Convert the data to be
written to CSVSink
  type -> new CSVSink(type.getFieldNames()))
 .to(".../path/to/")
 .withNaming(type -> defaultNaming(type + "-transactions", ".csv"));

we could do something similar for many JdbcIO reads:

PCollection bars;  // user-specific type from which all the read
parameters can be inferred
PCollection moos = bars.apply(JdbcIO.readAll()
  .fromQuery(bar -> ...compute query for this bar...)
  .withMapper((bar, resultSet) -> new Moo(...))
  .withBatchSize(bar -> ...compute batch size for this bar...)
  ...etc);


On Wed, Jun 24, 2020 at 6:53 AM Ismaël Mejía  wrote:

> Hello,
>
> (my excuses for the long email but this requires context)
>
> As part of the move from Source based IOs to DoFn based ones. One pattern
> emerged due to the composable nature of DoFn. The idea is to have a
> different
> kind of composable reads where we take a PCollection of different sorts of
> intermediate specifications e.g. tables, queries, etc, for example:
>
> JdbcIO:
> ReadAll extends
> PTransform, PCollection>
>
> RedisIO:
> ReadAll extends PTransform, PCollection String>>>
>
> HBaseIO:
> ReadAll extends PTransform, PCollection>
>
> These patterns enabled richer use cases like doing multiple queries in the
> same
> Pipeline, querying based on key patterns or querying from multiple tables
> at the
> same time but came with some maintenance issues:
>
> - We ended up needing to add to the ReadAll transforms the parameters for
>   missing information so we ended up with lots of duplicated with methods
> and
>   error-prone code from the Read transforms into the ReadAll transforms.
>
> - When you require new parameters you have to expand the input parameters
> of the
>   intermediary specification into something that resembles the full `Read`
>   definition for example imagine you want to read from multiple tables or
>   servers as part of the same pipeline but this was not in the intermediate
>   specification you end up adding those extra methods (duplicating more
> code)
>   just o get close to the be like the Read full spec.
>
> - If new parameters are added to the Read method we end up adding them
>   systematically to the ReadAll transform too so they are taken into
> account.
>
> Due to these issues I recently did a change to test a new approach that is
> simpler, more complete and maintainable. The code became:
>
> HBaseIO:
> ReadAll extends PTransform, PCollection>
>
> With this approach users gain benefits of improvements on parameters of
> normal
> Read because they count with the full Read parameters. But of course there
> are
> some minor caveats:
>
> 1. You need to push some information into normal Reads for example
>partition boundaries information or Restriction information (in the SDF
>case).  Notice that this consistent approach of ReadAll produces a
> simple
>pattern that ends up being almost reusable between IOs (e.g. the
> non-SDF
>case):
>
>   public static class ReadAll extends PTransform,
> PCollection> {
> @Override
> public PCollection expand(PCollection input) {
>   return input
>   .apply("Split", ParDo.of(new SplitFn()))
>   .apply("Reshuffle", Reshuffle.viaRandomKey())
>   .apply("Read", ParDo.of(new ReadFn()));
> }
>   }
>
> 2. If you are using Generic types for the results ReadAll you must have the
>Coders used in its definition and require consistent types from the data
>sources, in practice this means we need to add extra withCoder
> method(s) on
>ReadAll but not the full specs.
>
>
> At the moment HBaseIO and SolrIO already follow this ReadAll pattern.
> RedisIO
> and CassandraIO have already WIP PRs to do so. So I wanted to bring this
> subject
> to the mailing list to see your opinions, and if you see any sort of
> issues that
> we might be missing with this idea.
>
> Also I would like to see if we have consensus to start using consistently
> the
> terminology of ReadAll transforms based on Read and the readAll() method
> for new
> IOs (at this point probably outdoing this in the only remaining
> inconsistent
> place in JdbcIO might not be a good idea but apart of this we should be
> ok).
>
> I mention this because the recent PR on KafkaIO based on SDF is doing
> something
> similar to the old pattern but being called ReadAll and maybe it is worth
> to be
> consistent for the benefit of users.
>
> Regards,
> Ismaël
>