Hi, I actually also made a PR for this myself the other day, but forgot to update this thread, sorry :-| https://github.com/apache/beam/pull/3891 I also hit this conversion issue, and it is intended behavior because TableRow is the JSON representation of the data, and it matches what BigQuery does when exporting to JSON format: it converts numbers to STRING. Yes, some tests were incorrect.
On Mon, Sep 25, 2017 at 7:13 AM Steve Niemitz <[email protected]> wrote: > I've just about got something to send for a PR, I'll push it shortly. > > One thing I noticed though while running the BigQueryIO unit tests that I > found strange. > It looks like currently the TableRow / Avro / TableRowJsonCoder interaction > changes BigQuery INTEGERs to strings in the public interface. eg > TableRow.get("someInteger") returns a string, not a long. The strange > thing is some unit tests do not mimic this behavior. For > example testBigQueryTableSourceInitSplit asserts that the long values exist > in the result set, not the string versions. On the other > hand, testValidateReadSetsDefaultProject gets the value as a String and > converts it to a Long. > > It seems like the behavior to convert to strings is intended, and the unit > tests are incorrect? Can anyone confirm? > > On Thu, Sep 14, 2017 at 5:31 PM, Steve Niemitz <[email protected]> > wrote: > > > Cool, thanks for the shove in the right direction! > > > > I'll probably have some more time to spend on this early next week, > > hopefully I'll have a PR to submit after that. :) > > > > On Thu, Sep 14, 2017 at 4:37 PM, Eugene Kirpichov < > > [email protected]> wrote: > > > >> On Thu, Sep 14, 2017 at 1:10 PM Steve Niemitz <[email protected]> > >> wrote: > >> > >> > I spent a little time trying to refactor it yesterday, but ran into a > >> > couple tricky points: > >> > > >> > - The BigQuerySource implementation's non-split version (mentioned > >> above) > >> > doesn't read from avro files and this would be pretty difficult to > >> "fake" > >> > into GenericRecords. It sounds like this could just be dropped > >> completely > >> > from what was mentioned previously though. > >> > > >> Agreed. This would be a very welcome contribution. > >> > >> > >> > > >> > - A user-provided SerializableFunction<GenericRecord, T> seems like > >> the a > >> > good route to providing an extension point (which could be passed > >> directly > >> > to the AvroSource used to read the files), but a) goes against the > >> > PTransform style guide, and b) is tricky to shoehorn into the current > >> > implementation, due to the existing tight coupling of the > GenericRecord > >> -> > >> > TableRow transform and the rest of BigQuerySource. > >> > > >> If we create a version of BigQueryIO that goes through GenericRecord, > then > >> providing a SerializableFunction<GenericRecord, T> will be reasonable, > >> and > >> not against the PT Style Guide, because GenericRecord is not encodable > >> unless you know the schema, which in case of reading from BigQuery you > >> don't. > >> > >> > >> > > >> > - I feel like the ideal solution would really be to provide a coder > for > >> > GenericRecord, and allow anyone to hook up a MapElements to the output > >> of a > >> > BigQueryIO that produces them. However, the fact that GenericRecord > >> > bundles the avro schema along with the object means every record > >> serialized > >> > would need to also include the full schema. I was playing around with > >> ways > >> > to possibly memoize the schema so it doesn't need to be serialized for > >> each > >> > record, but I'm not familiar enough with the guarantees a Coder is > >> provided > >> > to know if its safe to do. > >> > > >> I suggest to not spend time looking in this direction - I think it's > >> impossible to provide a Coder for GenericRecord with the current Coder > API > >> [changing the Coder API may be possible, but it would be a huge > >> undertaking]. A SerializableFunction is a reasonable way to go. > >> > >> > >> > > >> > I hope to have something concrete soon as an example, but in the mean > >> time > >> > I'm interested to hear other people's thoughts on the above. > >> > > >> > > >> > On Thu, Sep 14, 2017 at 3:29 PM, Eugene Kirpichov < > >> > [email protected]> wrote: > >> > > >> > > Oh, I see what you mean. Yeah, I agree that having BigQueryIO use > >> > TableRow > >> > > as the native format was a suboptimal decision in retrospect, and I > >> agree > >> > > that it would be reasonable to provide ability to go through Avro > >> > > GenericRecord instead. I'm just not sure how to provide it in an > >> > > API-compatible way - that would be particularly challenging since > >> > > BigQueryIO is a beast in terms of amount of code and intermediate > >> > > transforms involved. But if you have ideas, they would be welcome. > >> > > > >> > > On Sat, Sep 9, 2017 at 11:18 AM Steve Niemitz <[email protected]> > >> > wrote: > >> > > > >> > > > Ah that makes sense wrt splitting, but is indeed confusing! > Thanks > >> for > >> > > the > >> > > > explanation. :) > >> > > > > >> > > > wrt native types and TableRow, I understand your point, but could > >> also > >> > > > argue that the raw avro records are just as "native" to the > BigQuery > >> > > > connector as the TableRow JSON objects, since both are directly > >> exposed > >> > > by > >> > > > BigQuery. > >> > > > > >> > > > Maybe my use-case is more specialized, but I already have a good > >> amount > >> > > of > >> > > > code that I used pre-Beam to process BigQuery avro extract files, > >> and > >> > > avro > >> > > > is significantly smaller and more performant than JSON, which is > why > >> > I'm > >> > > > using it rather than just using TableRows. > >> > > > > >> > > > In any case, if there's no desire for such a feature I can always > >> > > replicate > >> > > > the functionality of BigQueryIO in my own codebase, so it's not a > >> big > >> > > deal, > >> > > > it just seems like a feature that would be useful for other people > >> as > >> > > well. > >> > > > > >> > > > On Sat, Sep 9, 2017 at 1:55 PM, Reuven Lax > <[email protected] > >> > > >> > > > wrote: > >> > > > > >> > > > > On Sat, Sep 9, 2017 at 10:53 AM, Eugene Kirpichov < > >> > > > > [email protected]> wrote: > >> > > > > > >> > > > > > This is a bit confusing - BigQueryQuerySource and > >> > BigQueryTableSource > >> > > > > > indeed use the REST API to read rows if you read them unsplit > - > >> > > > however, > >> > > > > in > >> > > > > > split() they run extract jobs and produce a bunch of Avro > >> sources > >> > > that > >> > > > > are > >> > > > > > read in parallel. I'm not sure we have any use cases for > reading > >> > them > >> > > > > > unsplit (except unit tests) - perhaps that code path can be > >> > removed? > >> > > > > > > >> > > > > > >> > > > > I believe split() will always be called in production. Maybe not > >> in > >> > > unit > >> > > > > tests? > >> > > > > > >> > > > > > >> > > > > > > >> > > > > > About outputting non-TableRow: per > >> > > > > > https://beam.apache.org/contribute/ptransform-style- > >> > > > > > guide/#choosing-types-of-input-and-output-pcollections, > >> > > > > > it is recommended to output the native type of the connector, > >> > unless > >> > > > it's > >> > > > > > impossible to provide a coder for it. This is the case for > >> > > > > > AvroIO.parseGenericRecords, but it's not the case for > TableRow, > >> so > >> > I > >> > > > > would > >> > > > > > recommend against it: you can always map a TableRow to > something > >> > else > >> > > > > using > >> > > > > > MapElements. > >> > > > > > > >> > > > > > On Sat, Sep 9, 2017 at 10:37 AM Reuven Lax > >> > <[email protected] > >> > > > > >> > > > > > wrote: > >> > > > > > > >> > > > > > > Hi Steve, > >> > > > > > > > >> > > > > > > The BigQuery source should always uses extract jobs, > >> regardless > >> > of > >> > > > > > > withTemplateCompatibility. What makes you think otherwise? > >> > > > > > > > >> > > > > > > Reuven > >> > > > > > > > >> > > > > > > > >> > > > > > > On Sat, Sep 9, 2017 at 9:35 AM, Steve Niemitz < > >> > [email protected] > >> > > > > >> > > > > > wrote: > >> > > > > > > > >> > > > > > > > Hello! > >> > > > > > > > > >> > > > > > > > Until now I've been using a custom-built alternative to > >> > > > > BigQueryIO.Read > >> > > > > > > > that manually runs a BigQuery extract job (to avro), then > >> uses > >> > > > > > > > AvroIO.parseGenericRecords() to read the output. > >> > > > > > > > > >> > > > > > > > I'm investigating instead enhancing the actual > >> BigQueryIO.Read > >> > to > >> > > > > allow > >> > > > > > > > something similar, since it appears a good amount of the > >> > plumbing > >> > > > is > >> > > > > > > > already in place to do this. However I'm confused at some > >> of > >> > the > >> > > > > > > > implementation details. > >> > > > > > > > > >> > > > > > > > To start, it seems like there's two different read paths: > >> > > > > > > > - If "withTemplateCompatibility" is set, a similar method > to > >> > > what I > >> > > > > > > > described above is used; an extract job is started to > >> export to > >> > > > avro, > >> > > > > > and > >> > > > > > > > AvroSource is used to read files and transform them into > >> > > TableRows. > >> > > > > > > > > >> > > > > > > > - However, if not set, the BigQueryReader class simply > uses > >> the > >> > > > REST > >> > > > > > API > >> > > > > > > to > >> > > > > > > > read rows from the tables. This method, I've seen in > >> practice, > >> > > has > >> > > > > > some > >> > > > > > > > significant performance limitations. > >> > > > > > > > > >> > > > > > > > It seems to me that for large tables, I'd always want to > use > >> > the > >> > > > > first > >> > > > > > > > method, however I'm not sure why the implementation is > tied > >> to > >> > > the > >> > > > > > oddly > >> > > > > > > > named "withTemplateCompatibility" option. Does anyone > have > >> > > insight > >> > > > > as > >> > > > > > to > >> > > > > > > > the implementation details here? > >> > > > > > > > > >> > > > > > > > Additionally, would the community in general be accepting > to > >> > > > > > enhancements > >> > > > > > > > to BigQueryIO to allow the final output to be something > >> other > >> > > than > >> > > > > > > > "TableRow" instances, similar to how > >> AvroIO.parseGenericRecords > >> > > > > takes a > >> > > > > > > > parseFn? > >> > > > > > > > > >> > > > > > > > Thanks! > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > > > > >
