And next issue... I'm getting KeyError: 'beam:coders:javasdk:0.1' which I learned <https://cwiki.apache.org/confluence/display/BEAM/Multi-language+Pipelines+Tips> is because the transform is trying to return something that there isn't a standard Beam coder for <https://github.com/apache/beam/blob/05428866cdbf1ea8e4c1789dd40327673fd39451/model/pipeline/src/main/proto/beam_runner_api.proto#L784> . Makes sense, but... how do I fix this? The documentation talks about how to do this for the input, but not for the output.
Comparing to Spanner, it looks like Spanner returns a protobuf, which I'm guessing somehow gets converted to bytes... But CloudBigtableIO <https://github.com/googleapis/java-bigtable-hbase/blob/main/bigtable-dataflow-parent/bigtable-hbase-beam/src/main/java/com/google/cloud/bigtable/beam/CloudBigtableIO.java> returns org.apache.hadoop.hbase.client.Result. My buildExternal method looks like follows: @Override public PTransform<PBegin, PCollection<Result>> buildExternal( BigtableReadBuilder.Configuration configuration) { return Read.from(CloudBigtableIO.read( new CloudBigtableScanConfiguration.Builder() .withProjectId(configuration.projectId) .withInstanceId(configuration.instanceId) .withTableId(configuration.tableId) .build() )); I also got a warning, which I *believe* is unrelated (but also an issue): INFO:apache_beam.utils.subprocess_server:b"WARNING: Configuration class 'energy.camus.beam.BigtableRegistrar$BigtableReadBuilder$Configuration' has no schema registered. Attempting to construct with setter approach." INFO:apache_beam.utils.subprocess_server:b'Dec 30, 2022 7:46:14 AM org.apache.beam.sdk.expansion.service.ExpansionService$ExternalTransformRegistrarLoader payloadToConfig' What is this schema and what should it look like? Thanks! -Lina On Fri, Dec 30, 2022 at 12:28 AM Lina Mårtensson <lina@camus.energy> wrote: > Thanks! This was really helpful. It took a while to figure out the details > - a section in the docs on what's required of these jars for non-Java users > would be a great addition. > > But once I did, the Bazel config was actually quite straightforward and > makes sense. > I pasted the first section from here > <https://github.com/bazelbuild/rules_jvm_external/blob/master/README.md#usage> > into > my WORKSPACE file and changed the artifacts to the ones I needed. (How to > find the right ones remains confusing.) > > After that I updated my BUILD rules and Blaze had easy and straightforward > configs for it, all I needed was this: > > # From > https://github.com/google/bazel-common/blob/master/third_party/java/auto/BUILD > . > > # The auto service is what registers our Registrar class, and it needs to > be a plugin which > > # makes it run at compile-time. > > java_plugin( > > name = "auto_service_processor", > > processor_class = > "com.google.auto.service.processor.AutoServiceProcessor", > > deps = [ > > "@maven//:com_google_auto_service_auto_service", > > "@maven//:com_google_auto_service_auto_service_annotations", > > "@maven//:org_apache_beam_beam_vendor_guava_26_0_jre", > > ], > > ) > > > java_binary( > > name = "java_hbase", > > main_class = "energy.camus.beam.BigtableRegistrar", > > plugins = [":auto_service_processor"], > > srcs = ["src/main/java/energy/camus/beam/BigtableRegistrar.java"], > > deps = [ > > "@maven//:com_google_auto_service_auto_service", > > "@maven//:com_google_auto_service_auto_service_annotations", > > > "@maven//:com_google_cloud_bigtable_bigtable_hbase_beam", > > > "@maven//:org_apache_beam_beam_sdks_java_core", > > "@maven//:org_apache_beam_beam_vendor_guava_26_0_jre", > > "@maven//:org_apache_hbase_hbase_shaded_client", > > ], > > ) > > > On Thu, Dec 29, 2022 at 2:43 PM Luke Cwik <lc...@google.com> wrote: > >> AutoService relies on Java's compiler annotation processor. >> https://github.com/google/auto/tree/main/service#getting-started shows >> that you need to configure Java's compiler to use the annotation processors >> within AutoService. >> >> I saw this public gist that seemed to enable using the AutoService >> annotation processor with Bazel >> https://gist.github.com/jart/5333824b94cd706499a7bfa1e086ee00 >> >> >> >> On Thu, Dec 29, 2022 at 2:27 PM Lina Mårtensson via dev < >> dev@beam.apache.org> wrote: >> >>> That's good news about the direct runner, thanks! >>> >>> On Thu, Dec 29, 2022 at 2:02 PM Robert Bradshaw <rober...@google.com> >>> wrote: >>> >>>> On Thu, Jul 28, 2022 at 5:37 PM Chamikara Jayalath via dev >>>> <dev@beam.apache.org> wrote: >>>> > >>>> > On Thu, Jul 28, 2022 at 4:51 PM Lina Mårtensson <lina@camus.energy> >>>> wrote: >>>> >> >>>> >> Thanks for the detailed answers! >>>> >> >>>> >> I totally get the points about development & maintenance cost, and, >>>> >> from a user perspective, about getting the performance right. >>>> >> >>>> >> I decided to try out the Spanner connector to get a sense of how well >>>> >> the x-language approach works in our world, since that's an existing >>>> >> x-language connector. >>>> >> Overall, it works and with minimal intervention as you say - it is >>>> >> very slow, though. >>>> >> I'm a little confused about "portable runners" - if I understand this >>>> >> correctly, this means we couldn't run with the DirectRunner anymore >>>> if >>>> >> using an x-language connector? (At least it didn't work when I tried >>>> >> it.) >>>> > >>>> > >>>> > You'll have to use the portable DirectRunner - >>>> https://github.com/apache/beam/tree/master/sdks/python/apache_beam/runners/portability >>>> > >>>> > Job service for this can be started using following command: >>>> > python apache_beam/runners/portability/local_job_service_main.py -p >>>> <port> >>>> >>>> Note that the Python direct runner is already a portable runner, so >>>> you shouldn't have to do anything special (like start up a separate >>>> job service and pass extra options) to run locally. Just use the >>>> cross-language transforms as you would any normal Python transform. >>>> >>>> The goal is to make this as smooth and transparent as possible; please >>>> keep coming back to us if you find rough edges. >>>> >>>
