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. >> >
