On Wed, Feb 3, 2021 at 12:34 PM Kyle Weaver <kcwea...@google.com> wrote:
> Hi Beamers, > > Recently we’ve had some requests on user@ and Slack for instructions on > how to use custom-built containers in cross-language pipelines (typically > calling Java transforms from a predominantly Python pipeline). Currently, > it seems like there is no way to change the container used by a > cross-language transform except by modifying and rebuilding the expansion > service. The SDK does not pass pipeline options to the expansion service > (BEAM-9449 [1]). Fixing BEAM-9449 does not solve everything, however. Even > if pipeline options are passed, the existing set of pipeline options still > limits the amount of control we have over environments. Here are the > existing pipeline options that I’m aware of: > > Python [2] and Go [3] have these: > > - > > environment_type (DOCKER, PROCESS, LOOPBACK) > - > > environment_config (This one is confusingly overloaded. It’s a string > that means different things depending on environment_type. For DOCKER, it > is the Docker image URL. For PROCESS it is a JSON blob. For EXTERNAL, it is > the external service address.) > > > Whereas Java [4] has defaultEnvironmentType and defaultEnvironmentConfig, > which are named differently but otherwise act the same as the above. > > I was unsatisfied with environment_config for a number of reasons. First, > having a single overloaded option that can mean entirely different things > depending on context is poor design. Second, in PROCESS mode, requiring the > user to type in a JSON blob for environment_config is not especially > human-friendly (though it has also been argued that JSON makes complex > arguments like this easier to parse). Finally, we must overload this string > further to introduce new environment-specific options, such as a mounted > Docker volume (BEAM-5440 [5]). > Agree. > > To address these problems, I added a new option called > “environment_options” (BEAM-10671 [6]). (This option has been implemented > in the Python SDK, but not the other SDKs yet.) Environment_options, > similar to the “experiments” option, takes a list of strings, for example > “--environment_option=docker_container_image=my_beam_sdk:latest”. It could > be argued we should have made “docker_container_image” etc. top-level > options instead, but this “catch-all” design makes what I am about to > propose a lot easier. > > The solution proposed in PR #11638 [7] set a flag to include unrecognized > pipeline options during serialization, since otherwise unrecognized options > are dropped. In a Python pipeline, this will allow us to set > environment_config and default_environment_config to separate values, for > Python and Java containers, respectively. However, this still limits us to > one container image for all Python and Go transforms, and one container > image for all Java transforms. As more cross-language transforms are > implemented, sooner or later someone will want to have different Java SDK > containers for different external transforms. > > (I should also mention the sdk_harness_container_image_overrides pipeline > option [8], which is currently only supported by the Dataflow runner. It > lets us basically perform a find/replace on container image strings. This > is not significantly more flexible than having a single option per SDK, > since the default container images for all external transforms in each SDK > are expected to be the same.) > > Environments logically belong with transforms, and that’s how it works in > the Runner API [9]. The problem now is that from the user’s perspective, > the environment is bound to the expansion service. After addressing > BEAM-9449, the problem will be that one or two environments at most are > bound to the pipeline. Ideally, though, users should have fully granular > control over environments at the transform level. > > All this context for a very simple proposal: we should have all > ExternalTransform subclasses take optional environment_type and > environment_options fields in their constructors. As with their > corresponding pipeline options, these options would default to DOCKER and > none, respectively. Then we could overwrite the environment_type and > environment_options in the pipeline options passed to the expansion service > with these values. (Alternatively, we could pass environment_type and > environment_options to the expansion service individually to avoid having > to overwrite their original values, but their original values should be > irrelevant to the expansion service anyway.) > > What do you think? > So, an external transform is uniquely identified by its URN. An external transform identified by a URN may refer to an arbitrary composite which may have sub-transforms that refer to different environments. I think with the above proposal we'll lose this flexibility. What we need is a way to override environments (or properties of environments) that results in the final pipeline proto. Once we modify such environments in the proto it will be reflected to all transforms that utilize such environments. 'sdk_harness_container_image_overrides' is such a property (which unfortunately only works for Dataflow today). Also this only works for Docker URLs. Maybe we can extend this property to all runners or introduce a new property that works for all types of environments ? Thanks, Cham > > [1] https://issues.apache.org/jira/browse/BEAM-9449 > > [2] > https://github.com/apache/beam/blob/f2c9b6e1aa5d38385f4c168107c85d4fe7f0f259/sdks/python/apache_beam/options/pipeline_options.py#L1097-L1115 > > [3] > https://github.com/apache/beam/blob/b56b61a9a6401271f14746000ecc38b17aab753d/sdks/go/pkg/beam/options/jobopts/options.go#L41-L53 > > [4] > https://github.com/apache/beam/blob/b56b61a9a6401271f14746000ecc38b17aab753d/sdks/java/core/src/main/java/org/apache/beam/sdk/options/PortablePipelineOptions.java#L53-L71 > > [5] https://issues.apache.org/jira/browse/BEAM-5440 > > [6] https://issues.apache.org/jira/browse/BEAM-10671 > > [7] https://github.com/apache/beam/pull/11638 > > [8] > https://github.com/apache/beam/blob/f2c9b6e1aa5d38385f4c168107c85d4fe7f0f259/sdks/python/apache_beam/options/pipeline_options.py#L840-L850 > > [9] > https://github.com/apache/beam/blob/b56b61a9a6401271f14746000ecc38b17aab753d/model/pipeline/src/main/proto/beam_runner_api.proto#L194 > >
