Multiplex Workers (experimental feature)

Multiplex Workers allow Bazel to handle multiple requests with a single worker process. For multi-threaded workers, Bazel is able to use less resources to achieve the same, or even better performance. For example, instead of having one worker process per worker, Bazel can have four multiplexed workers talking to the same worker process, which can then handle requests in parallel. For languages like Java and Scala, this saves JVM warm-up time and JIT compilation time.


Multiplex Workers Overview

We add two layers between the Bazel server and the worker process. For certain mnemonics that can run processes in parallel, Bazel gets a WorkerProxy from the worker pool. The WorkerProxy forwards requests to the worker process sequentially along with a request_id, the worker process processes the request and sends responses to the WorkerMultiplexer. When the WorkerMultiplexer receives a response, it parses the request_id and then forwards the responses back to the correct WorkerProxy. Just as with non-multiplexed workers, all communication is done over standard in/out.

Each worker has a key. Bazel uses the hash code (composed of environment variables, the execution root, and the mnemonic) of the key to determine which WorkerMultiplexer to use. WorkerProxys communicate with the same WorkerMultiplexer if they have the same hash code. Therefore, assuming environment variables and the execution root are the same in a single Bazel invocation, each unique mnemonic can only have one WorkerMultiplexer and one worker process. The total number of workers, including regular workers and WorkerProxys, is still limited by --worker_max_instances.

A Guide to Write a Multiplex-Compatible Ruleset

The rule’s worker process should be multi-threaded to take advantage of Multiplex Workers. Protobuf allows a ruleset to parse a single request even though there might be multiple requests piling up in the stream. Whenever the worker process parses a request from the stream, it should handle the request in a new thread. Since different thread could complete and write to the stream at the same time, the worker process needs to make sure the responses are written atomically (i.e. messages don’t overlap). Responses must contain the request_id of the request they’re handling.

Enable Multiplex Workers

Multiplex workers are not enabled by default. A ruleset can turn on Multiplex Workers by using the supports-multiplex-workers tag in the execution_requirements of an action (just like the supports-workers tag enables regular workers). As is the case when using regular workers, a worker strategy needs to be specified, either at the ruleset level, eg. --strategy=[some_mnemonic]=worker, or generally at the strategy level, eg. --dynamic_local_strategy=worker,standalone. No additional flags are necessary, and supports-multiplex-workers takes precedence over supports-workers, if both are set. A ruleset is encouraged to use Multiplex Workers if possible, since this will improve performance.


Due to a rare bug, Multiplex Workers are currently unstable. Occasionally, you might see Bazel hanging at the execution phase. We believe this happens because Multiplex Workers are waiting for responses from the worker process which never comes. Bazel will hang indefinitely. If you see this behavior, stop the Bazel server and rerun. It is not expected to happen often. We are actively working on a fix.

There is also a chance that the issue lies in the ruleset worker implementation. It is possible a thread dies or a race condition occurs. Make sure the worker process always returns responses in all circumstances.