Multiplex Workers (Experimental Feature)

This page describes multiplex workers, how to write multiplex-compatible rules, and workarounds for certain limitations.

Caution: Experimental features are subject to change at any time.

Multiplex workers allow Bazel to handle multiple requests with a single worker process. For multi-threaded workers, Bazel can use fewer resources to achieve the same, or 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.

Overview

There are 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 key’s hash code (composed of environment variables, the execution root, and the mnemonic) 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.

Writing multiplex-compatible rules

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. Because 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.

Enabling 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 (for example, --strategy=[some_mnemonic]=worker) or generally at the strategy level (for example, --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, to reduce memory pressure and improve performance. However, multiplex workers are not currently compatible with dynamic execution.

Warning about rare bug

Due to a rare bug, multiplex workers are currently not enabled by default. Occasionally, Bazel hangs indefinitely at the execution phase. If you see this behavior, stop the Bazel server and rerun. This delay is probably caused by

• Multiplex workers waiting for responses from the worker process that never comes.
• Incorrectly configured ruleset worker implementation where a thread dies or a race condition occurs. To counteract this, ensure the worker process returns responses in all circumstances.