Creating persistent workers
Persistent workers can make your build faster. If you have repeated actions in your build that have a high startup cost or would benefit from cross-action caching, you may want to implement your own persistent worker to perform these actions.
The worker implementation has two parts:
- The worker,
- The rule that uses the worker.
Making the worker
A worker upholds a few requirements:
- It reads WorkRequests
from its
stdin
. - It writes WorkResponses
(and only
WorkResponse
s) to itsstdout
. - It accepts the
--persistent_worker
flag.
If your program upholds these requirements, it can be used as a worker!
Work requests
A WorkRequest
contains a list of arguments to the worker, a list of path-digest
pairs representing the inputs the worker can access (this isn’t enforced, but
you can use this info for caching), and a request id, which is 0 for singleplex
workers.
{
“args” : [“--some_argument”],
“inputs” : [
{ “/path/to/my/file/1” : “fdk3e2ml23d”},
{ “/path/to/my/file/2” : “1fwqd4qdd” }
],
“request_id” : 12
}
Work responses
A WorkResponse
should contain the same request id, a zero or nonzero exit
code, and an output string that contains any errors encountered in processing
or executing the request. Workers may write additional output to stderr
, but
they must only write WorkResponse
s to stdout
.
{
“exit_code” : 1,
“output” : “Action failed with the following message:\nCould not find input
file “/path/to/my/file/1”,
“request_id” : 12
}
As per the norm for protobufs, the fields are optional. However, Bazel requires
the WorkRequest
and the corresponding WorkResponse
, to have the same request
id, so the request id must be specified if it is nonzero. This is a valid
WorkResponse
.
{
“request_id” : 12,
}
A request_id
of 0 indicates a “singleplex” request, i.e. this request cannot
be processed in parallel with other requests. The server guarantees that a
given worker receives requests with either only request_id
0 or only
request_id
greater than zero. Singleplex requests are sent in serial, i.e. the
server doesn’t send another request until it has received a response (except
for cancel requests, see below).
Notes
- Each protocol buffer is preceded by its length in
varint
format (seeMessageLite.writeDelimitedTo()
. - JSON requests and responses are not preceded by a size indicator.
- JSON requests uphold the same structure as the protobuf, but use standard JSON.
- Bazel stores requests as protobufs and converts them to JSON using protobuf’s JSON format
Cancellation
Workers can optionally allow work requests to be cancelled before they finish.
This is particularly useful in connection with dynamic execution, where local
execution can regularly be interrupted by a faster remote execution. To allow
cancellation, add supports-worker-cancellation: 1
to the
execution-requirements
field (see below) and set the
--experimental_worker_cancellation
flag.
A cancel request is a WorkRequest
with the cancel
field set (and
similarly a cancel response is a WorkResponse
with the was_cancelled
field set). The only other field that must be in a cancel request or cancel
response is request_id
, indicating which
request to cancel. The request_id
field will be 0 for singleplex workers
or the non-0 request_id
of a previously sent WorkRequest
for multiplex
workers. The server may send cancel requests for requests that the worker has
already responded to, in which case the cancel request must be ignored.
Each non-cancel WorkRequest
message must be answered exactly once, whether
or not it was cancelled. Once the server has sent a cancel request, the worker
may respond with a WorkResponse
with the request_id
set
and the was_cancelled
field set to true. Sending a regular WorkResponse
is also accepted, but the output
and exit_code
fields will be ignored.
Once a response has been sent for a WorkRequest
, the worker must not touch
the files in its working directory. The server is free to clean up the files,
including temporary files.
Making the rule that uses the worker
You’ll also need to create a rule that generates actions to be performed by the worker. Making a Starlark rule that uses a worker is just like creating any other rule.
In addition, the rule needs to contain a reference to the worker itself, and there are some requirements for the actions it produces.
Referring to the worker
The rule that uses the worker needs to contain a field that refers to the worker itself,
so you’ll need to create an instance of a \*\_binary
rule to define your
worker. If your worker is called MyWorker.Java
, this might be the associated
rule:
java_binary(
name = “worker”,
srcs = [“MyWorker.Java”],
)
This creates the “worker” label, which refers to the worker binary. You’ll then define a rule that uses the worker. This rule should define an attribute that refers to the worker binary.
If the worker binary you built is in a package named “work”, which is at the top level of the build, this might be the attribute definition:
"worker": attr.label(
default = Label("//work:worker"),
executable = True,
cfg = "host",
)
cfg = "host"
indicates that the worker should be built to run on your host
platform.
Work action requirements
The rule that uses the worker creates actions for the worker to perform. These actions have a couple of requirements.
-
The “arguments” field. This takes a list of strings, all but the last of which are arguments passed to the worker upon startup. The last element in the “arguments” list is a
flag-file
(@-preceded) argument. Workers read the arguments from the specified flagfile on a per-WorkRequest basis. Your rule can write non-startup arguments for the worker to this flagfile. -
The “execution-requirements” field, which takes a dictionary containing
“supports-workers” : “1”
,“supports-multiplex-workers” : “1”
, or both.The “arguments” and “execution-requirements” fields are required for all actions sent to workers. Additionally, actions that should be executed by JSON workers need to include
“requires-worker-protocol” : “json”
in the execution requirements field.“requires-worker-protocol” : “proto”
is also a valid execution requirement, though it’s not required for proto workers, since they are the default.You can also set a “worker-key-mnemonic” in the execution requirements. This may be useful if you’re reusing the executable for multiple action types and want to distinguish actions by this worker.
-
Temporary files generated in the course of the action should be saved to the worker’s directory. This enables sandboxing.
Assuming a rule definition with “worker” attribute described above, in addition
to a “srcs” attribute representing the inputs, an “output” attribute
representing the outputs, and an “args” attribute representing the worker
startup args, the call to ctx.actions.run
might be:
ctx.actions.run(
inputs=ctx.files.srcs,
outputs=[ctx.attr.output],
executable=ctx.attr.worker,
mnemonic="someMnemonic",
execution_requirements={
“supports-workers” : “1”,
“requires-worker-protocol” : “json},
arguments=ctx.attr.args + [“@flagfile”]
)
Examples
The Bazel code base uses Java compiler workers, in addition to an example JSON worker that is used in our integration tests.
You can use their scaffolding to make any Java-based tool into a worker by passing in the correct callback.
For an example of a rule that uses a worker, take a look at Bazel’s worker integration test.
External contributors have implemented workers in a variety of languages; you can find many more examples on GitHub!