Execution groups allow for multiple execution platforms within a single target. Each execution group has its own toolchain dependencies and performs its own toolchain resolution.
Background
Execution groups allow the rule author to define sets of actions, each with a potentially different execution platform. Multiple execution platforms can allow actions to execution differently, for example compiling an iOS app on a remote (linux) worker and then linking/code signing on a local mac worker.
Being able to define groups of actions also helps alleviate the usage of action mnemonics as a proxy for specifying actions. Mnemonics are not guaranteed to be unique and can only reference a single action. This is especially helpful in allocating extra resources to specific memory and processing intensive actions like linking in C++ builds without over-allocating to less demanding tasks.
Defining execution groups
During rule definition, rule authors can
declare
a set of execution groups. On each execution group, the rule author can specify
everything needed to select an execution platform for that execution group,
namely any constraints via exec_compatible_with and toolchain types via
toolchain.
# foo.bzl
my_rule = rule(
_impl,
exec_groups = {
“link”: exec_group(
exec_compatible_with = [ "@platforms//os:linux" ]
toolchains = ["//foo:toolchain_type"],
),
“test”: exec_group(
toolchains = ["//foo_tools:toolchain_type"],
),
},
attrs = {
"_compiler": attr.label(cfg = config.exec("link"))
},
)
In the code snippet above, you can see that tool dependencies can also specify
transition for an exec group using the
cfg
attribute param and the
config
module. The module exposes an exec function which takes a single string
parameter which is the name of the exec group for which the dependency should be
built.
As on native rules, the test execution group is present by default on Starlark
test rules.
Accessing execution groups
In the rule implementation, you can declare that actions should be run on the
execution platform of an execution group. You can do this by using the exec_group
param of action generating methods, specifically ctx.actions.run and
ctx.actions.run_shell.
# foo.bzl
def _impl(ctx):
ctx.actions.run(
inputs = [ctx.attr._some_tool, ctx.srcs[0]]
exec_group = "compile",
# ...
)
Rule authors will also be able to access the resolved toolchains of execution groups, similarly to how you can access the resolved toolchain of a target:
# foo.bzl
def _impl(ctx):
foo_info = ctx.exec_groups["link"].toolchains["//foo:toolchain_type"].fooinfo
ctx.actions.run(
inputs = [foo_info, ctx.srcs[0]]
exec_group = "link",
# ...
)
Using execution groups to set execution properties
Execution groups are integrated with the
exec_properties
attribute that exists on every rule and allows the target writer to specify a
string dict of properties that is then passed to the execution machinery. For
example, if you wanted to set some property, say memory, for the target and give
certain actions a higher memory allocation, you would write an exec_properties
entry with an execution-group-augmented key, such as:
# BUILD
my_rule(
name = 'my_target',
exec_properties = {
'mem': '12g',
'link.mem': '16g'
}
…
)
All actions with exec_group = "link" would see the exec properties
dictionary as {"mem": "16g"}. As you see here, execution-group-level
settings override target-level settings.
Execution groups for native rules
The following execution groups are available for actions defined by native rules:
test: Test runner actions.cpp_link: C++ linking actions.
Execution groups and platform execution properties
It is possible to define exec_properties for arbitrary execution groups on
platform targets (unlike exec_properties set directly on a target, where
properties for unknown execution groups are rejected). Targets then inherit the
execution platform's exec_properties that affect the default execution group
and any other relevant execution groups.
For example, suppose running a C++ test requires some resource to be available, but it isn't required for compiling and linking; this can be modelled as follows:
constraint_setting(name = "resource")
constraint_value(name = "has_resource", constraint_setting = ":resource")
platform(
name = "platform_with_resource",
constraint_values = [":has_resource"],
exec_properties = {
"test.resource": "...",
},
)
cc_test(
name = "my_test",
srcs = ["my_test.cc"],
exec_compatible_with = [":has_resource"],
)
exec_properties defined directly on targets take precedence over those that
are inherited from the execution platform.