Debugging Remote Cache Hits for Remote Execution
This page describes how to check your cache hit rate and how to investigate cache misses in the context of remote execution.
This page assumes that you have a build and/or test that successfully utilizes remote execution, and you want to ensure that you are effectively utilizing remote cache.
Checking your cache hit rate
In the standard output of your Bazel run, look at the
INFO line that lists
processes, which roughly correspond to Bazel actions. That line details
where the action was run. Look for the
remote label, which indicates an action
linux-sandbox for actions executed in a local sandbox,
and other values for other execution strategies. An action whose result came
from a remote cache is displayed as
remote cache hit.
INFO: 7 processes: 3 remote cache hit, 4 remote.
In this example there were 3 remote cache hits, and 4 actions did not have
cache hits and were executed remotely. Local cache hits are not included in this
summary. If you are getting 0 processes (or a number lower than expected),
bazel clean followed by your build/test command.
Troubleshooting cache hits
If you are not getting the cache hit rate you are expecting, do the following:
Ensure re-running the same build/test command produces cache hits.
Run the build(s) and/or test(s) that you expect to populate the cache. The first time a new build is run on a particular stack, we expect no remote cache hits. As part of remote execution, action results are stored in the cache and a subsequent run should pick them up.
bazel clean. This command cleans your local cache, which allows you to investigate remote cache hits without the results being masked by local cache hits.
Run the build(s) and test(s) that you are investigating again (on the same machine).
INFOline for cache hit rate. If you see no processes except
remote cache hit, then your cache is being correctly populated and accessed. In that case, skip to the next section.
A likely source of discrepancy is something non-hermetic in the build causing the actions to receive different action keys across the two runs. To find those actions, do the following:
a. Re-run the build(s) or test(s) in question to obtain execution logs:
bazel clean bazel $YOUR_FLAGS build //your:target --experimental_execution_log_file=/tmp/exec1.log bazel clean bazel $YOUR_FLAGS build //your:target --experimental_execution_log_file=/tmp/exec2.log
b. Compare the execution logs between the two runs. Ensure that the actions are identical across the two log files. Discrepancies provide a clue about the changes that occurred between the runs. Update your build to eliminate those discrepancies.
If you are able to resolve the caching problems and now the repeated run produces all cache hits, skip to the next section.
If your action IDs are identical but there are no cache hits, then something in your configuration is preventing caching. Continue with this section to check for common problems.
Check that all actions in the execution log have
cacheableset to true. If
cacheabledoes not appear in the execution log for a give action, that means that the corresponding rule may have a
no-cachetag in its definition in the
BUILDfile. Look at the human-readable
progress_messagefield in the execution log to help determine where the action is coming from.
If the actions are identical and
cacheablebut there are no cache hits, it is possible that your command line includes
--noremote_accept_cachedwhich would disable cache lookups for a build.
If figuring out the actual command line is difficult, use the canonical command line from the Build Event Protocol as follows:
--build_event_text_file=/tmp/bep.txtto your Bazel command to get the text version of the log.
b. Open the text version of the log and search for the
command_line_label: "canonical". It will list all the options after expansion.
c. Search for
remote_accept_cachedand check whether it’s set to
false, determine where it is being set to
false: either at the command line or in a bazelrc file.
Ensure caching across machines
After cache hits are happening as expected on the same machine, run the same build(s)/test(s) on a different machine. If you suspect that caching is not happening across machines, do the following:
Make a small modification to your build to avoid hitting existing caches.
Run the build on the first machine:
bazel clean bazel ... build ... --experimental_execution_log_file=/tmp/exec1.log
Run the build on the second machine, ensuring the modification from step 1 is included:
bazel clean bazel ... build ... --experimental_execution_log_file=/tmp/exec2.log
Compare the execution logs for the two runs. If the logs are not identical, investigate your build configurations for discrepancies as well as properties from the host environment leaking into either of the builds.
Comparing the execution logs
Execution logs contain records of all actions executed during the build. For each action there is a SpawnExec element containing all of the information from the action key, Thus, if the logs are identical then so are the action cache keys.
To compare logs for two builds that are not sharing cache hits as expected, do the folowing:
Get the execution logs from each build and store them as
Download the Bazel source code and navigate to the Bazel folder by using the command below. You need the source code to parse the execution logs with the execlog parser.
git clone https://github.com/bazelbuild/bazel.git cd bazel
Use the execution log parser to convert the logs to text. The following invocation also sorts the actions in the second log to match the action order in the first log for ease of comparison.
bazel build src/tools/execlog:parser bazel-bin/src/tools/execlog/parser \ --log_path=/tmp/exec1.log \ --log_path=/tmp/exec2.log \ --output_path=/tmp/exec1.log.txt \ --output_path=/tmp/exec2.log.txt
Use your favourite text differ to diff