bugbug/scripts/test_scheduling_history_ret...

350 строки
12 KiB
Python

# -*- coding: utf-8 -*-
import argparse
import json
import os
import time
import traceback
from datetime import datetime
from logging import INFO, basicConfig, getLogger
import adr
import dateutil.parser
import mozci
from dateutil.relativedelta import relativedelta
from tqdm import tqdm
from bugbug import commit_features, db, repository, test_scheduling
from bugbug.utils import (
download_check_etag,
open_tar_zst,
zstd_compress,
zstd_decompress,
)
basicConfig(level=INFO)
logger = getLogger(__name__)
JOBS_TO_CONSIDER = ("test-", "build-")
JOBS_TO_IGNORE = ("build-docker-image-",)
ADR_CACHE_DB = "data/adr_cache.tar"
db.register(
ADR_CACHE_DB,
"https://s3-us-west-2.amazonaws.com/communitytc-bugbug/data/adr_cache.tar.zst",
3,
)
PUSH_DATA_URL = "https://community-tc.services.mozilla.com/api/index/v1/task/project.relman.bugbug.data_test_scheduling_history_push_data.latest/artifacts/public/push_data_{granularity}.json.zst"
TRAINING_MONTHS = 6
def filter_runnables(runnables, all_runnables, granularity):
return tuple(
runnable
for runnable in runnables
if runnable in all_runnables
and (
granularity == "group"
or (
any(runnable.startswith(j) for j in JOBS_TO_CONSIDER)
and not any(runnable.startswith(j) for j in JOBS_TO_IGNORE)
)
)
)
# Handle "meaningless" labeling changes ("meaningless" as they shouldn't really affect test scheduling).
def rename_tasks(tasks):
return [task.replace("test-linux64-", "test-linux1804-64-") for task in tasks]
class Retriever(object):
def __init__(self):
os.makedirs("data", exist_ok=True)
self.cache_path = os.path.splitext(ADR_CACHE_DB)[0]
def generate_push_data(self, runnable, from_months):
def upload_adr_cache():
with open_tar_zst(f"{ADR_CACHE_DB}.zst") as tar:
tar.add(self.cache_path)
db.upload(ADR_CACHE_DB)
pushes = mozci.push.make_push_objects(
from_date=f"today-{from_months}month",
to_date="today-3day",
branch="autoland",
)
start_time = time.monotonic()
num_cached = 0
push_data = []
for push in tqdm(pushes):
key = f"push_data.{runnable}.{push.rev}"
logger.info(f"Analyzing {push.rev} at the {runnable} level...")
if adr.config.cache.has(key):
num_cached += 1
push_data.append(adr.config.cache.get(key))
else:
try:
if runnable == "label":
runnables = push.task_labels
elif runnable == "group":
runnables = push.group_summaries.keys()
value = [
push.revs,
list(runnables),
list(push.get_possible_regressions(runnable)),
list(push.get_likely_regressions(runnable)),
]
push_data.append(value)
adr.config.cache.forever(key, value)
except adr.errors.MissingDataError:
logger.warning(
f"Tasks for push {push.rev} can't be found on ActiveData"
)
except Exception:
traceback.print_exc()
if time.monotonic() - start_time >= 3600:
upload_adr_cache()
start_time = time.monotonic()
logger.info(f"{num_cached} pushes were already cached out of {len(pushes)}")
upload_adr_cache()
with open(f"push_data_{runnable}.json", "w") as f:
json.dump(push_data, f)
def retrieve_push_data(self):
# Download previous cache.
db.download(ADR_CACHE_DB)
# Setup adr cache configuration.
os.makedirs(os.path.expanduser("~/.config/adr"), exist_ok=True)
with open(os.path.expanduser("~/.config/adr/config.toml"), "w") as f:
f.write(
f"""[adr.cache.stores]
file = {{ driver = "file", path = "{os.path.abspath(self.cache_path)}" }}
"""
)
# We'll use the past TRAINING_MONTHS months only for training the model,
# but we use 3 months more than that to calculate the failure statistics.
self.generate_push_data("label", TRAINING_MONTHS + 3)
# For groups, we only have 12 weeks in ActiveData. Getting previous data
# from task artifacts is slow, so for now we only get what we can get from
# ActiveData and we'll see if it's enough to train a satisfying model.
self.generate_push_data("group", 3)
zstd_compress("push_data_label.json")
zstd_compress("push_data_group.json")
def generate_test_scheduling_history(self, granularity):
push_data_path = f"push_data_{granularity}.json"
updated = download_check_etag(PUSH_DATA_URL.format(granularity=granularity))
if updated:
zstd_decompress(push_data_path)
assert os.path.exists(push_data_path), "Decompressed push data file exists"
# Get the commits DB.
assert db.download(repository.COMMITS_DB)
HISTORY_DATE_START = datetime.now() - relativedelta(months=TRAINING_MONTHS)
if granularity == "label":
test_scheduling_db = test_scheduling.TEST_LABEL_SCHEDULING_DB
past_failures_db = os.path.join(
"data", test_scheduling.PAST_FAILURES_LABEL_DB
)
elif granularity == "group":
test_scheduling_db = test_scheduling.TEST_GROUP_SCHEDULING_DB
past_failures_db = os.path.join(
"data", test_scheduling.PAST_FAILURES_GROUP_DB
)
db.download(test_scheduling_db, support_files_too=True)
last_node = None
for test_data in test_scheduling.get_test_scheduling_history(granularity):
last_node = test_data["revs"][0]
def generate_all_data():
past_failures = test_scheduling.get_past_failures(granularity)
push_num = past_failures["push_num"] if "push_num" in past_failures else 0
# We can start once we get to the last revision we added in the previous run.
can_start = True if last_node is None else False
commit_map = {}
for commit_data in tqdm(repository.get_commits()):
if not can_start:
if last_node == commit_data["node"]:
can_start = True
continue
commit_map[commit_data["node"]] = commit_data
with open(push_data_path, "r") as f:
push_data = json.load(f)
logger.info(f"push data nodes: {len(push_data)}")
if granularity == "label":
push_data = [
(
revisions,
rename_tasks(push_tasks),
rename_tasks(possible_regressions),
rename_tasks(likely_regressions),
)
for revisions, push_tasks, possible_regressions, likely_regressions in push_data
]
# In the last 28 pushes, we definitely run all possible runnables.
all_runnables_set = set(
sum((push_runnables for _, push_runnables, _, _ in push_data[-28:]), [])
)
# Filter runnables we don't need.
all_runnables = filter_runnables(
list(all_runnables_set), all_runnables_set, granularity
)
all_runnables_set = set(all_runnables_set)
logger.info(f"{len(all_runnables_set)} runnables run in the last 28 pushes")
# Store all runnables in the past_failures DB so it can be used in the evaluation phase.
past_failures["all_runnables"] = all_runnables
# XXX: Should we recreate the DB from scratch if the previous all_runnables are not the
# same as the current ones?
saved_nodes = set()
skipped_no_commits = 0
skipped_too_big_commits = 0
skipped_no_runnables = 0
# We can start once we get to the last revision we added in the previous run.
can_start = True if last_node is None else False
for i in tqdm(range(len(push_data))):
(
revisions,
push_runnables,
possible_regressions,
likely_regressions,
) = push_data.pop(0)
if not can_start:
if last_node == revisions[0]:
can_start = True
continue
push_num += 1
# XXX: Some commits are skipped in the repository mining, e.g. merges and backouts. Maybe we should not skip them.
commits = tuple(
commit_map.pop(revision)
for revision in revisions
if revision in commit_map
)
if len(commits) == 0:
skipped_no_commits += 1
continue
merged_commits = commit_features.merge_commits(commits)
# XXX: For now, skip commits which are too large.
# In the future we can either:
# - Improve shelve perf and go back to consider all files;
# - Consider only files which appear with a given frequency, like the "files" feature in commit_features;
# - Keep a limit of number of files.
if len(merged_commits["files"]) > 50:
skipped_too_big_commits += 1
continue
# If we considered all_runnables, we'd generate a huge amount of data.
# So we consider only the runnables which run in this push, and the possible and likely regressions
# from this push.
runnables_to_consider = list(
set(push_runnables + possible_regressions + likely_regressions)
)
runnables_to_consider = filter_runnables(
runnables_to_consider, all_runnables_set, granularity
)
if len(runnables_to_consider) == 0:
skipped_no_runnables += 1
continue
# Sync DB every 250 pushes, so we cleanup the shelve cache (we'd run OOM otherwise!).
if i % 250 == 0:
past_failures.sync()
pushdate = dateutil.parser.parse(merged_commits["pushdate"])
for data in test_scheduling.generate_data(
past_failures,
merged_commits,
push_num,
runnables_to_consider,
possible_regressions,
likely_regressions,
):
if pushdate > HISTORY_DATE_START:
saved_nodes.add(i)
data["revs"] = revisions
yield data
logger.info(f"saved push data nodes: {len(saved_nodes)}")
logger.info(f"skipped {skipped_no_commits} (no commits in our DB)")
logger.info(f"skipped {skipped_too_big_commits} (too big commits)")
logger.info(f"skipped {skipped_no_runnables} (no interesting runnables)")
past_failures["push_num"] = push_num
past_failures.close()
db.append(test_scheduling_db, generate_all_data())
zstd_compress(test_scheduling_db)
with open_tar_zst(past_failures_db) as tar:
tar.add(past_failures_db[: -len(".tar.zst")])
def main():
description = "Retrieve and extract the test scheduling history from ActiveData"
parser = argparse.ArgumentParser(description=description)
parser.add_argument(
"op", help="Which operation to perform.", choices=["retrieve", "generate"]
)
parser.add_argument(
"--granularity",
help="Which test granularity to use.",
choices=["label", "group"],
)
args = parser.parse_args()
retriever = Retriever()
if args.op == "retrieve":
retriever.retrieve_push_data()
elif args.op == "generate":
assert args.granularity is not None
retriever.generate_test_scheduling_history(args.granularity)
if __name__ == "__main__":
main()