def extend(d):
try:
db.insert_list(table_name, d)
db.flush()
Log.note("added {{num}} records", {"num":len(d)})
except Exception, e:
Log.warning("Can not inert into database", e)
def extract_from_datazilla_using_id(es, settings, transformer):
existing_ids = get_existing_ids(es, settings, transformer.pushlog.keys())
max_existing_id = nvl(MAX(existing_ids), settings.production.min)
holes = set(range(settings.production.min, max_existing_id)) - existing_ids
missing_ids = set(range(settings.production.min, max_existing_id+nvl(settings.production.step, NUM_PER_BATCH))) - existing_ids
Log.note("Number missing: {{num}}", {"num": len(missing_ids)})
Log.note("Number in holes: {{num}}", {"num": len(holes)})
#FASTER IF NO INDEXING IS ON
es.set_refresh_interval(-1)
#FILE IS FASTER THAN NETWORK
if (len(holes) > 10000 or settings.args.scan_file or settings.args.restart) and File(settings.param.output_file).exists:
#ASYNCH PUSH TO ES IN BLOCKS OF 1000
with Timer("Scan file for missing ids"):
with ThreadedQueue(es, size=nvl(es.settings.batch_size, 100)) as json_for_es:
num = 0
for line in File(settings.param.output_file):
try:
if len(line.strip()) == 0:
continue
col = line.split("\t")
id = int(col[0])
# if id==3003529:
# Log.debug()
if id < settings.production.min:
continue
if id in existing_ids:
continue
if num > settings.production.step:
return
num += 1
with Profiler("decode and transform"):
data = CNV.JSON2object(col[-1])
if data.test_run_id:
with Profiler("transform"):
data = transformer.transform(id, data)
json_for_es.extend({"value": d} for d in data)
Log.note("Added {{id}} from file", {"id": id})
existing_ids.add(id)
else:
Log.note("Skipped {{id}} from file (no test_run_id)", {"id": id})
num -= 1
except Exception, e:
Log.warning("Bad line id={{id}} ({{length}}bytes):\n\t{{prefix}}", {
"id": id,
"length": len(CNV.object2JSON(line)),
"prefix": CNV.object2JSON(line)[0:130]
}, e)
missing_ids = missing_ids - existing_ids
def arrays_add(id, path, r):
try:
if isinstance(r, dict):
for k, v in [(k, v) for k, v in r.items()]:
new_path = path + "[" + k + "]"
arrays_add(id, new_path, v)
elif isinstance(r, list):
try:
values = r.map(float)
arrays.append([id, path, len(values), 1])
except Exception, e:
for i, v in enumerate(r):
r[i] = arrays_add(id, path + "[" + str(i) + "]", v)
# return r
except Exception, e:
Log.warning("Can not summarize: {{json}}", {"json": CNV.object2JSON(r)})
def etl(es_sink, file_sink, settings, transformer, max_id, id):
"""
PULL FROM DZ AND PUSH TO es AND file_sink
"""
# DEBUG GROWTH
# with GC_LOCKER:
# try:
# if COUNTER.count % 100 == 0:
# # gc.collect()
# deltas, stats = objgraph.get_growth()
# Log.note("Deltas:\n{{deltas|indent}}", {"deltas": deltas})
# except Exception, e:
# Log.warning("objgraph problem", e)
#
# COUNTER.count += 1
url = settings.production.blob_url + "/" + str(id)
try:
with Timer("read {{id}} from DZ", {"id": id}):
content = requests.get(url, timeout=nvl(settings.production.timeout, 30)).content
except Exception, e:
Log.warning("Failure to read from {{url}}", {"url": url}, e)
return False
def transform(self, id, datazilla):
try:
r = datazilla.json_blob
#ADD DATAZILLA MARKUP
r.datazilla = {
"id": id,
"date_loaded": datazilla.date_loaded * 1000,
"error_flag": datazilla.error_flag,
"test_run_id": datazilla.test_run_id,
"processed_flag": datazilla.processed_flag,
"error_msg": datazilla.error_msg
}
#CONVERT UNIX TIMESTAMP TO MILLISECOND TIMESTAMP
r.testrun.date *= 1000
def mainthread_transform(r):
if r == None:
return None
output = Struct()
for i in r.mainthread_readbytes:
output[literal_field(i[1])].name = i[1]
output[literal_field(i[1])].readbytes = i[0]
r.mainthread_readbytes = None
for i in r.mainthread_writebytes:
output[literal_field(i[1])].name = i[1]
output[literal_field(i[1])].writebytes = i[0]
r.mainthread_writebytes = None
for i in r.mainthread_readcount:
output[literal_field(i[1])].name = i[1]
output[literal_field(i[1])].readcount = i[0]
r.mainthread_readcount = None
for i in r.mainthread_writecount:
output[literal_field(i[1])].name = i[1]
output[literal_field(i[1])].writecount = i[0]
r.mainthread_writecount = None
r.mainthread = output.values()
mainthread_transform(r.results_aux)
mainthread_transform(r.results_xperf)
#ADD PUSH LOG INFO
try:
branch = r.test_build.branch
if branch.endswith("-Non-PGO"):
r.test_build.branch = branch
r.test_build.pgo = False
branch = branch[0:-8]
else:
r.test_build.pgo = True
with Profiler("get from pushlog"):
if not self.pushlog:
#NO PUSHLOG MEANS WE DO NOTHING TO MARKUP TEST RESULTS
pass
elif self.pushlog[branch]:
possible_dates = self.pushlog[branch][r.test_build.revision]
if possible_dates:
r.test_build.push_date = int(Math.round(possible_dates[0].date * 1000))
else:
if r.test_build.revision == 'NULL':
r.test_build.no_pushlog = True # OOPS! SOMETHING BROKE
elif CNV.milli2datetime(Math.min(r.testrun.date, r.datazilla.date_loaded)) < PUSHLOG_TOO_OLD:
Log.note("{{branch}} @ {{revision}} has no pushlog, transforming anyway", r.test_build)
r.test_build.no_pushlog = True
else:
Log.note("{{branch}} @ {{revision}} has no pushlog, try again later", r.test_build)
return [] # TRY AGAIN LATER
else:
with self.locker:
if branch not in self.unknown_branches:
Log.note("Whole branch {{branch}} has no pushlog", {"branch":branch})
self.unknown_branches.add(branch)
if CNV.milli2datetime(Math.min(r.testrun.date, r.datazilla.date_loaded)) < PUSHLOG_TOO_OLD:
r.test_build.no_pushlog = True
else:
r.test_build.no_pushlog = True
#return [r] #TODO: DO THIS IF WE FIGURE OUT HOW TO HANDLE THE VERY LARGE NUMBER OF RESULTS WITH NO PUSHLOG
except Exception, e:
Log.warning("{{branch}} @ {{revision}} has no pushlog", r.test_build, e)
new_records = []
# RECORD THE UNKNOWN PART OF THE TEST RESULTS
remainder = r.copy()
remainder.results = None
if len(remainder.keys()) > 4:
new_records.append(remainder)
#RECORD TEST RESULTS
total = StructList()
if r.testrun.suite in ["dromaeo_css", "dromaeo_dom"]:
#dromaeo IS SPECIAL, REPLICATES ARE IN SETS OF FIVE
#RECORD ALL RESULTS
for i, (test_name, replicates) in enumerate(r.results.items()):
for g, sub_results in Q.groupby(replicates, size=5):
new_record = Struct(
test_machine=r.test_machine,
datazilla=r.datazilla,
testrun=r.testrun,
test_build=r.test_build,
result={
"test_name": unicode(test_name) + "." + unicode(g),
"ordering": i,
"samples": sub_results
}
)
try:
s = stats(sub_results)
new_record.result.stats = s
total.append(s)
except Exception, e:
Log.warning("can not reduce series to moments", e)
new_records.append(new_record)
test_machine=r.test_machine,
datazilla=r.datazilla,
testrun=r.testrun,
test_build=r.test_build,
result={
"test_name": test_name,
"ordering": i,
"samples": replicates
}
)
try:
s = stats(replicates)
new_record.result.stats = s
total.append(s)
except Exception, e:
Log.warning("can not reduce series to moments", e)
new_records.append(new_record)
if len(total) > 1:
# ADD RECORD FOR GEOMETRIC MEAN SUMMARY
new_record = Struct(
test_machine=r.test_machine,
datazilla=r.datazilla,
testrun=r.testrun,
test_build=r.test_build,
result={
"test_name": "SUMMARY",
"ordering": -1,
"stats": geo_mean(total)
}
added.add(id)
data = CNV.JSON2object(col[1])
records_for_db.add({
"id": nvl(data.test_run_id, id),
"branch": data.json_blob.test_build.branch,
"name": data.json_blob.test_build.name,
"version": data.json_blob.test_build.version,
"suite": data.json_blob.testrun.suite,
"revision": data.json_blob.test_build.revision,
"date": data.json_blob.testrun.date
})
Log.note("Added {{id}} from file", {"id": data.test_run_id})
except Exception, e:
Log.warning("Bad line ({{length}}bytes):\n\t{{prefix}}", {
"length": len(CNV.object2JSON(line)),
"prefix": CNV.object2JSON(line)[0:130]
}, e)
def main():
try:
settings = startup.read_settings(filename="file2db_settings.json")
Log.start(settings.debug)
with DB(settings.db) as db:
db.execute("""
DROP TABLE IF EXISTS b2g_tests
""")
db.execute("""
date = CNV.unix2datetime(data.testrun.date)
if id % 1000 == 0:
Log.println("loading id " + str(id) + " date: " + CNV.datetime2string(date, "%Y-%m-%d %H:%M:%S"))
if date < MINIMUM_DATE:
continue
if id in all:
continue
all.add(id)
arrays_add(id, "[" + data.test_build.branch + "][" + data.testrun.suite + "]", data)
output_file.write(str(id) + "\t" + json)
except Exception, e:
Log.warning("can not process line:\n\t" + line, e)
smallest = min(*all)
Log.println("First id >= date: {{min}}", {"min": smallest})
df = DataFrame(arrays, columns=["id", "path", "length", "count"])
colNames = [str(p) + " to " + str(parts[i + 1] - 1) for i, p in enumerate(parts[0:-1])]
# http://pandas.pydata.org/pandas-docs/stable/groupby.html#na-group-handling
length_dim = pandas.cut(df.length, parts, labels=colNames, right=False)
summary = df.groupby(["path", length_dim], sort=False).size()
#summary=summary.reindex(length_dim, level="length")
table = summary.unstack("length")
s = CNV.DataFrame2string(table)#, columns=colNames)
Log.println("\n" + s)
with open("talos_big_array_summary.tab", "w") as output_file:
es_sink.extend({"value": d} for d in result)
file_sink.add(str(id) + "\t" + content + "\n")
elif data.error_flag == 'Y':
error = data.json_blob
error.datazilla = data
error.results = None
data.json_blob = None
es_sink.add({"value": error})
else:
Log.println("No test run id for {{id}}", {"id": id})
del data
return True
except Exception, e:
Log.warning("Failure to etl (content length={{length}})", {"length": len(content)}, e)
return False
def get_existing_ids(es, settings, branches):
#FIND WHAT'S IN ES
bad_ids = []
int_ids = set()
demand_pushlog = {"match_all":{}}
if branches:
demand_pushlog = {"or": [
{"not": {"missing": {"field": "test_build.push_date"}}},
{"not": {"missing": {"field": "test_build.no_pushlog"}}}
]}
