def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in SCHEMAS:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
for schema in AGGREGATION_SCHEMAS:
if schema.matches(metric):
log.creates('new metric %s matched aggregation schema %s' % (metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception("No storage schema matched the metric '%s', check your storage-schemas.conf file." % metric)
log.creates("creating database metric %s (archive=%s xff=%s agg=%s)" %
(metric, archiveConfig, xFilesFactor, aggregationMethod))
try:
state.database.create(metric, archiveConfig, xFilesFactor, aggregationMethod)
instrumentation.increment('creates')
except Exception, e:
log.err()
log.msg("Error creating %s: %s" % (metric, e))
instrumentation.increment('errors')
continue
# If we've got a rate limit configured lets makes sure we enforce it
if UPDATE_BUCKET:
UPDATE_BUCKET.drain(1, blocking=True)
try:
t1 = time.time()
# If we have duplicated points, always pick the last. update_many()
# has no guaranted behavior for that, and in fact the current implementation
# will keep the first point in the list.
datapoints = dict(datapoints).items()
state.database.write(metric, datapoints)
updateTime = time.time() - t1
except Exception, e:
log.err()
log.msg("Error writing to %s: %s" % (metric, e))
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath, dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in SCHEMAS:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
for schema in AGGREGATION_SCHEMAS:
if schema.matches(metric):
log.creates('new metric %s matched aggregation schema %s' % (metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception("No storage schema matched the metric '%s', check your storage-schemas.conf file." % metric)
log.creates("creating database file %s (archive=%s xff=%s agg=%s)" %
(dbFilePath, archiveConfig, xFilesFactor, aggregationMethod))
try:
state.database.create(metric, archiveConfig, xFilesFactor, aggregationMethod)
instrumentation.increment('creates')
except Exception:
log.err("Error creating %s" % (dbFilePath))
continue
# If we've got a rate limit configured lets makes sure we enforce it
if UPDATE_BUCKET:
UPDATE_BUCKET.drain(1, blocking=True)
try:
t1 = time.time()
state.database.write(metric, datapoints)
updateTime = time.time() - t1
except Exception:
log.msg("Error writing to %s" % (dbFilePath))
log.err()
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
updates = 0
lastSecond = 0
while MetricCache:
dataWritten = False
#for (metric, datapoints, dbFilePath, dbFileExists) in optimalWriteOrder():
for (metric, datapoints, dbIdentifier, dbExists) in optimalWriteOrder():
dataWritten = True
if not dbExists:
persister.create_db(metric)
instrumentation.increment('creates')
try:
t1 = time.time()
persister.update_many(metric, datapoints, dbIdentifier)
t2 = time.time()
updateTime = t2 - t1
except:
log.msg("Error writing to %s" % (dbIdentifier))
log.err()
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep( int(t2 + 1) - t2 )
# Let the persister know it can flush
# (depends on the implementation)
persister.flush()
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints(channel, exchange):
log.msg("Entered function writeCachedDataPoints")
log.msg("MetricCache count: %d"%(len(MetricCache.counts())))
while MetricCache:
dataWritten = False
log.msg("Calling optimalWriteOrder")
for (metric, datapoints) in optimalWriteOrder():
dataWritten = True
body = ""
for point in datapoints:
temp = "%f %d\n"%(point[1], point[0])
body = body + temp
message = Content(body)
message["delivery mode"] = 2
channel.basic_publish(exchange=exchange, content=message, routing_key=metric)
log.updates("Published %d datapoints of metric %s"%(len(datapoints),metric))
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
updates = 0
lastSecond = 0
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath, dbFileExists) in optimalWriteOrder():
dataWritten = True
write_lock.acquire()
try:
if not createWhisperFile(metric, dbFilePath, dbFileExists):
continue
t1 = time.time()
written = writeWhisperFile(dbFilePath, datapoints)
finally:
write_lock.release()
if written:
t2 = time.time()
updateTime = t2 - t1
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep(int(t2 + 1) - t2)
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath,
dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in SCHEMAS:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' %
(metric, schema.name))
archiveConfig = [
archive.getTuple() for archive in schema.archives
]
break
for schema in AGGREGATION_SCHEMAS:
if schema.matches(metric):
log.creates(
'new metric %s matched aggregation schema %s' %
(metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception(
"No storage schema matched the metric '%s', check your storage-schemas.conf file."
% metric)
dbDir = dirname(dbFilePath)
try:
if not exists(dbDir):
os.makedirs(dbDir)
except OSError, e:
log.err("%s" % e)
log.creates(
"creating database file %s (archive=%s xff=%s agg=%s)" %
(dbFilePath, archiveConfig, xFilesFactor,
aggregationMethod))
try:
whisper.create(dbFilePath, archiveConfig, xFilesFactor,
aggregationMethod,
settings.WHISPER_SPARSE_CREATE,
settings.WHISPER_FALLOCATE_CREATE)
instrumentation.increment('creates')
except:
log.err("Error creating %s" % (dbFilePath))
continue
# If we've got a rate limit configured lets makes sure we enforce it
if UPDATE_BUCKET:
UPDATE_BUCKET.drain(1, blocking=True)
try:
t1 = time.time()
whisper.update_many(dbFilePath, datapoints)
updateTime = time.time() - t1
except Exception:
log.msg("Error writing to %s" % (dbFilePath))
log.err()
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" %
(pointCount, metric, updateTime))
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
cache = MetricCache()
while cache:
(metric, datapoints) = cache.drain_metric()
if metric is None:
# end the loop
break
dbFileExists = state.database.exists(metric)
if not dbFileExists:
if CREATE_BUCKET and not CREATE_BUCKET.drain(1):
# If our tokenbucket doesn't have enough tokens available to create a new metric
# file then we'll just drop the metric on the ground and move on to the next
# metric.
# XXX This behavior should probably be configurable to no tdrop metrics
# when rate limitng unless our cache is too big or some other legit
# reason.
instrumentation.increment('droppedCreates')
continue
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in SCHEMAS:
if schema.matches(metric):
if settings.LOG_CREATES:
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
for schema in AGGREGATION_SCHEMAS:
if schema.matches(metric):
if settings.LOG_CREATES:
log.creates('new metric %s matched aggregation schema %s'
% (metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception(("No storage schema matched the metric '%s',"
" check your storage-schemas.conf file.") % metric)
if settings.LOG_CREATES:
log.creates("creating database metric %s (archive=%s xff=%s agg=%s)" %
(metric, archiveConfig, xFilesFactor, aggregationMethod))
try:
state.database.create(metric, archiveConfig, xFilesFactor, aggregationMethod)
if settings.ENABLE_TAGS:
tagQueue.add(metric)
instrumentation.increment('creates')
except Exception as e:
log.err()
log.msg("Error creating %s: %s" % (metric, e))
instrumentation.increment('errors')
continue
# If we've got a rate limit configured lets makes sure we enforce it
waitTime = 0
if UPDATE_BUCKET:
t1 = time.time()
yield UPDATE_BUCKET.drain(1, blocking=True)
waitTime = time.time() - t1
try:
t1 = time.time()
# If we have duplicated points, always pick the last. update_many()
# has no guaranted behavior for that, and in fact the current implementation
# will keep the first point in the list.
datapoints = dict(datapoints).items()
state.database.write(metric, datapoints)
if settings.ENABLE_TAGS:
tagQueue.update(metric)
updateTime = time.time() - t1
except Exception as e:
log.err()
log.msg("Error writing to %s: %s" % (metric, e))
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
if waitTime > 0.001:
log.updates("wrote %d datapoints for %s in %.5f seconds after waiting %.5f seconds" % (
pointCount, metric, updateTime, waitTime))
else:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (
pointCount, metric, updateTime))
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
updates = 0
lastSecond = 0
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath,
dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in schemas:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' %
(metric, schema.name))
archiveConfig = [
archive.getTuple() for archive in schema.archives
]
break
for schema in agg_schemas:
if schema.matches(metric):
log.creates(
'new metric %s matched aggregation schema %s' %
(metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception(
"No storage schema matched the metric '%s', check your storage-schemas.conf file."
% metric)
dbDir = dirname(dbFilePath)
try:
os.makedirs(dbDir, 0755)
except OSError as e:
log.err("%s" % e)
log.creates(
"creating database file %s (archive=%s xff=%s agg=%s)" %
(dbFilePath, archiveConfig, xFilesFactor,
aggregationMethod))
whisper.create(dbFilePath, archiveConfig, xFilesFactor,
aggregationMethod,
settings.WHISPER_SPARSE_CREATE,
settings.WHISPER_FALLOCATE_CREATE)
instrumentation.increment('creates')
try:
t1 = time.time()
whisper.update_many(dbFilePath, datapoints)
t2 = time.time()
updateTime = t2 - t1
except:
log.msg("Error writing to %s" % (dbFilePath))
log.err()
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" %
(pointCount, metric, updateTime))
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep(int(t2 + 1) - t2)
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
updates = 0
lastSecond = 0
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath, dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in schemas:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
for schema in agg_schemas:
if schema.matches(metric):
log.creates('new metric %s matched aggregation schema %s' % (metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception("No storage schema matched the metric '%s', check your storage-schemas.conf file." % metric)
dbDir = dirname(dbFilePath)
try:
os.makedirs(dbDir, 0755)
except OSError as e:
log.err("%s" % e)
log.creates("creating database file %s (archive=%s xff=%s agg=%s)" %
(dbFilePath, archiveConfig, xFilesFactor, aggregationMethod))
whisper.create(dbFilePath, archiveConfig, xFilesFactor, aggregationMethod, settings.WHISPER_SPARSE_CREATE, settings.WHISPER_FALLOCATE_CREATE)
instrumentation.increment('creates')
try:
t1 = time.time()
whisper.update_many(dbFilePath, datapoints)
t2 = time.time()
updateTime = t2 - t1
except:
log.msg("Error writing to %s" % (dbFilePath))
log.err()
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep(int(t2 + 1) - t2)
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
cache = MetricCache()
while cache:
dataWritten = False
for (metric, datapoints, dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in SCHEMAS:
if schema.matches(metric):
if settings.LOG_CREATES:
log.creates('new metric %s matched schema %s' %
(metric, schema.name))
archiveConfig = [
archive.getTuple() for archive in schema.archives
]
break
for schema in AGGREGATION_SCHEMAS:
if schema.matches(metric):
if settings.LOG_CREATES:
log.creates(
'new metric %s matched aggregation schema %s' %
(metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception(
"No storage schema matched the metric '%s', check your storage-schemas.conf file."
% metric)
if settings.LOG_CREATES:
log.creates(
"creating database metric %s (archive=%s xff=%s agg=%s)"
% (metric, archiveConfig, xFilesFactor,
aggregationMethod))
try:
state.database.create(metric, archiveConfig, xFilesFactor,
aggregationMethod)
instrumentation.increment('creates')
except Exception, e:
log.err()
log.msg("Error creating %s: %s" % (metric, e))
instrumentation.increment('errors')
continue
# If we've got a rate limit configured lets makes sure we enforce it
if UPDATE_BUCKET:
UPDATE_BUCKET.drain(1, blocking=True)
try:
t1 = time.time()
# If we have duplicated points, always pick the last. update_many()
# has no guaranted behavior for that, and in fact the current implementation
# will keep the first point in the list.
datapoints = dict(datapoints).items()
state.database.write(metric, datapoints)
updateTime = time.time() - t1
except Exception, e:
log.err()
log.msg("Error writing to %s: %s" % (metric, e))
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" %
(pointCount, metric, updateTime))
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
updates = 0
lastSecond = 0
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath, dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
for schema in schemas:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
if not archiveConfig:
raise Exception("No storage schema matched the metric '%s', check your storage-schemas.conf file." % metric)
dbDir = dirname(dbFilePath)
os.system("mkdir -p -m 755 '%s'" % dbDir)
log.creates("creating database file %s" % dbFilePath)
whisper.create(dbFilePath, archiveConfig)
os.chmod(dbFilePath, 0755)
instrumentation.increment('creates')
# Create metadata file
dbFileName = basename(dbFilePath)
metaFilePath = join(dbDir, dbFileName[ :-len('.wsp') ] + '.context.pickle')
createMetaFile(metric, schema, metaFilePath)
try:
t1 = time.time()
whisper.update_many(dbFilePath, datapoints)
t2 = time.time()
updateTime = t2 - t1
except:
log.err()
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep( int(t2 + 1) - t2 )
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
cache = MetricCache()
while cache:
(metric, datapoints) = cache.drain_metric()
if metric is None:
# end the loop
break
dbFileExists = state.database.exists(metric)
if not dbFileExists:
if CREATE_BUCKET and not CREATE_BUCKET.drain(1):
# If our tokenbucket doesn't have enough tokens available to create a new metric
# file then we'll just drop the metric on the ground and move on to the next
# metric.
# XXX This behavior should probably be configurable to no tdrop metrics
# when rate limitng unless our cache is too big or some other legit
# reason.
instrumentation.increment('droppedCreates')
continue
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in SCHEMAS:
if schema.matches(metric):
if settings.LOG_CREATES:
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
for schema in AGGREGATION_SCHEMAS:
if schema.matches(metric):
if settings.LOG_CREATES:
log.creates('new metric %s matched aggregation schema %s'
% (metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception(("No storage schema matched the metric '%s',"
" check your storage-schemas.conf file.") % metric)
if settings.LOG_CREATES:
log.creates("creating database metric %s (archive=%s xff=%s agg=%s)" %
(metric, archiveConfig, xFilesFactor, aggregationMethod))
try:
state.database.create(metric, archiveConfig, xFilesFactor, aggregationMethod)
if settings.ENABLE_TAGS:
tagQueue.add(metric)
instrumentation.increment('creates')
except Exception as e:
log.err()
log.msg("Error creating %s: %s" % (metric, e))
instrumentation.increment('errors')
continue
# If we've got a rate limit configured lets makes sure we enforce it
waitTime = 0
if UPDATE_BUCKET:
t1 = time.time()
UPDATE_BUCKET.drain(1, blocking=True)
waitTime = time.time() - t1
try:
t1 = time.time()
# If we have duplicated points, always pick the last. update_many()
# has no guaranted behavior for that, and in fact the current implementation
# will keep the first point in the list.
datapoints = dict(datapoints).items()
state.database.write(metric, datapoints)
if settings.ENABLE_TAGS:
tagQueue.update(metric)
updateTime = time.time() - t1
except Exception as e:
log.err()
log.msg("Error writing to %s: %s" % (metric, e))
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
if waitTime > 0.001:
log.updates("wrote %d datapoints for %s in %.5f seconds after waiting %.5f seconds" % (
pointCount, metric, updateTime, waitTime))
else:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (
pointCount, metric, updateTime))
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
updates = 0
lastSecond = 0
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath,
dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
for schema in schemas:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' %
(metric, schema.name))
archiveConfig = [
archive.getTuple() for archive in schema.archives
]
break
if not archiveConfig:
raise Exception(
"No storage schema matched the metric '%s', check your storage-schemas.conf file."
% metric)
dbDir = dirname(dbFilePath)
os.system("mkdir -p -m 755 '%s'" % dbDir)
log.creates("creating database file %s" % dbFilePath)
whisper.create(dbFilePath, archiveConfig)
os.chmod(dbFilePath, 0755)
increment('creates')
# Create metadata file
dbFileName = basename(dbFilePath)
metaFilePath = join(
dbDir, dbFileName[:-len('.wsp')] + '.context.pickle')
createMetaFile(metric, schema, metaFilePath)
try:
t1 = time.time()
whisper.update_many(dbFilePath, datapoints)
t2 = time.time()
updateTime = t2 - t1
except:
log.err()
increment('errors')
else:
pointCount = len(datapoints)
increment('committedPoints', pointCount)
append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" %
(pointCount, metric, updateTime))
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep(int(t2 + 1) - t2)
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
global updates
global lastSecond
# while MetricCache:
# dataWritten = False
for (metric, datapoints, dbFilePath, dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
archiveConfig = None
xFilesFactor, aggregationMethod = None, None
for schema in schemas:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
for schema in agg_schemas:
if schema.matches(metric):
log.creates('new metric %s matched aggregation schema %s' % (metric, schema.name))
xFilesFactor, aggregationMethod = schema.archives
break
if not archiveConfig:
raise Exception("No storage schema matched the metric '%s', check your storage-schemas.conf file." % metric)
try:
dbDir = dirname(dbFilePath)
os.system("umask u=rwx,go=rx ; mkdir -p -m 755 '%s'" % dbDir)
log.creates("creating database file %s (archive=%s xff=%s agg=%s)" %
(dbFilePath, archiveConfig, xFilesFactor, aggregationMethod))
whisper.create(dbFilePath, archiveConfig, xFilesFactor, aggregationMethod)
os.chmod(dbFilePath, 0755)
instrumentation.increment('creates')
except IOError as e:
log.msg("IOError: {0}".format(e))
try:
t1 = time.time()
whisper.update_many(dbFilePath, datapoints)
t2 = time.time()
updateTime = t2 - t1
except:
log.err()
instrumentation.increment('errors')
else:
pointCount = len(datapoints)
instrumentation.increment('committedPoints', pointCount)
instrumentation.append('updateTimes', updateTime)
if settings.LOG_UPDATES:
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep( int(t2 + 1) - t2 )
time.sleep(5)
def writeCachedDataPoints():
"Write datapoints until the MetricCache is completely empty"
updates = 0
lastSecond = 0
while MetricCache:
dataWritten = False
for (metric, datapoints, dbFilePath, dbFileExists) in optimalWriteOrder():
dataWritten = True
if not dbFileExists:
for schema in schemas:
if schema.matches(metric):
log.creates('new metric %s matched schema %s' % (metric, schema.name))
archiveConfig = [archive.getTuple() for archive in schema.archives]
break
dbDir = dirname(dbFilePath)
os.system("mkdir -p '%s'" % dbDir)
log.creates("creating database file %s" % dbFilePath)
whisper.create(dbFilePath, archiveConfig)
increment('creates')
# Create metadata file
dbFileName = basename(dbFilePath)
metaFilePath = join(dbDir, dbFileName[ :-len('.wsp') ] + '.context.pickle')
createMetaFile(metric, schema, metaFilePath)
data = {}
try:
t1 = time.time()
counts = {}
for dp in datapoints:
key = long(dp[0] / 60)
if not key in data:
data[key] = 0
counts[key] = 0
data[key] += dp[1]
counts[key] += 1
if "/rt" in dbFilePath or "latency_ms" in dbFilePath:
print "AVERAGING", dbFilePath
for key, value in data.iteritems():
data[key] = value / counts[key]
for dptime, datavalue in data.iteritems():
whisper.update(dbFilePath, datavalue, dptime * 60)
t2 = time.time()
updateTime = t2 - t1
except:
log.err()
increment('errors')
else:
pointCount = len(data)
log.updates("wrote %d datapoints for %s in %.5f seconds" % (pointCount, metric, updateTime))
increment('committedPoints', pointCount)
append('updateTimes', updateTime)
# Rate limit update operations
thisSecond = int(t2)
if thisSecond != lastSecond:
lastSecond = thisSecond
updates = 0
else:
updates += 1
if updates >= settings.MAX_UPDATES_PER_SECOND:
time.sleep( int(t2 + 1) - t2 )
# Avoid churning CPU when only new metrics are in the cache
if not dataWritten:
time.sleep(0.1)
def writeMetric(metricList, host, port, username, password,
vhost, exchange, spec=None, channel_number=1, ssl=False):
t1 = time.time()
if not spec:
spec = txamqp.spec.load(os.path.normpath(
os.path.join(os.path.dirname(__file__), 'amqp0-8.xml')))
delegate = TwistedDelegate()
#log.msg("Creating AMQClient")
connector = ClientCreator(reactor, AMQClient, delegate=delegate,
vhost=vhost, spec=spec)
#log.msg("Created AMQClient")
try:
if ssl:
from twisted.internet.ssl import ClientContextFactory
conn = yield connector.connectSSL(host, port, ClientContextFactory())
else:
#log.msg("Requesting TCP connection to host %s, and port %s" % (host, port))
#try:
conn = yield connector.connectTCP(host, port, timeout=130)
#except:
#log.msg("Not able to connect to RabitMQ server!!")
#Push metrics back into the cache
#backIntoCache(metricList)
#return
#raise Exception("Not able to connect to RabitMQ server!!")
#log.msg("TCP connection established")
#log.msg("Authenticating")
yield conn.authenticate(username, password)
#log.msg("Authentication done")
except:
log.msg("Not able to connect to RabitMQ server!!")
backIntoCache(metricList)
return
channel = yield conn.channel(channel_number)
yield channel.channel_open()
#log.msg("Channel open")
yield channel.exchange_declare(exchange=exchange, type="topic", durable=True, auto_delete=False)
reply = yield channel.queue_declare(queue = settings.AMQP_QUEUE, durable = True)
my_queue = reply.queue
for bind_pattern in settings.BIND_PATTERNS:
#log.listener("binding exchange '%s' to queue '%s' with pattern %s" % (exchange, my_queue, bind_pattern))
yield channel.queue_bind(exchange=exchange, queue=my_queue, routing_key=bind_pattern)
pointCount = 0
for (metric, datapoints) in metricList:
body = ""
pointCount += len(datapoints)
for point in datapoints:
temp = "%f %d\n"%(point[1], point[0])
body = body + temp
message = Content(body)
message["delivery mode"] = 2
channel.basic_publish(exchange=exchange, content=message, routing_key=metric)
yield channel.channel_close()
yield conn.close("The job is done")
t2 = time.time()
publishTime = t2 - t1
if settings.LOG_UPDATES:
log.updates("Published %d metrics in %.5f seconds" % (len(metricList), publishTime))
instrumentation.append('updateTimes', publishTime)
instrumentation.increment('committedPoints', pointCount)