def runpreproccall(preproc, result, mtypes, ctx, mdata, description):
data = []
for i in xrange(result.contents.numpmid):
data.append(numpy.array([pcpfast.pcpfastExtractValues(result, i, j, mtypes[i])
for j in xrange(result.contents.get_numval(i))]))
return preproc.process(float(result.contents.timestamp), data, description)
def runcallback(self, analytic, result, mtypes, ctx, mdata, metric_id_array):
""" get the data and call the analytic """
if self.indomcache == None:
# First time through populate the indom cache
self.indomcache = self.getindomdict(ctx, metric_id_array)
if self.indomcache == None:
# Unable to get indom information
return False
data = []
description = []
for i in xrange(result.contents.numpmid):
ninstances = result.contents.get_numval(i)
if ninstances < 0:
logging.warning("%s %s ninstances = %s @ %s", mdata.nodename, analytic.name, ninstances, float(result.contents.timestamp))
self.logerror(mdata.nodename, analytic.name, "get_numval() error")
return False
tmp = numpy.empty(ninstances, dtype=self.pcptypetonumpy(mtypes[i]))
tmpnames = []
tmpidx = numpy.empty(ninstances, dtype=long)
for j in xrange(ninstances):
pcpdata = pcpfast.pcpfastExtractValues(result, i, j, mtypes[i])
tmp[j] = pcpdata[0]
if pcpdata[1] > -1:
tmpidx[j] = pcpdata[1]
if pcpdata[1] not in self.indomcache[i]:
# indoms must have changed; rebuild the cache
self.indomcache = self.getindomdict(ctx, metric_id_array)
if self.indomcache == None:
return False
if pcpdata[1] not in self.indomcache[i]:
# Unable to get indom information for one of the instance domains
# Ignore this timestep, but carry on
logging.warning("%s %s missing indom @ %s", mdata.nodename, analytic.name, float(result.contents.timestamp))
self.logerror(mdata.nodename, analytic.name, "missing indom")
return True
tmpnames.append(self.indomcache[i][pcpdata[1]])
data.append(tmp)
description.append([tmpidx, tmpnames])
try:
retval = analytic.process(mdata, float(result.contents.timestamp), data, description)
return retval
except Exception as e:
logging.exception("%s %s @ %s", self.job.job_id, analytic.name, float(result.contents.timestamp))
self.logerror(mdata.nodename, analytic.name, str(e))
return False
def runpreproccall(self, preproc, result, mtypes, ctx, mdata, metric_id_array):
""" Call the pre-processor data processing function """
description = self.getindomdict(ctx, metric_id_array)
if description == None:
return True
data = []
for i in xrange(result.contents.numpmid):
data.append(numpy.array([pcpfast.pcpfastExtractValues(result, i, j, mtypes[i])
for j in xrange(result.contents.get_numval(i))]))
return preproc.process(float(result.contents.timestamp), data, description)
def runcallback(self, analytic, result, mtypes, ctx, mdata, description):
data = []
for i in xrange(result.contents.numpmid):
data.append(numpy.array([pcpfast.pcpfastExtractValues(result, i, j, mtypes[i])[0]
for j in xrange(result.contents.get_numval(i))]))
try:
retval = analytic.process(mdata, float(result.contents.timestamp), data, description)
return retval
except Exception as e:
logging.exception("%s %s @ %s", self.job.job_id, analytic.name, float(result.contents.timestamp))
self.logerror(mdata.nodename, analytic.name, str(e))
return False
def runpreproccall(self, preproc, result, mtypes, ctx, mdata,
metric_id_array):
""" Call the pre-processor data processing function """
description = self.getindomdict(ctx, metric_id_array)
if description == None:
return True
data = []
for i in xrange(result.contents.numpmid):
data.append(
numpy.array([
pcpfast.pcpfastExtractValues(result, i, j, mtypes[i])
for j in xrange(result.contents.get_numval(i))
]))
return preproc.process(float(result.contents.timestamp), data,
description)
def runcallback(self, analytic, result, mtypes, ctx, mdata,
metric_id_array):
""" get the data and call the analytic """
if self.indomcache == None:
# First time through populate the indom cache
self.indomcache = self.getindomdict(ctx, metric_id_array)
if self.indomcache == None:
# Unable to get indom information
return False
data = []
description = []
for i in xrange(result.contents.numpmid):
ninstances = result.contents.get_numval(i)
if ninstances < 0:
logging.warning("%s %s ninstances = %s @ %s", mdata.nodename,
analytic.name, ninstances,
float(result.contents.timestamp))
self.logerror(mdata.nodename, analytic.name,
"get_numval() error")
return False
tmp = numpy.empty(ninstances, dtype=self.pcptypetonumpy(mtypes[i]))
tmpnames = []
tmpidx = numpy.empty(ninstances, dtype=long)
for j in xrange(ninstances):
pcpdata = pcpfast.pcpfastExtractValues(result, i, j, mtypes[i])
tmp[j] = pcpdata[0]
if pcpdata[1] > -1:
tmpidx[j] = pcpdata[1]
if pcpdata[1] not in self.indomcache[i]:
# indoms must have changed; rebuild the cache
self.indomcache = self.getindomdict(
ctx, metric_id_array)
if self.indomcache == None:
return False
if pcpdata[1] not in self.indomcache[i]:
# Unable to get indom information for one of the instance domains
# Ignore this timestep, but carry on
logging.warning("%s %s missing indom @ %s",
mdata.nodename, analytic.name,
float(result.contents.timestamp))
self.logerror(mdata.nodename, analytic.name,
"missing indom")
return True
tmpnames.append(self.indomcache[i][pcpdata[1]])
data.append(tmp)
description.append([tmpidx, tmpnames])
try:
self.rangechange.normalise_data(float(result.contents.timestamp),
data)
retval = analytic.process(mdata, float(result.contents.timestamp),
data, description)
return retval
except Exception as e:
logging.exception("%s %s @ %s", self.job.job_id, analytic.name,
float(result.contents.timestamp))
self.logerror(mdata.nodename, analytic.name, str(e))
return False