def process_gc_collector(self, bean, kept):
context = bean['name'].split("java.lang:type=")[1].split(",name=")
for key, value in bean.iteritems():
if key in EXCLUDED_KEYS:
continue
if value is None:
continue
if key == 'LastGcInfo':
context.append(key)
for lastgc_key, lastgc_val in bean[key].iteritems():
if lastgc_key == 'memoryUsageAfterGc' or lastgc_key == 'memoryUsageBeforeGc':
context.append(lastgc_key)
for memusage in lastgc_val: # lastgc_val is a list
context.append(memusage["key"])
for final_key, final_val in memusage[
"value"].iteritems():
safe_context, safe_final_key = self.safe_replace(
context, final_key)
kept.append(
(safe_context, safe_final_key, final_val))
context.pop()
context.pop()
elif is_numeric(lastgc_val):
safe_context, safe_lastgc_key = self.safe_replace(
context, lastgc_key)
kept.append(
(safe_context, safe_lastgc_key, lastgc_val))
context.pop()
elif is_numeric(value):
safe_context, safe_key = self.safe_replace(context, key)
kept.append((safe_context, safe_key, value))
def poll(self):
"""
Get metrics from the http server's /jmx page, and transform them into normalized tupes
@return: array of tuples ([u'Context', u'Array'], u'metricName', value)
"""
json_arr = self.request().get('beans', [])
kept = []
for bean in json_arr:
if (not bean['name']) or (not "name=" in bean['name']):
continue
#split the name string
bean_name = bean['name'].split("name=")[1]
context = re.split(",sub=|,q[0-9]+=", bean_name)
# Create a set that keeps the first occurrence
context = OrderedDict.fromkeys(context).keys()
# lower case and replace spaces.
context = [c.lower().replace(" ", "_") for c in context]
# don't want to include the service or daemon twice
context = [c for c in context if c != self.service and c != self.daemon]
for key, value in bean.iteritems():
if key in EXCLUDED_KEYS:
continue
value = value if is_numeric(value) else self.to_numeric(context, key, value)
if not is_numeric(value):
continue
kept.append((context, key, value))
return kept
def poll(self):
"""
Get metrics from the http server's /jmx page, and transform them into normalized tupes
@return: array of tuples ([u'Context', u'Array'], u'metricName', value)
"""
json_arr = self.request().get('beans', [])
kept = []
for bean in json_arr:
if (not bean['name']) or (not "name=" in bean['name']):
continue
#split the name string
context = bean['name'].split("name=")[1].split(",sub=")
# Create a set that keeps the first occurrence
context = OrderedDict.fromkeys(context).keys()
# lower case and replace spaces.
context = [c.lower().replace(" ", "_") for c in context]
# don't want to include the service or daemon twice
context = [
c for c in context if c != self.service and c != self.daemon
]
for key, value in bean.iteritems():
if key in EXCLUDED_KEYS:
continue
if not is_numeric(value):
continue
kept.append((context, key, value))
return kept
def print_metrics(self, d, metric_prefix, timestamp, tags, not_tags=[]):
""" Take a dict of attributes and print out numerical metric strings
Recurse if necessary
"""
for k, v in d.items():
# Tack on the name of the attribute
attribute, more_tags = self.parse_attribute(k.lower(), not_tags)
metric_name = '.'.join([metric_prefix, attribute])
my_tags = tags + more_tags
# If numerical
if utils.is_numeric(v):
print("%s %d %s %s" %
(metric_name, timestamp, str(v), ' '.join(my_tags)))
# If a bool, True=1, False=0
elif type(v) is bool:
print("%s %d %s %s" %
(metric_name, timestamp, str(int(v)), ' '.join(my_tags)))
# Or a dict of more attributes, call ourselves again
elif type(v) is dict:
self.print_metrics(v, metric_name, timestamp, my_tags,
not_tags)
else:
#lists, strings, etc
#print '# ', type(v), metric_name, str(v)
pass
def process_java_lang_metrics(self, bean, kept):
context = bean['name'].split("java.lang:type=")[1].split(",name=")
for key, value in bean.iteritems():
if key in EXCLUDED_KEYS:
continue
if value is None:
continue
if is_numeric(value):
safe_context, safe_key = self.safe_replace(context, key)
kept.append((safe_context, safe_key, value))
elif isinstance(
value, dict
): # only go one level deep since there is no other level empirically
for subkey, subvalue in value.iteritems():
if is_numeric(subvalue):
safe_context, final_key = self.safe_replace(
context, key + "." + subkey)
kept.append((safe_context, final_key, subvalue))
def poll(self):
"""
Get metrics from the http server's /jmx page, and transform them into normalized tupes
@return: array of tuples ([u'Context', u'Array'], u'metricName', value)
"""
json_arr = self.request().get('beans', [])
kept = []
for bean in json_arr:
try:
if (bean['name']) and (bean['name'].startswith(
'java.lang:type=GarbageCollector')):
self.process_gc_collector(bean, kept)
elif (bean['name']) and (
bean['name'].startswith('java.lang:type=')):
self.process_java_lang_metrics(bean, kept)
elif (bean['name']) and ("name=" in bean['name']):
# split the name string
context = bean['name'].split("name=")[1].split(",sub=")
# Create a set that keeps the first occurrence
context = OrderedDict.fromkeys(context).keys()
# lower case and replace spaces.
context = [c.lower().replace(" ", "_") for c in context]
# don't want to include the service or daemon twice
context = [
c for c in context
if c != self.service and c != self.daemon
]
for key, value in bean.iteritems():
if key in EXCLUDED_KEYS:
continue
if not is_numeric(value):
continue
kept.append((context, key, value))
except Exception as e:
self.logger.exception(
"exception in HadoopHttp when collecting %s", bean['name'])
return kept
def _traverse(metric, stats, ts, tags):
"""
Recursively traverse the json tree and print out leaf numeric values
Please make sure you call this inside a lock and don't add locking
inside this function
"""
#print metric,stats,ts,tags
if isinstance(stats, dict):
if "timestamp" in stats:
ts = stats["timestamp"] / 1000 # ms -> s
for key in stats.keys():
if key != "timestamp":
_traverse(metric + "." + key, stats[key], ts, tags)
if isinstance(stats, (list, set, tuple)):
count = 0
for value in stats:
_traverse(metric + "." + str(count), value, ts, tags)
count += 1
if utils.is_numeric(stats) and not isinstance(stats, bool):
if isinstance(stats, int):
stats = int(stats)
printmetric(metric, ts, stats, tags)
return
def _traverse(metric, stats, ts, tags):
"""
Recursively traverse the json tree and print out leaf numeric values
Please make sure you call this inside a lock and don't add locking
inside this function
"""
#print metric,stats,ts,tags
if isinstance(stats,dict):
if "timestamp" in stats:
ts = stats["timestamp"] / 1000 # ms -> s
for key in stats.keys():
if key != "timestamp":
_traverse(metric + "." + key, stats[key], ts, tags)
if isinstance(stats, (list, set, tuple)):
count = 0
for value in stats:
_traverse(metric + "." + str(count), value, ts, tags)
count += 1
if utils.is_numeric(stats) and not isinstance(stats, bool):
if isinstance(stats, int):
stats = int(stats)
printmetric(metric, ts, stats, tags)
return
def print_metrics(self, d, metric_prefix, timestamp, tags, not_tags=[]):
""" Take a dict of attributes and print out numerical metric strings
Recurse if necessary
"""
for k, v in d.iteritems():
# Tack on the name of the attribute
attribute, more_tags = self.parse_attribute(k.lower(), not_tags)
metric_name = '.'.join([metric_prefix, attribute])
my_tags = tags + more_tags
# If numerical
if utils.is_numeric(v):
print "%s %d %s %s" % (metric_name, timestamp, str(v),
' '.join(my_tags))
# If a bool, True=1, False=0
elif type(v) is bool:
print "%s %d %s %s" % (metric_name, timestamp, str(int(v)),
' '.join(my_tags))
# Or a dict of more attributes, call ourselves again
elif type(v) is dict:
self.print_metrics(v, metric_name, timestamp, my_tags, not_tags)
else:
#lists, strings, etc
#print '# ', type(v), metric_name, str(v)
pass
% (cluster_name, nstats["cluster_name"]))
return 1
this_nodeid, nstats = nstats["nodes"].popitem()
if this_nodeid != nodeid:
err("node ID changed from %r to %r" % (nodeid, this_nodeid))
return 1
is_master = nodeid == cluster_state(server)["master_node"]
printmetric("is_master", int(is_master))
if is_master:
ts = int(time.time()) # In case last call took a while.
cstats = cluster_health(server)
for stat, value in cstats.iteritems():
if stat == "status":
value = STATUS_MAP.get(value, -1)
elif not utils.is_numeric(value):
continue
printmetric("cluster." + stat, value)
if "os" in nstats:
ts = nstats["os"]["timestamp"] / 1000 # ms -> s
if "timestamp" in nstats:
ts = nstats["timestamp"] / 1000 # ms -> s
if "indices" in nstats:
indices = nstats["indices"]
if "docs" in indices:
printmetric("num_docs", indices["docs"]["count"])
if "store" in indices:
printmetric("indices.size", indices["store"]["size_in_bytes"])
if "indexing" in indices:
def _collect_server(server, version):
ts = int(time.time())
nstats = node_stats(server, version)
cluster_name = nstats["cluster_name"]
nodeid, nstats = nstats["nodes"].popitem()
node_name = nstats["name"]
is_master = nodeid == cluster_state(server)["master_node"]
printmetric("is_master",
ts,
int(is_master),
node=node_name,
cluster=cluster_name)
if is_master:
ts = int(time.time()) # In case last call took a while.
cstats = cluster_health(server)
for stat, value in cstats.iteritems():
if stat == "status":
value = STATUS_MAP.get(value, -1)
elif not utils.is_numeric(value):
continue
printmetric("cluster." + stat, ts, value, cluster=cluster_name)
if "os" in nstats:
ts = nstats["os"]["timestamp"] / 1000 # ms -> s
if "timestamp" in nstats:
ts = nstats["timestamp"] / 1000 # ms -> s
if "indices" in nstats:
indices = nstats["indices"]
if "docs" in indices:
printmetric("num_docs",
ts,
indices["docs"]["count"],
node=node_name,
cluster=cluster_name)
if "store" in indices:
printmetric("indices.size",
ts,
indices["store"]["size_in_bytes"],
node=node_name,
cluster=cluster_name)
if "indexing" in indices:
d = indices["indexing"]
printmetric("indexing.index_total",
ts,
d["index_total"],
node=node_name,
cluster=cluster_name)
printmetric("indexing.index_time",
ts,
d["index_time_in_millis"],
node=node_name,
cluster=cluster_name)
printmetric("indexing.index_current",
ts,
d["index_current"],
node=node_name,
cluster=cluster_name)
printmetric("indexing.delete_total",
ts,
d["delete_total"],
node=node_name,
cluster=cluster_name)
printmetric("indexing.delete_time_in_millis",
ts,
d["delete_time_in_millis"],
node=node_name,
cluster=cluster_name)
printmetric("indexing.delete_current",
ts,
d["delete_current"],
node=node_name,
cluster=cluster_name)
del d
if "get" in indices:
d = indices["get"]
printmetric("get.total",
ts,
d["total"],
node=node_name,
cluster=cluster_name)
printmetric("get.time",
ts,
d["time_in_millis"],
node=node_name,
cluster=cluster_name)
printmetric("get.exists_total",
ts,
d["exists_total"],
node=node_name,
cluster=cluster_name)
printmetric("get.exists_time",
ts,
d["exists_time_in_millis"],
node=node_name,
cluster=cluster_name)
printmetric("get.missing_total",
ts,
d["missing_total"],
node=node_name,
cluster=cluster_name)
printmetric("get.missing_time",
ts,
d["missing_time_in_millis"],
node=node_name,
cluster=cluster_name)
del d
if "search" in indices:
d = indices["search"]
printmetric("search.query_total",
ts,
d["query_total"],
node=node_name,
cluster=cluster_name)
printmetric("search.query_time",
ts,
d["query_time_in_millis"],
node=node_name,
cluster=cluster_name)
printmetric("search.query_current",
ts,
d["query_current"],
node=node_name,
cluster=cluster_name)
printmetric("search.fetch_total",
ts,
d["fetch_total"],
node=node_name,
cluster=cluster_name)
printmetric("search.fetch_time",
ts,
d["fetch_time_in_millis"],
node=node_name,
cluster=cluster_name)
printmetric("search.fetch_current",
ts,
d["fetch_current"],
node=node_name,
cluster=cluster_name)
del d
if "cache" in indices:
d = indices["cache"]
printmetric("cache.field.evictions",
ts,
d["field_evictions"],
node=node_name,
cluster=cluster_name)
printmetric("cache.field.size",
ts,
d["field_size_in_bytes"],
node=node_name,
cluster=cluster_name)
printmetric("cache.filter.count",
ts,
d["filter_count"],
node=node_name,
cluster=cluster_name)
printmetric("cache.filter.evictions",
ts,
d["filter_evictions"],
node=node_name,
cluster=cluster_name)
printmetric("cache.filter.size",
ts,
d["filter_size_in_bytes"],
node=node_name,
cluster=cluster_name)
del d
if "merges" in indices:
d = indices["merges"]
printmetric("merges.current",
ts,
d["current"],
node=node_name,
cluster=cluster_name)
printmetric("merges.total",
ts,
d["total"],
node=node_name,
cluster=cluster_name)
printmetric("merges.total_time",
ts,
d["total_time_in_millis"] / 1000.,
node=node_name,
cluster=cluster_name)
del d
del indices
if "process" in nstats:
process = nstats["process"]
ts = process["timestamp"] / 1000 # ms -> s
open_fds = process.get("open_file_descriptors") # ES 0.17
if open_fds is None:
open_fds = process.get("fd") # ES 0.16
if open_fds is not None:
open_fds = open_fds["total"]
if open_fds is not None:
printmetric("process.open_file_descriptors",
ts,
open_fds,
node=node_name,
cluster=cluster_name)
if "cpu" in process:
d = process["cpu"]
printmetric("process.cpu.percent",
ts,
d["percent"],
node=node_name,
cluster=cluster_name)
printmetric("process.cpu.sys",
ts,
d["sys_in_millis"] / 1000.,
node=node_name,
cluster=cluster_name)
printmetric("process.cpu.user",
ts,
d["user_in_millis"] / 1000.,
node=node_name,
cluster=cluster_name)
del d
if "mem" in process:
d = process["mem"]
printmetric("process.mem.resident",
ts,
d["resident_in_bytes"],
node=node_name,
cluster=cluster_name)
printmetric("process.mem.shared",
ts,
d["share_in_bytes"],
node=node_name,
cluster=cluster_name)
printmetric("process.mem.total_virtual",
ts,
d["total_virtual_in_bytes"],
node=node_name,
cluster=cluster_name)
del d
del process
if "jvm" in nstats:
jvm = nstats["jvm"]
ts = jvm["timestamp"] / 1000 # ms -> s
if "mem" in jvm:
d = jvm["mem"]
printmetric("jvm.mem.heap_used",
ts,
d["heap_used_in_bytes"],
node=node_name,
cluster=cluster_name)
printmetric("jvm.mem.heap_committed",
ts,
d["heap_committed_in_bytes"],
node=node_name,
cluster=cluster_name)
printmetric("jvm.mem.non_heap_used",
ts,
d["non_heap_used_in_bytes"],
node=node_name,
cluster=cluster_name)
printmetric("jvm.mem.non_heap_committed",
ts,
d["non_heap_committed_in_bytes"],
node=node_name,
cluster=cluster_name)
del d
if "threads" in jvm:
d = jvm["threads"]
printmetric("jvm.threads.count",
ts,
d["count"],
node=node_name,
cluster=cluster_name)
printmetric("jvm.threads.peak_count",
ts,
d["peak_count"],
node=node_name,
cluster=cluster_name)
del d
for gc, d in jvm["gc"]["collectors"].iteritems():
printmetric("jvm.gc.collection_count",
ts,
d["collection_count"],
gc=gc,
node=node_name,
cluster=cluster_name)
printmetric("jvm.gc.collection_time",
ts,
d["collection_time_in_millis"] / 1000.,
gc=gc,
node=node_name,
cluster=cluster_name)
del jvm
del d
if "network" in nstats:
for stat, value in nstats["network"]["tcp"].iteritems():
if utils.is_numeric(value):
printmetric("network.tcp." + stat,
ts,
value,
node=node_name,
cluster=cluster_name)
for stat, value in nstats["transport"].iteritems():
if utils.is_numeric(value):
printmetric("transport." + stat,
ts,
value,
node=node_name,
cluster=cluster_name)
# New in ES 0.17:
for stat, value in nstats.get("http", {}).iteritems():
if utils.is_numeric(value):
printmetric("http." + stat,
ts,
value,
node=node_name,
cluster=cluster_name)
del nstats
(cluster_name, nstats["cluster_name"]))
return 1
this_nodeid, nstats = nstats["nodes"].popitem()
if this_nodeid != nodeid:
utils.err("node ID changed from %r to %r" % (nodeid, this_nodeid))
return 1
is_master = nodeid == cluster_state(server)["master_node"]
printmetric("is_master", int(is_master))
if is_master:
ts = int(time.time()) # In case last call took a while.
cstats = cluster_health(server)
for stat, value in cstats.iteritems():
if stat == "status":
value = STATUS_MAP.get(value, -1)
elif not utils.is_numeric(value):
continue
printmetric("cluster." + stat, value)
if "os" in nstats:
ts = nstats["os"]["timestamp"] / 1000 # ms -> s
if "timestamp" in nstats:
ts = nstats["timestamp"] / 1000 # ms -> s
if "indices" in nstats:
indices = nstats["indices"]
if "docs" in indices:
printmetric("num_docs", indices["docs"]["count"])
if "store" in indices:
printmetric("indices.size", indices["store"]["size_in_bytes"])
if "indexing" in indices:
def _collect_server(server, version):
ts = int(time.time())
nstats = node_stats(server, version)
cluster_name = nstats["cluster_name"]
nodeid, nstats = nstats["nodes"].popitem()
node_name = nstats["name"]
is_master = nodeid == cluster_state(server)["master_node"]
printmetric("is_master", ts, int(is_master), node=node_name, cluster=cluster_name)
if is_master:
ts = int(time.time()) # In case last call took a while.
cstats = cluster_health(server)
for stat, value in cstats.iteritems():
if stat == "status":
value = STATUS_MAP.get(value, -1)
elif not utils.is_numeric(value):
continue
printmetric("cluster." + stat, ts, value, cluster=cluster_name)
if "os" in nstats:
ts = nstats["os"]["timestamp"] / 1000 # ms -> s
if "timestamp" in nstats:
ts = nstats["timestamp"] / 1000 # ms -> s
if "indices" in nstats:
indices = nstats["indices"]
if "docs" in indices:
printmetric("num_docs", ts, indices["docs"]["count"], node=node_name, cluster=cluster_name)
if "store" in indices:
printmetric("indices.size", ts, indices["store"]["size_in_bytes"], node=node_name, cluster=cluster_name)
if "indexing" in indices:
d = indices["indexing"]
printmetric("indexing.index_total", ts, d["index_total"], node=node_name, cluster=cluster_name)
printmetric("indexing.index_time", ts, d["index_time_in_millis"], node=node_name, cluster=cluster_name)
printmetric("indexing.index_current", ts, d["index_current"], node=node_name, cluster=cluster_name)
printmetric("indexing.delete_total", ts, d["delete_total"], node=node_name, cluster=cluster_name)
printmetric("indexing.delete_time_in_millis", ts, d["delete_time_in_millis"], node=node_name, cluster=cluster_name)
printmetric("indexing.delete_current", ts, d["delete_current"], node=node_name, cluster=cluster_name)
del d
if "get" in indices:
d = indices["get"]
printmetric("get.total", ts, d["total"], node=node_name, cluster=cluster_name)
printmetric("get.time", ts, d["time_in_millis"], node=node_name, cluster=cluster_name)
printmetric("get.exists_total", ts, d["exists_total"], node=node_name, cluster=cluster_name)
printmetric("get.exists_time", ts, d["exists_time_in_millis"], node=node_name, cluster=cluster_name)
printmetric("get.missing_total", ts, d["missing_total"], node=node_name, cluster=cluster_name)
printmetric("get.missing_time", ts, d["missing_time_in_millis"], node=node_name, cluster=cluster_name)
del d
if "search" in indices:
d = indices["search"]
printmetric("search.query_total", ts, d["query_total"], node=node_name, cluster=cluster_name)
printmetric("search.query_time", ts, d["query_time_in_millis"], node=node_name, cluster=cluster_name)
printmetric("search.query_current", ts, d["query_current"], node=node_name, cluster=cluster_name)
printmetric("search.fetch_total", ts, d["fetch_total"], node=node_name, cluster=cluster_name)
printmetric("search.fetch_time", ts, d["fetch_time_in_millis"], node=node_name, cluster=cluster_name)
printmetric("search.fetch_current", ts, d["fetch_current"], node=node_name, cluster=cluster_name)
del d
if "cache" in indices:
d = indices["cache"]
printmetric("cache.field.evictions", ts, d["field_evictions"], node=node_name, cluster=cluster_name)
printmetric("cache.field.size", ts, d["field_size_in_bytes"], node=node_name, cluster=cluster_name)
printmetric("cache.filter.count", ts, d["filter_count"], node=node_name, cluster=cluster_name)
printmetric("cache.filter.evictions", ts, d["filter_evictions"], node=node_name, cluster=cluster_name)
printmetric("cache.filter.size", ts, d["filter_size_in_bytes"], node=node_name, cluster=cluster_name)
del d
if "merges" in indices:
d = indices["merges"]
printmetric("merges.current", ts, d["current"], node=node_name, cluster=cluster_name)
printmetric("merges.total", ts, d["total"], node=node_name, cluster=cluster_name)
printmetric("merges.total_time", ts, d["total_time_in_millis"] / 1000., node=node_name, cluster=cluster_name)
del d
del indices
if "process" in nstats:
process = nstats["process"]
ts = process["timestamp"] / 1000 # ms -> s
open_fds = process.get("open_file_descriptors") # ES 0.17
if open_fds is None:
open_fds = process.get("fd") # ES 0.16
if open_fds is not None:
open_fds = open_fds["total"]
if open_fds is not None:
printmetric("process.open_file_descriptors", ts, open_fds, node=node_name, cluster=cluster_name)
if "cpu" in process:
d = process["cpu"]
printmetric("process.cpu.percent", ts, d["percent"], node=node_name, cluster=cluster_name)
printmetric("process.cpu.sys", ts, d["sys_in_millis"] / 1000., node=node_name, cluster=cluster_name)
printmetric("process.cpu.user", ts, d["user_in_millis"] / 1000., node=node_name, cluster=cluster_name)
del d
if "mem" in process:
d = process["mem"]
printmetric("process.mem.resident", ts, d["resident_in_bytes"], node=node_name, cluster=cluster_name)
printmetric("process.mem.shared", ts, d["share_in_bytes"], node=node_name, cluster=cluster_name)
printmetric("process.mem.total_virtual", ts, d["total_virtual_in_bytes"], node=node_name, cluster=cluster_name)
del d
del process
if "jvm" in nstats:
jvm = nstats["jvm"]
ts = jvm["timestamp"] / 1000 # ms -> s
if "mem" in jvm:
d = jvm["mem"]
printmetric("jvm.mem.heap_used", ts, d["heap_used_in_bytes"], node=node_name, cluster=cluster_name)
printmetric("jvm.mem.heap_committed", ts, d["heap_committed_in_bytes"], node=node_name, cluster=cluster_name)
printmetric("jvm.mem.non_heap_used", ts, d["non_heap_used_in_bytes"], node=node_name, cluster=cluster_name)
printmetric("jvm.mem.non_heap_committed", ts, d["non_heap_committed_in_bytes"], node=node_name, cluster=cluster_name)
del d
if "threads" in jvm:
d = jvm["threads"]
printmetric("jvm.threads.count", ts, d["count"], node=node_name, cluster=cluster_name)
printmetric("jvm.threads.peak_count", ts, d["peak_count"], node=node_name, cluster=cluster_name)
del d
for gc, d in jvm["gc"]["collectors"].iteritems():
printmetric("jvm.gc.collection_count", ts, d["collection_count"], gc=gc, node=node_name, cluster=cluster_name)
printmetric("jvm.gc.collection_time", ts,
d["collection_time_in_millis"] / 1000., gc=gc, node=node_name, cluster=cluster_name)
del jvm
del d
if "network" in nstats:
for stat, value in nstats["network"]["tcp"].iteritems():
if utils.is_numeric(value):
printmetric("network.tcp." + stat, ts, value, node=node_name, cluster=cluster_name)
for stat, value in nstats["transport"].iteritems():
if utils.is_numeric(value):
printmetric("transport." + stat, ts, value, node=node_name, cluster=cluster_name)
# New in ES 0.17:
for stat, value in nstats.get("http", {}).iteritems():
if utils.is_numeric(value):
printmetric("http." + stat, ts, value, node=node_name, cluster=cluster_name)
del nstats
