update

celery_stats/es_status.py

@@ -73,7 +73,9 @@ def get_node_status(ip):
         cpu_5m = data["os"]["cpu"]["load_average"]['5m']
         cpu_15m = data["os"]["cpu"]["load_average"]['15m']
         young_gc = data["jvm"]["gc"]["collectors"]['young']['collection_count']
-        yield node_name, ip, query_time, query_current, fetch_current, cpu_percent, cpu_1m, cpu_5m, cpu_15m, young_gc
+        young_gc_ms = data["jvm"]["gc"]["collectors"]['young']['collection_time_in_millis']
+        young_gc_per_ms = int(young_gc_ms/young_gc)
+        yield node_name, ip, query_time, query_current, fetch_current, cpu_percent, cpu_1m, cpu_5m, cpu_15m, young_gc_per_ms
 
 
 def parse_cluster_stats(data):
@@ -91,7 +93,7 @@ def parse_node_stats(data):
     node_name, ip, query_time, query_current, fetch_current, cpu_percent, cpu_1m, cpu_5m, cpu_15m, young_gc = data
     if cpu_1m >= cpu_top or cpu_5m >= cpu_top or cpu_15m >= cpu_top:
         res_str += "{name}节点CPU使用率预警 1m {cpu_1m} 5m {cpu_5m} 15m {cpu_15m} \n" \
-                   "目前 query_current为{query_current} fetch_current为{fetch_current} young_gc为{young_gc}".format(cpu_1m=str(int(cpu_1m*100))+"%",name=node_name,
+                   "目前 query_current为{query_current} fetch_current为{fetch_current} young_gc为{young_gc}ms".format(cpu_1m=str(int(cpu_1m*100))+"%",name=node_name,
                                                                              cpu_5m=str(int(cpu_5m*100))+"%",
                                                                              cpu_15m= str(int(cpu_15m*100))+"%",
                    query_current=str(query_current),fetch_current=str(fetch_current),young_gc=str(young_gc))