Add field key length output by field type in schema_sizing Starlark s…

…cript (influxdata#8934)

plugins/processors/starlark/testdata/schema_sizing.star

@@ -5,7 +5,7 @@
 # logstash,environment_id=EN456,property_id=PR789,request_type=ingress,stack_id=engd asn=1313i,cache_response_code=202i,colo_code="LAX",colo_id=12i,compute_time=28736i,edge_end_timestamp=1611085500320i,edge_start_timestamp=1611085496208i,id="1b5c67ed-dfd0-4d30-99bd-84f0a9c5297b_76af1809-29d1-4b35-a0cf-39797458275c",parent_ray_id="00",processing_details="ok",rate_limit_id=0i,ray_id="76af1809-29d1-4b35-a0cf-39797458275c",request_bytes=7777i,request_host="engd-08364a825824e04f0a494115.reactorstream.dev",request_id="1b5c67ed-dfd0-4d30-99bd-84f0a9c5297b",request_result="succeeded",request_uri="/ENafcb2798a9be4bb7bfddbf35c374db15",response_code=200i,subrequest=false,subrequest_count=1i,user_agent="curl/7.64.1" 1611085496208
 #
 # Example Output:
-# sizing,measurement=logstash,environment_id=EN456,property_id=PR789,request_type=ingress,stack_id=engd tag_count=4,tag_key_avg_length=11.25,tag_value_avg_length=5.25,int_avg_length=4.9,int_count=10,bool_avg_length=5,bool_count=1,str_avg_length=25.4,str_count=10 1611085496208
+# sizing,measurement=logstash,environment_id=EN456,property_id=PR789,request_type=ingress,stack_id=engd tag_count=4,tag_key_avg_length=11.25,tag_value_avg_length=5.25,int_key_avg_length=13.4,int_avg_length=4.9,int_count=10,bool_key_avg_length=10,bool_avg_length=5,bool_count=1,str_key_avg_length=10.5,str_avg_length=25.4,str_count=10 1611085496208
 
 def apply(metric):
     new_metric = Metric("sizing")
@@ -20,7 +20,7 @@ def apply(metric):
 
     ints, floats, bools, strs = [], [], [], []
     for field in metric.fields.items():
-        value = field[1]
+        key, value = field[0], field[1]
         if type(value) == "int":
             ints.append(field)
         elif type(value) == "float":
@@ -31,26 +31,38 @@ def apply(metric):
             strs.append(field)
 
     if len(ints) > 0:
+        int_keys = [i[0] for i in ints]
         int_vals = [i[1] for i in ints]
+        produce_pairs(new_metric, int_keys, "int", key=True)
         produce_pairs(new_metric, int_vals, "int")
     if len(floats) > 0:
+        float_keys = [i[0] for i in floats]
         float_vals = [i[1] for i in floats]
+        produce_pairs(new_metric, float_keys, "float", key=True)
         produce_pairs(new_metric, float_vals, "float")
     if len(bools) > 0:
+        bool_keys = [i[0] for i in bools]
         bool_vals = [i[1] for i in bools]
+        produce_pairs(new_metric, bool_keys, "bool", key=True)
         produce_pairs(new_metric, bool_vals, "bool")     
     if len(strs) > 0:
+        str_keys = [i[0] for i in strs]
         str_vals = [i[1] for i in strs]
+        produce_pairs(new_metric, str_keys, "str", key=True)
         produce_pairs(new_metric, str_vals, "str")
 
+
     return new_metric
 
-def produce_pairs(metric, li, field_type):
+def produce_pairs(metric, li, field_type, key=False):
     lens = elem_lengths(li)
     counts = count_lengths(lens)
+    metric.fields["{}_count".format(field_type)]               = float(len(li))
+    if key:
+        metric.fields["{}_key_avg_length".format(field_type)]  = float(mean(lens))     
+    else:
+        metric.fields["{}_avg_length".format(field_type)]      = float(mean(lens))
 
-    metric.fields["{}_avg_length".format(field_type)]  = float(mean(lens))
-    metric.fields["{}_count".format(field_type)]       = float(len(li))
 
 def elem_lengths(li):
     if type(li[0]) in ("int", "float", "bool"):