parse_trx.py script to parse response time

Author: root

scripts/parse_trx.py

@@ -1,24 +1,111 @@
 import sys
+import math
+import functools
 
 ins = open( sys.argv[1], "r" )
 array = {}
+response_times= {}
+
+array_10s = {}
+response_times_10s = {}
+
+array_60s = {}
+response_times_60s = {}
+
+def calms(f_sec,f_ms,s_sec,s_ms):
+	res=(int(f_sec)-int(s_sec))*1000 + (int(f_ms)-int(s_ms))/1000000
+	return res
+
+def percentile(N, percent, key=lambda x:x):
+    """
+    Find the percentile of a list of values.
+
+    @parameter N - is a list of values. Note N MUST BE already sorted.
+    @parameter percent - a float value from 0.0 to 1.0.
+    @parameter key - optional key function to compute value from each element of N.
+
+    @return - the percentile of the values
+    """
+    if not N:
+        return None
+    k = (len(N)-1) * percent
+    f = math.floor(k)
+    c = math.ceil(k)
+    if f == c:
+        return key(N[int(k)])
+    d0 = key(N[int(f)]) * (c-k)
+    d1 = key(N[int(c)]) * (k-f)
+    return d0+d1
+
 if len(sys.argv)>=2:
 	pref=sys.argv[2]
 else:
 	pref=""
+
 for line in ins:
 	data=line.split()
-	if array.has_key(data[3]):
-		array[data[3]] = array[data[3]]+1
+	current_sec = int(data[3]);
+	if array.has_key(current_sec):
+		array[current_sec] = array[current_sec]+1
+		response_times[current_sec].append(calms(data[3],data[4],data[6],data[7]))
+	else:
+		array[current_sec] = 1
+		response_times[current_sec]=[calms(data[3],data[4],data[6],data[7])]
+	cur_10s = current_sec/10
+	if array_10s.has_key(cur_10s):
+		array_10s[cur_10s] = array_10s[cur_10s]+1
+		response_times_10s[cur_10s].append(calms(data[3],data[4],data[6],data[7]))
+	else:
+		array_10s[cur_10s] = 1
+		response_times_10s[cur_10s]=[calms(data[3],data[4],data[6],data[7])]
+		# print calms(data[3],data[4],data[6],data[7])
+	cur_60s = current_sec/60
+	if array_60s.has_key(cur_60s):
+		array_60s[cur_60s] = array_60s[cur_60s]+1
+		response_times_60s[cur_60s].append(calms(data[3],data[4],data[6],data[7]))
+	else:
+		array_60s[cur_60s] = 1
+		response_times_60s[cur_60s]=[calms(data[3],data[4],data[6],data[7])]
+
+minsec=min(array.keys())
+maxsec=max(array.keys())
+i=minsec
+while i<=maxsec:
+	if array.has_key(i):
+		# print str(i),len(response_times[str(i)].sort())
+		response_times[i].sort()
+		pct99=percentile(response_times[i],0.99)
+		print pref,i-minsec,array[i],pct99
+	else:
+		print pref,i-minsec,0
+	i=i+1
+
+print "========== 10 sec ============="
+
+minsec=min(array_10s.keys())
+maxsec=max(array_10s.keys())
+i=minsec
+while i<=maxsec:
+	if array_10s.has_key(i):
+		# print str(i),len(response_times[str(i)].sort())
+		response_times_10s[i].sort()
+		pct99=percentile(response_times_10s[i],0.99)
+		print pref,i-minsec,array_10s[i],pct99
 	else:
-		array[data[3]] = 1
+		print pref,i-minsec,0
+	i=i+1
+
+print "========== 60 sec ============="
 
-minsec=int(min(array.keys()))
-maxsec=int(max(array.keys()))
+minsec=min(array_60s.keys())
+maxsec=max(array_60s.keys())
 i=minsec
 while i<=maxsec:
-	if array.has_key(str(i)):
-		print pref,i-minsec,array[str(i)]
+	if array_60s.has_key(i):
+		# print str(i),len(response_times[str(i)].sort())
+		response_times_60s[i].sort()
+		pct99=percentile(response_times_60s[i],0.99)
+		print pref,i-minsec,array_60s[i],pct99
 	else:
 		print pref,i-minsec,0
 	i=i+1