projects/linux·blob 0d55ec6f · refs

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1# event_analyzing_sample.py: general event handler in python
2# SPDX-License-Identifier: GPL-2.0
3#
4# Current perf report is already very powerful with the annotation integrated,
5# and this script is not trying to be as powerful as perf report, but
6# providing end user/developer a flexible way to analyze the events other
7# than trace points.
8#
9# The 2 database related functions in this script just show how to gather
10# the basic information, and users can modify and write their own functions
11# according to their specific requirement.
12#
13# The first function "show_general_events" just does a basic grouping for all
14# generic events with the help of sqlite, and the 2nd one "show_pebs_ll" is
15# for a x86 HW PMU event: PEBS with load latency data.
16#
17
18import os
19import sys
20import math
21import struct
22import sqlite3
23
24sys.path.append(os.environ['PERF_EXEC_PATH'] + \
25 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
26
27from perf_trace_context import *
28from EventClass import *
29
30#
31# If the perf.data has a big number of samples, then the insert operation
32# will be very time consuming (about 10+ minutes for 10000 samples) if the
33# .db database is on disk. Move the .db file to RAM based FS to speedup
34# the handling, which will cut the time down to several seconds.
35#
36con = sqlite3.connect("/dev/shm/perf.db")
37con.isolation_level = None
38
39def trace_begin():
40 print "In trace_begin:\n"
41
42 #
43 # Will create several tables at the start, pebs_ll is for PEBS data with
44 # load latency info, while gen_events is for general event.
45 #
46 con.execute("""
47 create table if not exists gen_events (
48 name text,
49 symbol text,
50 comm text,
51 dso text
52 );""")
53 con.execute("""
54 create table if not exists pebs_ll (
55 name text,
56 symbol text,
57 comm text,
58 dso text,
59 flags integer,
60 ip integer,
61 status integer,
62 dse integer,
63 dla integer,
64 lat integer
65 );""")
66
67#
68# Create and insert event object to a database so that user could
69# do more analysis with simple database commands.
70#
71def process_event(param_dict):
72 event_attr = param_dict["attr"]
73 sample = param_dict["sample"]
74 raw_buf = param_dict["raw_buf"]
75 comm = param_dict["comm"]
76 name = param_dict["ev_name"]
77
78 # Symbol and dso info are not always resolved
79 if (param_dict.has_key("dso")):
80 dso = param_dict["dso"]
81 else:
82 dso = "Unknown_dso"
83
84 if (param_dict.has_key("symbol")):
85 symbol = param_dict["symbol"]
86 else:
87 symbol = "Unknown_symbol"
88
89 # Create the event object and insert it to the right table in database
90 event = create_event(name, comm, dso, symbol, raw_buf)
91 insert_db(event)
92
93def insert_db(event):
94 if event.ev_type == EVTYPE_GENERIC:
95 con.execute("insert into gen_events values(?, ?, ?, ?)",
96 (event.name, event.symbol, event.comm, event.dso))
97 elif event.ev_type == EVTYPE_PEBS_LL:
98 event.ip &= 0x7fffffffffffffff
99 event.dla &= 0x7fffffffffffffff
100 con.execute("insert into pebs_ll values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
101 (event.name, event.symbol, event.comm, event.dso, event.flags,
102 event.ip, event.status, event.dse, event.dla, event.lat))
103
104def trace_end():
105 print "In trace_end:\n"
106 # We show the basic info for the 2 type of event classes
107 show_general_events()
108 show_pebs_ll()
109 con.close()
110
111#
112# As the event number may be very big, so we can't use linear way
113# to show the histogram in real number, but use a log2 algorithm.
114#
115
116def num2sym(num):
117 # Each number will have at least one '#'
118 snum = '#' * (int)(math.log(num, 2) + 1)
119 return snum
120
121def show_general_events():
122
123 # Check the total record number in the table
124 count = con.execute("select count(*) from gen_events")
125 for t in count:
126 print "There is %d records in gen_events table" % t[0]
127 if t[0] == 0:
128 return
129
130 print "Statistics about the general events grouped by thread/symbol/dso: \n"
131
132 # Group by thread
133 commq = con.execute("select comm, count(comm) from gen_events group by comm order by -count(comm)")
134 print "\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42)
135 for row in commq:
136 print "%16s %8d %s" % (row[0], row[1], num2sym(row[1]))
137
138 # Group by symbol
139 print "\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58)
140 symbolq = con.execute("select symbol, count(symbol) from gen_events group by symbol order by -count(symbol)")
141 for row in symbolq:
142 print "%32s %8d %s" % (row[0], row[1], num2sym(row[1]))
143
144 # Group by dso
145 print "\n%40s %8s %16s\n%s" % ("dso", "number", "histogram", "="*74)
146 dsoq = con.execute("select dso, count(dso) from gen_events group by dso order by -count(dso)")
147 for row in dsoq:
148 print "%40s %8d %s" % (row[0], row[1], num2sym(row[1]))
149
150#
151# This function just shows the basic info, and we could do more with the
152# data in the tables, like checking the function parameters when some
153# big latency events happen.
154#
155def show_pebs_ll():
156
157 count = con.execute("select count(*) from pebs_ll")
158 for t in count:
159 print "There is %d records in pebs_ll table" % t[0]
160 if t[0] == 0:
161 return
162
163 print "Statistics about the PEBS Load Latency events grouped by thread/symbol/dse/latency: \n"
164
165 # Group by thread
166 commq = con.execute("select comm, count(comm) from pebs_ll group by comm order by -count(comm)")
167 print "\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42)
168 for row in commq:
169 print "%16s %8d %s" % (row[0], row[1], num2sym(row[1]))
170
171 # Group by symbol
172 print "\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58)
173 symbolq = con.execute("select symbol, count(symbol) from pebs_ll group by symbol order by -count(symbol)")
174 for row in symbolq:
175 print "%32s %8d %s" % (row[0], row[1], num2sym(row[1]))
176
177 # Group by dse
178 dseq = con.execute("select dse, count(dse) from pebs_ll group by dse order by -count(dse)")
179 print "\n%32s %8s %16s\n%s" % ("dse", "number", "histogram", "="*58)
180 for row in dseq:
181 print "%32s %8d %s" % (row[0], row[1], num2sym(row[1]))
182
183 # Group by latency
184 latq = con.execute("select lat, count(lat) from pebs_ll group by lat order by lat")
185 print "\n%32s %8s %16s\n%s" % ("latency", "number", "histogram", "="*58)
186 for row in latq:
187 print "%32s %8d %s" % (row[0], row[1], num2sym(row[1]))
188
189def trace_unhandled(event_name, context, event_fields_dict):
190 print ' '.join(['%s=%s'%(k,str(v))for k,v in sorted(event_fields_dict.items())])