1 # event_analyzing_sample.py: general event handler in python
2 # SPDX-License-Identifier: GPL-2.0
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
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.
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.
24 sys
.path
.append(os
.environ
['PERF_EXEC_PATH'] + \
25 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
27 from perf_trace_context
import *
28 from EventClass
import *
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.
36 con
= sqlite3
.connect("/dev/shm/perf.db")
37 con
.isolation_level
= None
40 print "In trace_begin:\n"
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.
47 create table if not exists gen_events (
54 create table if not exists pebs_ll (
68 # Create and insert event object to a database so that user could
69 # do more analysis with simple database commands.
71 def 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"]
78 # Symbol and dso info are not always resolved
79 if (param_dict
.has_key("dso")):
80 dso
= param_dict
["dso"]
84 if (param_dict
.has_key("symbol")):
85 symbol
= param_dict
["symbol"]
87 symbol
= "Unknown_symbol"
89 # Create the event object and insert it to the right table in database
90 event
= create_event(name
, comm
, dso
, symbol
, raw_buf
)
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
))
105 print "In trace_end:\n"
106 # We show the basic info for the 2 type of event classes
107 show_general_events()
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.
117 # Each number will have at least one '#'
118 snum
= '#' * (int)(math
.log(num
, 2) + 1)
121 def show_general_events():
123 # Check the total record number in the table
124 count
= con
.execute("select count(*) from gen_events")
126 print "There is %d records in gen_events table" % t
[0]
130 print "Statistics about the general events grouped by thread/symbol/dso: \n"
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)
136 print "%16s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
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)")
142 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
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)")
148 print "%40s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
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.
157 count
= con
.execute("select count(*) from pebs_ll")
159 print "There is %d records in pebs_ll table" % t
[0]
163 print "Statistics about the PEBS Load Latency events grouped by thread/symbol/dse/latency: \n"
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)
169 print "%16s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
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)")
175 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
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)
181 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
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)
187 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
189 def 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())])