1 # event_analyzing_sample.py: general event handler in python
3 # Current perf report is already very powerful with the annotation integrated,
4 # and this script is not trying to be as powerful as perf report, but
5 # providing end user/developer a flexible way to analyze the events other
8 # The 2 database related functions in this script just show how to gather
9 # the basic information, and users can modify and write their own functions
10 # according to their specific requirement.
12 # The first function "show_general_events" just does a basic grouping for all
13 # generic events with the help of sqlite, and the 2nd one "show_pebs_ll" is
14 # for a x86 HW PMU event: PEBS with load latency data.
23 sys
.path
.append(os
.environ
['PERF_EXEC_PATH'] + \
24 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
26 from perf_trace_context
import *
27 from EventClass
import *
30 # If the perf.data has a big number of samples, then the insert operation
31 # will be very time consuming (about 10+ minutes for 10000 samples) if the
32 # .db database is on disk. Move the .db file to RAM based FS to speedup
33 # the handling, which will cut the time down to several seconds.
35 con
= sqlite3
.connect("/dev/shm/perf.db")
36 con
.isolation_level
= None
39 print "In trace_begin:\n"
42 # Will create several tables at the start, pebs_ll is for PEBS data with
43 # load latency info, while gen_events is for general event.
46 create table if not exists gen_events (
53 create table if not exists pebs_ll (
67 # Create and insert event object to a database so that user could
68 # do more analysis with simple database commands.
70 def process_event(param_dict
):
71 event_attr
= param_dict
["attr"]
72 sample
= param_dict
["sample"]
73 raw_buf
= param_dict
["raw_buf"]
74 comm
= param_dict
["comm"]
75 name
= param_dict
["ev_name"]
77 # Symbol and dso info are not always resolved
78 if (param_dict
.has_key("dso")):
79 dso
= param_dict
["dso"]
83 if (param_dict
.has_key("symbol")):
84 symbol
= param_dict
["symbol"]
86 symbol
= "Unknown_symbol"
88 # Create the event object and insert it to the right table in database
89 event
= create_event(name
, comm
, dso
, symbol
, raw_buf
)
93 if event
.ev_type
== EVTYPE_GENERIC
:
94 con
.execute("insert into gen_events values(?, ?, ?, ?)",
95 (event
.name
, event
.symbol
, event
.comm
, event
.dso
))
96 elif event
.ev_type
== EVTYPE_PEBS_LL
:
97 event
.ip
&= 0x7fffffffffffffff
98 event
.dla
&= 0x7fffffffffffffff
99 con
.execute("insert into pebs_ll values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
100 (event
.name
, event
.symbol
, event
.comm
, event
.dso
, event
.flags
,
101 event
.ip
, event
.status
, event
.dse
, event
.dla
, event
.lat
))
104 print "In trace_end:\n"
105 # We show the basic info for the 2 type of event classes
106 show_general_events()
111 # As the event number may be very big, so we can't use linear way
112 # to show the histogram in real number, but use a log2 algorithm.
116 # Each number will have at least one '#'
117 snum
= '#' * (int)(math
.log(num
, 2) + 1)
120 def show_general_events():
122 # Check the total record number in the table
123 count
= con
.execute("select count(*) from gen_events")
125 print "There is %d records in gen_events table" % t
[0]
129 print "Statistics about the general events grouped by thread/symbol/dso: \n"
132 commq
= con
.execute("select comm, count(comm) from gen_events group by comm order by -count(comm)")
133 print "\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42)
135 print "%16s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
138 print "\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58)
139 symbolq
= con
.execute("select symbol, count(symbol) from gen_events group by symbol order by -count(symbol)")
141 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
144 print "\n%40s %8s %16s\n%s" % ("dso", "number", "histogram", "="*74)
145 dsoq
= con
.execute("select dso, count(dso) from gen_events group by dso order by -count(dso)")
147 print "%40s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
150 # This function just shows the basic info, and we could do more with the
151 # data in the tables, like checking the function parameters when some
152 # big latency events happen.
156 count
= con
.execute("select count(*) from pebs_ll")
158 print "There is %d records in pebs_ll table" % t
[0]
162 print "Statistics about the PEBS Load Latency events grouped by thread/symbol/dse/latency: \n"
165 commq
= con
.execute("select comm, count(comm) from pebs_ll group by comm order by -count(comm)")
166 print "\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42)
168 print "%16s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
171 print "\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58)
172 symbolq
= con
.execute("select symbol, count(symbol) from pebs_ll group by symbol order by -count(symbol)")
174 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
177 dseq
= con
.execute("select dse, count(dse) from pebs_ll group by dse order by -count(dse)")
178 print "\n%32s %8s %16s\n%s" % ("dse", "number", "histogram", "="*58)
180 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
183 latq
= con
.execute("select lat, count(lat) from pebs_ll group by lat order by lat")
184 print "\n%32s %8s %16s\n%s" % ("latency", "number", "histogram", "="*58)
186 print "%32s %8d %s" % (row
[0], row
[1], num2sym(row
[1]))
188 def trace_unhandled(event_name
, context
, event_fields_dict
):
189 print ' '.join(['%s=%s'%(k
,str(v
))for k
,v
in sorted(event_fields_dict
.items())])