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Diffstat (limited to 'tools/perf/scripts/python/event_analyzing_sample.py')
| -rw-r--r-- | tools/perf/scripts/python/event_analyzing_sample.py | 189 |
1 files changed, 189 insertions, 0 deletions
diff --git a/tools/perf/scripts/python/event_analyzing_sample.py b/tools/perf/scripts/python/event_analyzing_sample.py new file mode 100644 index 000000000000..163c39fa12d9 --- /dev/null +++ b/tools/perf/scripts/python/event_analyzing_sample.py @@ -0,0 +1,189 @@ +# event_analyzing_sample.py: general event handler in python +# +# Current perf report is already very powerful with the annotation integrated, +# and this script is not trying to be as powerful as perf report, but +# providing end user/developer a flexible way to analyze the events other +# than trace points. +# +# The 2 database related functions in this script just show how to gather +# the basic information, and users can modify and write their own functions +# according to their specific requirement. +# +# The first function "show_general_events" just does a basic grouping for all +# generic events with the help of sqlite, and the 2nd one "show_pebs_ll" is +# for a x86 HW PMU event: PEBS with load latency data. +# + +import os +import sys +import math +import struct +import sqlite3 + +sys.path.append(os.environ['PERF_EXEC_PATH'] + \ + '/scripts/python/Perf-Trace-Util/lib/Perf/Trace') + +from perf_trace_context import * +from EventClass import * + +# +# If the perf.data has a big number of samples, then the insert operation +# will be very time consuming (about 10+ minutes for 10000 samples) if the +# .db database is on disk. Move the .db file to RAM based FS to speedup +# the handling, which will cut the time down to several seconds. +# +con = sqlite3.connect("/dev/shm/perf.db") +con.isolation_level = None + +def trace_begin(): + print "In trace_begin:\n" + + # + # Will create several tables at the start, pebs_ll is for PEBS data with + # load latency info, while gen_events is for general event. + # + con.execute(""" + create table if not exists gen_events ( + name text, + symbol text, + comm text, + dso text + );""") + con.execute(""" + create table if not exists pebs_ll ( + name text, + symbol text, + comm text, + dso text, + flags integer, + ip integer, + status integer, + dse integer, + dla integer, + lat integer + );""") + +# +# Create and insert event object to a database so that user could +# do more analysis with simple database commands. +# +def process_event(param_dict): + event_attr = param_dict["attr"] + sample = param_dict["sample"] + raw_buf = param_dict["raw_buf"] + comm = param_dict["comm"] + name = param_dict["ev_name"] + + # Symbol and dso info are not always resolved + if (param_dict.has_key("dso")): + dso = param_dict["dso"] + else: + dso = "Unknown_dso" + + if (param_dict.has_key("symbol")): + symbol = param_dict["symbol"] + else: + symbol = "Unknown_symbol" + + # Create the event object and insert it to the right table in database + event = create_event(name, comm, dso, symbol, raw_buf) + insert_db(event) + +def insert_db(event): + if event.ev_type == EVTYPE_GENERIC: + con.execute("insert into gen_events values(?, ?, ?, ?)", + (event.name, event.symbol, event.comm, event.dso)) + elif event.ev_type == EVTYPE_PEBS_LL: + event.ip &= 0x7fffffffffffffff + event.dla &= 0x7fffffffffffffff + con.execute("insert into pebs_ll values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", + (event.name, event.symbol, event.comm, event.dso, event.flags, + event.ip, event.status, event.dse, event.dla, event.lat)) + +def trace_end(): + print "In trace_end:\n" + # We show the basic info for the 2 type of event classes + show_general_events() + show_pebs_ll() + con.close() + +# +# As the event number may be very big, so we can't use linear way +# to show the histogram in real number, but use a log2 algorithm. +# + +def num2sym(num): + # Each number will have at least one '#' + snum = '#' * (int)(math.log(num, 2) + 1) + return snum + +def show_general_events(): + + # Check the total record number in the table + count = con.execute("select count(*) from gen_events") + for t in count: + print "There is %d records in gen_events table" % t[0] + if t[0] == 0: + return + + print "Statistics about the general events grouped by thread/symbol/dso: \n" + + # Group by thread + commq = con.execute("select comm, count(comm) from gen_events group by comm order by -count(comm)") + print "\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42) + for row in commq: + print "%16s %8d %s" % (row[0], row[1], num2sym(row[1])) + + # Group by symbol + print "\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58) + symbolq = con.execute("select symbol, count(symbol) from gen_events group by symbol order by -count(symbol)") + for row in symbolq: + print "%32s %8d %s" % (row[0], row[1], num2sym(row[1])) + + # Group by dso + print "\n%40s %8s %16s\n%s" % ("dso", "number", "histogram", "="*74) + dsoq = con.execute("select dso, count(dso) from gen_events group by dso order by -count(dso)") + for row in dsoq: + print "%40s %8d %s" % (row[0], row[1], num2sym(row[1])) + +# +# This function just shows the basic info, and we could do more with the +# data in the tables, like checking the function parameters when some +# big latency events happen. +# +def show_pebs_ll(): + + count = con.execute("select count(*) from pebs_ll") + for t in count: + print "There is %d records in pebs_ll table" % t[0] + if t[0] == 0: + return + + print "Statistics about the PEBS Load Latency events grouped by thread/symbol/dse/latency: \n" + + # Group by thread + commq = con.execute("select comm, count(comm) from pebs_ll group by comm order by -count(comm)") + print "\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42) + for row in commq: + print "%16s %8d %s" % (row[0], row[1], num2sym(row[1])) + + # Group by symbol + print "\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58) + symbolq = con.execute("select symbol, count(symbol) from pebs_ll group by symbol order by -count(symbol)") + for row in symbolq: + print "%32s %8d %s" % (row[0], row[1], num2sym(row[1])) + + # Group by dse + dseq = con.execute("select dse, count(dse) from pebs_ll group by dse order by -count(dse)") + print "\n%32s %8s %16s\n%s" % ("dse", "number", "histogram", "="*58) + for row in dseq: + print "%32s %8d %s" % (row[0], row[1], num2sym(row[1])) + + # Group by latency + latq = con.execute("select lat, count(lat) from pebs_ll group by lat order by lat") + print "\n%32s %8s %16s\n%s" % ("latency", "number", "histogram", "="*58) + for row in latq: + print "%32s %8d %s" % (row[0], row[1], num2sym(row[1])) + +def trace_unhandled(event_name, context, event_fields_dict): + print ' '.join(['%s=%s'%(k,str(v))for k,v in sorted(event_fields_dict.items())]) |