193 lines · python
1# event_analyzing_sample.py: general event handler in python2# SPDX-License-Identifier: GPL-2.03#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, but6# providing end user/developer a flexible way to analyze the events other7# than trace points.8#9# The 2 database related functions in this script just show how to gather10# the basic information, and users can modify and write their own functions11# according to their specific requirement.12#13# The first function "show_general_events" just does a basic grouping for all14# generic events with the help of sqlite, and the 2nd one "show_pebs_ll" is15# for a x86 HW PMU event: PEBS with load latency data.16#17 18from __future__ import print_function19 20import os21import sys22import math23import struct24import sqlite325 26sys.path.append(os.environ['PERF_EXEC_PATH'] + \27 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')28 29from perf_trace_context import *30from EventClass import *31 32#33# If the perf.data has a big number of samples, then the insert operation34# will be very time consuming (about 10+ minutes for 10000 samples) if the35# .db database is on disk. Move the .db file to RAM based FS to speedup36# the handling, which will cut the time down to several seconds.37#38con = sqlite3.connect("/dev/shm/perf.db")39con.isolation_level = None40 41def trace_begin():42 print("In trace_begin:\n")43 44 #45 # Will create several tables at the start, pebs_ll is for PEBS data with46 # load latency info, while gen_events is for general event.47 #48 con.execute("""49 create table if not exists gen_events (50 name text,51 symbol text,52 comm text,53 dso text54 );""")55 con.execute("""56 create table if not exists pebs_ll (57 name text,58 symbol text,59 comm text,60 dso text,61 flags integer,62 ip integer,63 status integer,64 dse integer,65 dla integer,66 lat integer67 );""")68 69#70# Create and insert event object to a database so that user could71# do more analysis with simple database commands.72#73def process_event(param_dict):74 event_attr = param_dict["attr"]75 sample = param_dict["sample"]76 raw_buf = param_dict["raw_buf"]77 comm = param_dict["comm"]78 name = param_dict["ev_name"]79 80 # Symbol and dso info are not always resolved81 if ("dso" in param_dict):82 dso = param_dict["dso"]83 else:84 dso = "Unknown_dso"85 86 if ("symbol" in param_dict):87 symbol = param_dict["symbol"]88 else:89 symbol = "Unknown_symbol"90 91 # Create the event object and insert it to the right table in database92 event = create_event(name, comm, dso, symbol, raw_buf)93 insert_db(event)94 95def insert_db(event):96 if event.ev_type == EVTYPE_GENERIC:97 con.execute("insert into gen_events values(?, ?, ?, ?)",98 (event.name, event.symbol, event.comm, event.dso))99 elif event.ev_type == EVTYPE_PEBS_LL:100 event.ip &= 0x7fffffffffffffff101 event.dla &= 0x7fffffffffffffff102 con.execute("insert into pebs_ll values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",103 (event.name, event.symbol, event.comm, event.dso, event.flags,104 event.ip, event.status, event.dse, event.dla, event.lat))105 106def trace_end():107 print("In trace_end:\n")108 # We show the basic info for the 2 type of event classes109 show_general_events()110 show_pebs_ll()111 con.close()112 113#114# As the event number may be very big, so we can't use linear way115# to show the histogram in real number, but use a log2 algorithm.116#117 118def num2sym(num):119 # Each number will have at least one '#'120 snum = '#' * (int)(math.log(num, 2) + 1)121 return snum122 123def show_general_events():124 125 # Check the total record number in the table126 count = con.execute("select count(*) from gen_events")127 for t in count:128 print("There is %d records in gen_events table" % t[0])129 if t[0] == 0:130 return131 132 print("Statistics about the general events grouped by thread/symbol/dso: \n")133 134 # Group by thread135 commq = con.execute("select comm, count(comm) from gen_events group by comm order by -count(comm)")136 print("\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42))137 for row in commq:138 print("%16s %8d %s" % (row[0], row[1], num2sym(row[1])))139 140 # Group by symbol141 print("\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58))142 symbolq = con.execute("select symbol, count(symbol) from gen_events group by symbol order by -count(symbol)")143 for row in symbolq:144 print("%32s %8d %s" % (row[0], row[1], num2sym(row[1])))145 146 # Group by dso147 print("\n%40s %8s %16s\n%s" % ("dso", "number", "histogram", "="*74))148 dsoq = con.execute("select dso, count(dso) from gen_events group by dso order by -count(dso)")149 for row in dsoq:150 print("%40s %8d %s" % (row[0], row[1], num2sym(row[1])))151 152#153# This function just shows the basic info, and we could do more with the154# data in the tables, like checking the function parameters when some155# big latency events happen.156#157def show_pebs_ll():158 159 count = con.execute("select count(*) from pebs_ll")160 for t in count:161 print("There is %d records in pebs_ll table" % t[0])162 if t[0] == 0:163 return164 165 print("Statistics about the PEBS Load Latency events grouped by thread/symbol/dse/latency: \n")166 167 # Group by thread168 commq = con.execute("select comm, count(comm) from pebs_ll group by comm order by -count(comm)")169 print("\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42))170 for row in commq:171 print("%16s %8d %s" % (row[0], row[1], num2sym(row[1])))172 173 # Group by symbol174 print("\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58))175 symbolq = con.execute("select symbol, count(symbol) from pebs_ll group by symbol order by -count(symbol)")176 for row in symbolq:177 print("%32s %8d %s" % (row[0], row[1], num2sym(row[1])))178 179 # Group by dse180 dseq = con.execute("select dse, count(dse) from pebs_ll group by dse order by -count(dse)")181 print("\n%32s %8s %16s\n%s" % ("dse", "number", "histogram", "="*58))182 for row in dseq:183 print("%32s %8d %s" % (row[0], row[1], num2sym(row[1])))184 185 # Group by latency186 latq = con.execute("select lat, count(lat) from pebs_ll group by lat order by lat")187 print("\n%32s %8s %16s\n%s" % ("latency", "number", "histogram", "="*58))188 for row in latq:189 print("%32s %8d %s" % (row[0], row[1], num2sym(row[1])))190 191def trace_unhandled(event_name, context, event_fields_dict):192 print (' '.join(['%s=%s'%(k,str(v))for k,v in sorted(event_fields_dict.items())]))193