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192 lines
7.3 KiB
192 lines
7.3 KiB
# event_analyzing_sample.py: general event handler in python |
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# SPDX-License-Identifier: GPL-2.0 |
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# |
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# Current perf report is already very powerful with the annotation integrated, |
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# and this script is not trying to be as powerful as perf report, but |
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# providing end user/developer a flexible way to analyze the events other |
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# than trace points. |
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# |
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# The 2 database related functions in this script just show how to gather |
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# the basic information, and users can modify and write their own functions |
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# according to their specific requirement. |
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# |
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# The first function "show_general_events" just does a basic grouping for all |
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# generic events with the help of sqlite, and the 2nd one "show_pebs_ll" is |
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# for a x86 HW PMU event: PEBS with load latency data. |
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# |
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from __future__ import print_function |
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import os |
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import sys |
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import math |
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import struct |
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import sqlite3 |
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sys.path.append(os.environ['PERF_EXEC_PATH'] + \ |
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'/scripts/python/Perf-Trace-Util/lib/Perf/Trace') |
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from perf_trace_context import * |
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from EventClass import * |
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# |
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# If the perf.data has a big number of samples, then the insert operation |
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# will be very time consuming (about 10+ minutes for 10000 samples) if the |
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# .db database is on disk. Move the .db file to RAM based FS to speedup |
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# the handling, which will cut the time down to several seconds. |
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# |
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con = sqlite3.connect("/dev/shm/perf.db") |
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con.isolation_level = None |
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def trace_begin(): |
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print("In trace_begin:\n") |
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# |
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# Will create several tables at the start, pebs_ll is for PEBS data with |
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# load latency info, while gen_events is for general event. |
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# |
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con.execute(""" |
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create table if not exists gen_events ( |
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name text, |
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symbol text, |
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comm text, |
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dso text |
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);""") |
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con.execute(""" |
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create table if not exists pebs_ll ( |
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name text, |
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symbol text, |
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comm text, |
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dso text, |
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flags integer, |
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ip integer, |
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status integer, |
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dse integer, |
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dla integer, |
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lat integer |
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);""") |
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# |
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# Create and insert event object to a database so that user could |
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# do more analysis with simple database commands. |
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# |
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def process_event(param_dict): |
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event_attr = param_dict["attr"] |
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sample = param_dict["sample"] |
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raw_buf = param_dict["raw_buf"] |
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comm = param_dict["comm"] |
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name = param_dict["ev_name"] |
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# Symbol and dso info are not always resolved |
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if ("dso" in param_dict): |
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dso = param_dict["dso"] |
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else: |
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dso = "Unknown_dso" |
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if ("symbol" in param_dict): |
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symbol = param_dict["symbol"] |
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else: |
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symbol = "Unknown_symbol" |
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# Create the event object and insert it to the right table in database |
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event = create_event(name, comm, dso, symbol, raw_buf) |
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insert_db(event) |
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def insert_db(event): |
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if event.ev_type == EVTYPE_GENERIC: |
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con.execute("insert into gen_events values(?, ?, ?, ?)", |
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(event.name, event.symbol, event.comm, event.dso)) |
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elif event.ev_type == EVTYPE_PEBS_LL: |
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event.ip &= 0x7fffffffffffffff |
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event.dla &= 0x7fffffffffffffff |
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con.execute("insert into pebs_ll values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", |
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(event.name, event.symbol, event.comm, event.dso, event.flags, |
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event.ip, event.status, event.dse, event.dla, event.lat)) |
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def trace_end(): |
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print("In trace_end:\n") |
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# We show the basic info for the 2 type of event classes |
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show_general_events() |
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show_pebs_ll() |
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con.close() |
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# |
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# As the event number may be very big, so we can't use linear way |
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# to show the histogram in real number, but use a log2 algorithm. |
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# |
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def num2sym(num): |
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# Each number will have at least one '#' |
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snum = '#' * (int)(math.log(num, 2) + 1) |
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return snum |
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def show_general_events(): |
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# Check the total record number in the table |
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count = con.execute("select count(*) from gen_events") |
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for t in count: |
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print("There is %d records in gen_events table" % t[0]) |
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if t[0] == 0: |
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return |
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print("Statistics about the general events grouped by thread/symbol/dso: \n") |
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# Group by thread |
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commq = con.execute("select comm, count(comm) from gen_events group by comm order by -count(comm)") |
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print("\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42)) |
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for row in commq: |
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print("%16s %8d %s" % (row[0], row[1], num2sym(row[1]))) |
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# Group by symbol |
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print("\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58)) |
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symbolq = con.execute("select symbol, count(symbol) from gen_events group by symbol order by -count(symbol)") |
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for row in symbolq: |
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print("%32s %8d %s" % (row[0], row[1], num2sym(row[1]))) |
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# Group by dso |
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print("\n%40s %8s %16s\n%s" % ("dso", "number", "histogram", "="*74)) |
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dsoq = con.execute("select dso, count(dso) from gen_events group by dso order by -count(dso)") |
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for row in dsoq: |
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print("%40s %8d %s" % (row[0], row[1], num2sym(row[1]))) |
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# |
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# This function just shows the basic info, and we could do more with the |
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# data in the tables, like checking the function parameters when some |
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# big latency events happen. |
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# |
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def show_pebs_ll(): |
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count = con.execute("select count(*) from pebs_ll") |
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for t in count: |
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print("There is %d records in pebs_ll table" % t[0]) |
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if t[0] == 0: |
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return |
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print("Statistics about the PEBS Load Latency events grouped by thread/symbol/dse/latency: \n") |
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# Group by thread |
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commq = con.execute("select comm, count(comm) from pebs_ll group by comm order by -count(comm)") |
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print("\n%16s %8s %16s\n%s" % ("comm", "number", "histogram", "="*42)) |
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for row in commq: |
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print("%16s %8d %s" % (row[0], row[1], num2sym(row[1]))) |
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# Group by symbol |
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print("\n%32s %8s %16s\n%s" % ("symbol", "number", "histogram", "="*58)) |
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symbolq = con.execute("select symbol, count(symbol) from pebs_ll group by symbol order by -count(symbol)") |
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for row in symbolq: |
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print("%32s %8d %s" % (row[0], row[1], num2sym(row[1]))) |
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# Group by dse |
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dseq = con.execute("select dse, count(dse) from pebs_ll group by dse order by -count(dse)") |
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print("\n%32s %8s %16s\n%s" % ("dse", "number", "histogram", "="*58)) |
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for row in dseq: |
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print("%32s %8d %s" % (row[0], row[1], num2sym(row[1]))) |
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# Group by latency |
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latq = con.execute("select lat, count(lat) from pebs_ll group by lat order by lat") |
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print("\n%32s %8s %16s\n%s" % ("latency", "number", "histogram", "="*58)) |
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for row in latq: |
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print("%32s %8d %s" % (row[0], row[1], num2sym(row[1]))) |
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def trace_unhandled(event_name, context, event_fields_dict): |
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print (' '.join(['%s=%s'%(k,str(v))for k,v in sorted(event_fields_dict.items())]))
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