monitor.py 是主监控程序,将监控数据写入日志,并统计监控数据生成HTML统计展示页面:

#!/usr/bin/env python2
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import threading, subprocess, re, os, sys, signal, socket
from time import sleep, time
from contextlib import closing
import traceback, thread
from datetime import datetime
from collections import namedtuple
from pprint import pprint
from itertools import groupby

# Probe intervals, in seconds.
# Warning: a value too short may get wrong results due to lack of data when system load goes high.
#          and must be float!
PROBE_INTERVAL=float(5)

#FIXME: use log helper later
#log_lock = threading.Lock()
def log(*s):
    if len(s)==1: s=s[0]
    else: s= " ".join([str(x) for x in s])
#    with log_lock:
#        with open("/home/zhihui/monitor_proc.log", 'a') as f:
    log_str = str(thread.get_ident())+":"+str(s) +'\n'
    #        f.write( log_str )
    sys.stderr.write(log_str)

entered=False
def sig_term_handler(signo, stack):
    global entered
    global log_path
    global report_path
    global workload_title
    global bench_log_path
    global na

    if not entered:
        entered=True            # FIXME: Not atomic
    else: return

    na.stop()
    generate_report(workload_title, log_path, bench_log_path, report_path)
    sys.exit(0)

def samedir(fn):
    """
    return abspath of fn in the same directory where this python file stores
    """
    return os.path.abspath(os.path.join(os.path.dirname(__file__), fn))

class PatchedNameTuple(object):
    def __sub__(self, other):
        assert isinstance(other, self.__class__)
        assert self[0] == other[0]
        cls = self.__class__
        return cls(self[0], *[a-b for a, b in zip(self[1:], other[1:])])

    def __div__(self, other):
        return self.__class__(self[0], *[a/other for a in self[1:]])

    def _add(self, other, override_title=None):
        if other == None: return self
        assert isinstance(other, self.__class__)
        cls = self.__class__
        title = self[0] if not override_title else override_title
        return cls(title, *[a+b for a, b in zip(self[1:], other[1:])])

def ident(size, s):
    return "\n".join((" "*size + x for x in s.split("\n")))

class RemoteProc(threading.Thread):
    SEP="----SEP----"
    template_debug=r"""exec('
import time, os, sys, socket, traceback
socket.setdefaulttimeout(1)
def log(*x, **kw):
 with open("/home/zhihui/probe.log", kw.get("mode","a")) as f:
  f.write(repr(x)+chr(10))
try:
 log("create socket", mode="w")
 s=socket.socket(socket.AF_INET, socket.SOCK_STREAM)
 log("bind socket")
 s.bind(("0.0.0.0",0))
 log("listen socket")
 s.listen(5)
 log("bind socket to:", s.getsockname())
 while True:
  log("accepting")
  try:
   print s.getsockname()[1]
   s2,peer=s.accept()
   break
  except socket.timeout:
   log("accept timeout, retry")
 log("accepted, peer:",peer)
except Exception as e:
 import traceback
 log(traceback.format_exc())
{func_template}
while True:
  s2.send(("{SEP}+%s" % time.time())+chr(10))
{call_template}
  s2.send("{SEP}#end"+chr(10))
  time.sleep({interval})
')"""
    template=r"""exec('
import time, os, sys, socket, traceback
s=socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind(("0.0.0.0",0))
s.listen(5)
print s.getsockname()[1]
s2,peer=s.accept()
{func_template}
while True:
  s2.send(("{SEP}+%s" % time.time())+chr(10))
{call_template}
  s2.send("{SEP}#end"+chr(10))
  time.sleep({interval})
')"""

    def __init__(self, host, interval=1):
        self.host = host
        self.cmds = []
        self.interval = interval
        self.monitor_ins = {}
        self.local_aggr_container={}
        self._running=True

        super(RemoteProc, self).__init__()

    def register(self, monitor_ins, cmds):
        assert isinstance(monitor_ins, BaseMonitor)
        self.monitor_ins[len(self.cmds)] = monitor_ins # monitor command seq id => monitor instance
        self.cmds.append(cmds)

    def run(self):
        func_template = "\n".join(["def func_{id}():\n{func}"\
                                       .format(id=id,
                                               func=ident(2,
                                                          func+'\ns2.send("{SEP}={id}"+chr(10))'\
                                                              .format(SEP=self.SEP, id=id))) \
                                       for id, func in enumerate(self.cmds)])
        call_template="\n".join(["  func_{id}()"\
                                     .format(id=id) for id in range(len(self.cmds))]
                                )
        script = self.template.format(func_template=func_template,
                                      call_template=call_template,
                                      interval = self.interval,
                                      SEP = self.SEP)

        s = script.replace('"', r'\"').replace("\n", r"\n")
        container=[]
#        log("ssh client to:", self.host)
        with self.ssh_client(self.host, "python -u -c \"{script}\"".format(script=s)) as f:
#            log("ssh client %s connected" % self.host)
            try:
                port_line = f.readline()
#                log("host:", self.host, "got port,", port_line)
                port = int(port_line.rstrip())
                s=socket.socket(socket.AF_INET, socket.SOCK_STREAM)
                s.settimeout(0.5)
                for i in range(30): # try to connect 30 times maximum
                    try:
#                        log("try to connect:", self.host, port)
                        s.connect((self.host, port))
#                        log("connectted to:", self.host, port)
                        break
                    except socket.timeout:
#                        log("connecting to:", self.host, port, "timedout")
                        pass
                else:           # not connectted after 30 times trying
#                    log("cann't connectted to:", self.host, port)
                    s.shutdown(socket.SHUT_RDWR)
                    self.ssh_close()
                    return
                s.settimeout(None)
            except Exception as e:
                log(traceback.format_exc())

            with closing(s.makefile()) as f2:
                while self._running:
                    try:
                        l = f2.readline()
                    except KeyboardInterrupt:
                        break
                    if not l: break
                    if l.startswith(self.SEP):
                        tail = l.lstrip(self.SEP)
                        if tail[0]=='+': # timestamp
                            remote_timestamp = float(tail[1:])
                            cur_timestamp = time()
                        elif tail.startswith('#end'): # end sign
#                            log("na push, timestamp:", cur_timestamp)
                            self.na_push(cur_timestamp)
                        else:
                            id = int(tail[1:])
                            if self.monitor_ins[id]:
                                self.monitor_ins[id].feed(container, cur_timestamp)
                        container = []
                    else:
                        container.append(l.rstrip())
            s.shutdown(socket.SHUT_RDWR)
        self.ssh_close()

    def stop(self):
        self._running=False

    def aggregate(self, timestamp, data):
        if not self.local_aggr_container:
            self.local_aggr_container['timestamp']=timestamp
        assert timestamp == self.local_aggr_container['timestamp']
        assert type(data) is dict
        self.local_aggr_container.update(data)
        self.local_aggr_container['timestamp'] = timestamp

    def na_register(self, na):
        assert isinstance(na, NodeAggregator)
        self.node_aggr_parent = na

    def na_push(self, timestamp):
        if self.local_aggr_container:
            assert self.local_aggr_container.get('timestamp', -1) == timestamp
            self.node_aggr_parent.commit_aggregate(self.host, self.local_aggr_container)
            self.local_aggr_container={}

class BaseMonitor(object):
    IGNORE_KEYS=[]
    def __init__(self, rproc):
        self.rproc = rproc
        self._last = None

    def feed(self, container, timestamp):            # override to parse pulled data files
        raise NotImplementedError()

    def ssh_client(self, host, shell):    # override for opening ssh client
        raise NotImplementedError()

    def ssh_close(self):                  # override for clear up ssh client
        raise NotImplementedError()

    def commit(self, timestamp, header, stat):
        if self._last is None: self._last = stat
        else:
            stat_delta = dict([(header+'/'+k, stat[k] - self._last[k]) \
                                for k in set(self._last.keys()).union(set(stat.keys()))\
                                if k in stat and k in self._last and k not in self.IGNORE_KEYS
                                ])
            self._last = stat
#            if header.startswith("net"):
#                print stat_delta
            stat_delta[header+'/total'] = reduce_patched(lambda a,b: a._add(b, 'total'), stat_delta.values())
            self.rproc.aggregate(timestamp, stat_delta)

class BashSSHClientMixin(object):
    ssh_lock = threading.Lock()
    def ssh_client(self, host, shell):
        with open(os.devnull, 'rb', 0) as DEVNULL:
            with BashSSHClientMixin.ssh_lock:
                self.proc = subprocess.Popen(["ssh", host, shell], bufsize=1,
                                             stdin=DEVNULL, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
        return self.proc.stdout

    def ssh_close(self):
        assert self.proc
        self.proc.terminate()
        self.proc.wait()
        return self.proc.returncode

_CPU=namedtuple("CPU", ['label', 'user', 'nice', 'system', 'idle', 'iowait', 'irq', 'softirq'])
class CPU(_CPU, PatchedNameTuple):
    def percentage(self):
        total = sum(self[1:])
        return CPU(self[0], *[x*100.0 / total for x in self[1:]]) if total>0 else self

class CPUMonitor(BaseMonitor):
    def __init__(self, rproc):
        super(CPUMonitor, self).__init__(rproc)
        rproc.register(self, """with open("/proc/stat") as f:
  s2.send("".join([x for x in f.readlines() if x.startswith("cpu")]))
""")

    def feed(self, container, timestamp):
        "parse /proc/stat"
        self.commit(timestamp, dict([self._parse_stat(line) for line in container]))

    def _parse_stat(self, line):
        "parse one line of /proc/stat"
        assert line.strip(), "BUG! empty line in /proc/stat"
        fields = line.split()
        if fields[0]=='cpu':
            fields[0]='total'
        return (fields[0], CPU(fields[0], *[int(x) for x in fields[1:8]]))

    def commit(self, timestamp, cpu_stat):
        if self._last is None:
            self._last = cpu_stat
        else:
            cpu_usage = dict([("cpu/"+k, (cpu_stat[k] - self._last[k]).percentage()) for k in self._last])
            self._last = cpu_stat
            self.rproc.aggregate(timestamp, cpu_usage)

_Network=namedtuple("Network", ['label', "recv_bytes", "recv_packets", "recv_errs", "recv_drop",
                                "send_bytes", "send_packets", "send_errs", "send_drop"])
class Network(_Network, PatchedNameTuple): pass

class NetworkMonitor(BaseMonitor):
    IGNORE_KEYS=["lo"]
    def __init__(self, rproc):
        rproc.register(self, """with open("/proc/net/dev") as f:
  s2.send("".join([x for x in f.readlines()]))
""")
        self._filter = re.compile('^\s*(.+):\s*(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+\d+\s+\d+\s+\d+\s+\d+\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+).*$')
        super(NetworkMonitor, self).__init__(rproc)

    def feed(self, container, timestamp):
        "parse /proc/net/dev"
        self.commit(timestamp, "net", dict(filter(lambda x:x, [self._parse_net_dev(line) for line in container])))

    def _parse_net_dev(self, line):
        matched = self._filter.match(line)
        if matched:
            obj = Network(matched.groups()[0], *[int(x) for x in matched.groups()[1:]])
            if not (obj.recv_bytes==0 and obj.send_bytes==0):
                return (obj[0], obj)

_Disk=namedtuple("Disk", ["label", "io_read", "bytes_read", "time_spent_read", "io_write", "bytes_write", "time_spent_write"])

class Disk(_Disk, PatchedNameTuple): pass

class DiskMonitor(BaseMonitor):
    def __init__(self, rproc):
        super(DiskMonitor, self).__init__(rproc)
        rproc.register(self, """with open("/proc/diskstats") as f:
  blocks = os.listdir("/sys/block")
  s2.send("".join([x for x in f.readlines() if x.split()[2] in blocks and not x.split()[2].startswith("loop") and x.split()[3]!="0"]))
""")

    def feed(self, container, timestamp):
        "parse /proc/diskstats"
        self.commit(timestamp, "disk", dict([self._parse_disk_stat(line) for line in container]))

    def _parse_disk_stat(self, line):
        fields = line.split()[2:]
        obj = Disk(fields[0],
                    io_read=int(fields[1]), bytes_read=int(fields[3])*512, time_spent_read=int(fields[4])/1000.0,
                    io_write=int(fields[5]), bytes_write=int(fields[7])*512, time_spent_write=int(fields[8])/1000.0)
        return (obj[0], obj)

_Memory=namedtuple("Memory", ["label", "total", "used", "buffer_cache", "free", "map"])
class Memory(_Memory, PatchedNameTuple): pass

class MemoryMonitor(BaseMonitor):
    def __init__(self, rproc):
        super(MemoryMonitor, self).__init__(rproc)
        rproc.register(self, """with open("/proc/meminfo") as f:
  mem = dict([(a, b.split()[0].strip()) for a, b in [x.split(":") for x in f.readlines()]])
  s2.send(":".join([mem[field] for field in ["MemTotal", "Buffers", "Cached", "MemFree", "Mapped"]])+chr(10))
""")

    def feed(self, memory_status, timestamp):
        "parse /proc/meminfo"
        total, buffers, cached, free, mapped= [int(x) for x in memory_status[0].split(":")]

        self.rproc.aggregate(timestamp, {"memory/total":Memory(label="total", total=total,
                                                               used=total - free - buffers-cached,
                                                               buffer_cache=buffers + cached,
                                                               free=free, map=mapped)})
_Proc=namedtuple("Proc", ["label", "load5", "load10", "load15", "running", "procs"])
class Proc(_Proc, PatchedNameTuple): pass

class ProcMonitor(BaseMonitor):
    def __init__(self, rproc):
        super(ProcMonitor, self).__init__(rproc)
        rproc.register(self, """with open("/proc/loadavg") as f:
  s2.send(f.read())
""")

    def feed(self, load_status, timestamp):
        "parse /proc/meminfo"
        load5, load10, load15, running_procs= load_status[0].split()[:4]
        running, procs = running_procs.split('/')

        self.rproc.aggregate(timestamp, {"proc":Proc(label="total", load5=float(load5), load10=float(load10),
                                                     load15=float(load15), running=int(running), procs=int(procs))})

class NodeAggregator(object):
    def __init__(self, log_name):
        self.node_pool = {}
        self.log_name = log_name
        self.log_lock = threading.Lock()
        try:
            os.unlink(self.log_name)
        except OSError:
            pass

    def append(self, node):
        assert isinstance(node, RemoteProc)
        self.node_pool[node.host] = node
        node.na_register(self)

    def commit_aggregate(self, node, datas):
        datas['hostname'] = node
        with self.log_lock:
            with file(self.log_name, "a") as f:
                f.write(repr(datas) + "\n")

    def run(self):
        for v in self.node_pool.values():
            v.start()

    def stop(self):
        for v in self.node_pool.values():
            v.stop()
        for v in self.node_pool.values():
            v.join()

def round_to_base(v, b):
    """
    >>> round_to_base(0.1, 0.3)
    0.0
    >>> round_to_base(0.3, 0.3)
    0.3
    >>> round_to_base(0.0, 0.3)
    0.0
    >>> round_to_base(0.5, 0.3)
    0.3
    >>> round_to_base(0.51, 0.3)
    0.3
    """
    for i in range(10):
        base = int(b * 10**i)
        if abs(base - b * 10**i) < 0.001: break
    assert base>0
    return float(int(v * 10**i) / base * base) / (10**i)

def filter_dict_with_prefix(d, prefix, sort=True):
    keys = sorted(d.keys()) if sort else d.keys()
    if prefix[0]=='!':
        return  dict([(x, d[x]) for x in keys if not x.startswith(prefix[1:])])
    else:
        return  dict([(x, d[x]) for x in keys if x.startswith(prefix)])

def reduce_patched(func, data):
    if len(data)==1:
        return data[0]
    elif len(data)==0:
        return data
    else:
        return reduce(func, data)

def filter_dict_with_prefixes(d, *prefixes):
    if len(prefixes)==1:
        return filter_dict_with_prefix(d, prefixes[0])
    else:
        return reduce_patched(lambda a,b: filter_dict_with_prefix(filter_dict_with_prefix(d, a),b),
                      prefixes)

def test():
    p = BashSSHClientMixin()
    script=r"""exec('
import time, os, sys
while 1:
  with open("/proc/stat") as f: print f.read(),
  print "---hello---"
  time.sleep(1)
')"""
    s = script.replace('"', r'\"').replace("\n", r"\n")
    with p.ssh_client("localhost", "python -u -c \"{s}\"".format(s=s)) as f:
        while 1:
            l = f.readline()
            print l.rstrip()
            if not l: break
    p.ssh_close()

def test2():
    class P(RemoteProc, BashSSHClientMixin):  pass

    p = P("localhost", 0.3)
    CPUMonitor(p)
    NetworkMonitor(p)
    DiskMonitor(p)
    MemoryMonitor(p)

    p.run()

def start_monitor(log_filename, nodes):
    class P(RemoteProc, BashSSHClientMixin):
        def __init__(self, *args):
            RemoteProc.__init__(self, *args)
            CPUMonitor(self)
            NetworkMonitor(self)
            DiskMonitor(self)
            MemoryMonitor(self)
            ProcMonitor(self)
    global na
    na = NodeAggregator(log_filename)
    nodes = sorted(list(set(nodes)))
    for node in nodes:
        na.append(P(node, PROBE_INTERVAL))
    na.run()

def parse_bench_log(benchlog_fn):
    events=["x,event"]
    _spark_stage_submit = re.compile("^(\d{2}\/\d{2}\/\d{2} \d{2}:\d{2}:\d{2}) INFO [a-zA-Z0-9_\.]*DAGScheduler: Submitting (Stage \d+) \((.*)\).+$") # submit spark stage
    _spark_stage_finish = re.compile("^(\d{2}\/\d{2}\/\d{2} \d{2}:\d{2}:\d{2}) INFO [a-zA-Z0-9_\.]*DAGScheduler: (Stage \d+) \((.*)\) finished.+$")   # spark stage finish
    _hadoop_run_job = re.compile("^(\d{2}\/\d{2}\/\d{2} \d{2}:\d{2}:\d{2}) INFO mapred.*\.Job.*: Running job: job_([\d_]+)$") # hadoop run job
    _hadoop_map_reduce_progress = re.compile("^(\d{2}\/\d{2}\/\d{2} \d{2}:\d{2}:\d{2}) INFO mapred.*\.Job.*:\s+map (\d{1,2})% reduce (\d{1,2})%$") # hadoop reduce progress
    _hadoop_job_complete_mr1 = re.compile("^(\d{2}\/\d{2}\/\d{2} \d{2}:\d{2}:\d{2}) INFO mapred.JobClient: Job complete: job_([\d_]+)$")
    _hadoop_job_complete_mr2 = re.compile("^(\d{2}\/\d{2}\/\d{2} \d{2}:\d{2}:\d{2}) INFO mapreduce.Job: Job job_([\d_]+) completed successfully$")

    """
# MR1 sample
14/06/24 11:18:39 INFO mapred.JobClient: Running job: job_201406241116_0001
14/06/24 11:18:40 INFO mapred.JobClient:  map 0% reduce 0%
...
13/11/21 14:38:55 INFO mapred.JobClient: Job complete: job_201311150128_0050

# MR2 sample
15/04/10 17:20:01 INFO mapreduce.Job: Running job: job_1427781540447_0448
15/04/10 17:20:07 INFO mapreduce.Job: Job job_1427781540447_0448 running in uber mode : false
15/04/10 17:20:07 INFO mapreduce.Job:  map 0% reduce 0%
...
15/04/10 17:20:25 INFO mapreduce.Job: Job job_1427781540447_0448 completed successfully
    """
    flag={}
    with open(benchlog_fn) as f:
        while True:
            line = f.readline().rstrip()
            if not line: break
            for rule in [_spark_stage_submit, _spark_stage_finish, _hadoop_run_job, _hadoop_map_reduce_progress, _hadoop_job_complete_mr1, _hadoop_job_complete_mr2]:
                matched = rule.match(line)
                if matched:
                    result = matched.groups()
                    timestamp = datetime.strptime(result[0], r" # convert to millsec for js
                    if rule is _spark_stage_submit:
                        events.append("{t},Start {v1} ({v2})".format(t=timestamp, v1=result[1], v2=result[2]))
                    elif rule is _spark_stage_finish:
                        events.append("{t},Finish {v1} ({v2})".format(t=timestamp, v1=result[1], v2=result[2]))
                    elif rule is _hadoop_run_job:
                        events.append("{t},Start Job {v1}".format(t=timestamp, v1=result[1]))
                        flag={}
                    elif rule is _hadoop_map_reduce_progress:
                        map_progress,reduce_progress = int(result[1]), int(result[2])
                        op={'map':False, 'reduce':False}
                        if map_progress == 100:
                            if not "map" in flag:
                                op['map'] = True
                                flag['map'] = True
                        elif reduce_progress>0:
                            if not 'reduce' in flag:
                                op['reduce'] = True
                                flag['reduce'] = True
                        if op['map'] and op['reduce']:
                            events.append("{t},Map finish and Reduce start".format(t=timestamp))
                        elif op['map']:
                            events.append("{t},Map finish".format(t=timestamp))
                        elif op['reduce']:
                            events.append("{t},Reduce start".format(t=timestamp))
                    elif rule is _hadoop_job_complete_mr1 or rule is _hadoop_job_complete_mr2:
                        events.append("{t},Finsih Job {v1}".format(t=timestamp, v1=result[1]))
                    else:
                        assert 0, "should never reach here"

        # limit maximum string length of events
        for i in range(len(events)):
            event_time, event_str = re.split(',', events[i], 1)
            if len(event_str) > 45:
                event_str = event_str[:21]+ '...' + event_str[-21:]
                events[i]="%s,%s" % (event_time, event_str)

        # merge events occurred at sametime:
        i = 1
        while i < len(events)-1:
            cur = events[i].split(',')[0]
            next = events[i+1].split(',')[0]
            if abs(int(cur)/1000 - int(next)/1000) < 1:
                events[i] = events[i] + "<br>" + re.split(',', events[i+1], 1)[1]
                del events[i+1]
                continue
            i += 1
        return events

def generate_report(workload_title, log_fn, benchlog_fn, report_fn):
    c =- 1
    with open(log_fn) as f:
        datas=[eval(x) for x in f.readlines()]

    all_hosts = sorted(list(set([x['hostname'] for x in datas])))
    data_slices = groupby(datas, lambda x:round_to_base(x['timestamp'], PROBE_INTERVAL)) # round to time interval and groupby

    # Generating CSVs
    cpu_heatmap = ["x,y,value,hostname,coreid"]
    cpu_overall = ["x,idle,user,system,iowait,others"]
    network_heatmap = ["x,y,value,hostname,adapterid"]
    network_overall = ["x,recv_bytes,send_bytes,|recv_packets,send_packets,errors"]
    diskio_heatmap = ["x,y,value,hostname,diskid"]
    diskio_overall = ["x,read_bytes,write_bytes,|read_io,write_io"]
    memory_heatmap = ["x,y,value,hostname"]
    memory_overall = ["x,free,buffer_cache,used"]
    procload_heatmap = ["x,y,value,hostname"]
    procload_overall = ["x,load5,load10,load15,|running,procs"]
    events = parse_bench_log(benchlog_fn)

    cpu_count={}
    network_count={}
    diskio_count={}
    memory_count={}
    proc_count={}

    for t, sub_data in data_slices:
        classed_by_host = dict([(x['hostname'], x) for x in sub_data])
        # total cpus, plot user/sys/iowait/other
        data_by_all_hosts = [classed_by_host.get(h, {}) for h in all_hosts]

        # all cpu cores, total cluster
        summed1 = [x['cpu/total'] for x in data_by_all_hosts if x.has_key('cpu/total')]
        if summed1:
            summed = reduce_patched(lambda a,b: a._add(b), summed1) / len(summed1)
            for x in data_by_all_hosts:
                cpu = x.get('cpu/total', None)
                if not cpu: continue
            # user, system, io, idle, others
#            print t, x['hostname'], cpu.user, cpu.system, cpu.iowait, cpu.idle, cpu.nice+cpu.irq+cpu.softirq
#        print t, summed
            cpu_overall.append("{time},{idle},{user},{system},{iowait},{others}" \
                                   .format(time   = int(t*1000), user = summed.user, system = summed.system,
                                           iowait = summed.iowait, idle = summed.idle,
                                           others = summed.nice + summed.irq + summed.softirq))

        # all cpu cores, plot heatmap according to cpus/time/usage(100%-idle)
        for idx, x in enumerate(data_by_all_hosts):
            for idy, y in enumerate(filter_dict_with_prefixes(x, "cpu", "!cpu/total").values()):
                try:
                    pos = cpu_count[(idx, idy, x['hostname'])]
                except:
                    pos =  len(cpu_count)
                    cpu_count[(idx, idy, x['hostname'])] = pos
#                print t, pos, 100-y.idle, x['hostname'], y.label
                cpu_heatmap.append("{time},{pos},{value},{host},{cpuid}" \
                                       .format(time = int(t*1000), pos = pos, value = 100-y.idle,
                                               host = x['hostname'], cpuid = y.label))

        # all disk of each node, total cluster
        summed1=[x['disk/total'] for x in data_by_all_hosts if x.has_key('disk/total')]
        if summed1:
            summed = reduce_patched(lambda a,b: a._add(b), summed1)
            for x in data_by_all_hosts:
                disk = x.get('disk/total', None)
                if not disk: continue
            # io-read, io-write, bytes-read, bytes-write
#            print t, x['hostname'], disk.io_read, disk.io_write, disk.bytes_read, disk.bytes_write
 #       print t, summed
            diskio_overall.append("{time},{bytes_read},{bytes_write},{io_read},{io_write}" \
                                      .format(time        = int(t*1000),
                                              bytes_read  = summed.bytes_read / PROBE_INTERVAL,
                                              bytes_write = summed.bytes_write / PROBE_INTERVAL,
                                              io_read     = summed.io_read / PROBE_INTERVAL,
                                              io_write    = summed.io_write / PROBE_INTERVAL))

        # all disks, plot heatmap according to disks/bytes_read+bytes_write
        for idx, x in enumerate(data_by_all_hosts):
            for idy, y in enumerate(filter_dict_with_prefixes(x, "disk", "!disk/total").values()):
                try:
                    pos = diskio_count[(idx, idy, x['hostname'])]
                except:
                    pos =  len(diskio_count)
                    diskio_count[(idx, idy, x['hostname'])] = pos
#                print t, pos, 100-y.idle, x['hostname'], y.label
                diskio_heatmap.append("{time},{pos},{value},{host},{diskid}" \
                                       .format(time   = int(t*1000),
                                               pos    = pos,
                                               value  = (y.bytes_read + y.bytes_write) / PROBE_INTERVAL,
                                               host   = x['hostname'],
                                               diskid = y.label))

        # memory of each node, total cluster
        summed1 = [x['memory/total'] for x in data_by_all_hosts if x.has_key('memory/total')]
        if summed1:
            summed = reduce_patched(lambda a,b: a._add(b), summed1)
            for x in data_by_all_hosts:
                mem = x.get("memory/total", None)
                if not mem: continue
                # mem-total, mem-used, mem-buffer&cache, mem-free, KB
    #            print t, x['hostname'], mem.total, mem.used, mem.buffer_cache, mem.free
            #print t, summed
            memory_overall.append("{time},{free},{buffer_cache},{used}" \
                                      .format(time = int(t*1000),
                                              free = summed.free,
                                              used = summed.used,
                                              buffer_cache = summed.buffer_cache))

        # all memory, plot heatmap according to memory/total - free
        for idx, x in enumerate(data_by_all_hosts):
            for idy, y in enumerate(filter_dict_with_prefixes(x, "memory/total").values()):
                try:
                    pos = memory_count[(idx, idy, x['hostname'])]
                except:
                    pos =  len(memory_count)
                    memory_count[(idx, idy, x['hostname'])] = pos
#                print t, pos, 100-y.idle, x['hostname'], y.label
                memory_heatmap.append("{time},{pos},{value},{host}" \
                                       .format(time  = int(t*1000),
                                               pos   = pos,
                                               value = (y.total - y.free)*1000,
                                               host  = x['hostname']))

        # proc of each node, total cluster
        summed1 = [x['proc'] for x in data_by_all_hosts if x.has_key('proc')]
        if summed1:
            summed = reduce_patched(lambda a,b: a._add(b), summed1)
            for x in data_by_all_hosts:
                procs = x.get("proc", None)
                if not procs: continue
            procload_overall.append("{time},{load5},{load10},{load15},{running},{procs}"\
                                        .format(time   = int(t*1000),
                                                load5  = summed.load5,load10=summed.load10,
                                                load15 = summed.load15,running=summed.running,
                                                procs  = summed.procs))

        # all nodes' proc, plot heatmap according to proc/proc.procs
        for idx, x in enumerate(data_by_all_hosts):
            for idy, y in enumerate(filter_dict_with_prefixes(x, "proc").values()):
                try:
                    pos = proc_count[(idx, idy, x['hostname'])]
                except:
                    pos =  len(proc_count)
                    proc_count[(idx, idy, x['hostname'])] = pos
#                print t, pos, 100-y.idle, x['hostname'], y.label
                procload_heatmap.append("{time},{pos},{value},{host}" \
                                            .format(time = int(t*1000), pos = pos, value = y.procs,
                                                    host = x['hostname']))

        # all network interface, total cluster
        summed1 = [x['net/total'] for x in data_by_all_hosts if x.has_key('net/total')]

        if summed1:
            summed = reduce_patched(lambda a,b: a._add(b), summed1)
            for x in data_by_all_hosts:
                net = x.get("net/total", None)
                if not net: continue
                # recv-byte, send-byte, recv-packet, send-packet, errors
    #            print t, x['hostname'], net.recv_bytes, net.send_bytes, net.recv_packets, net.send_packets, net.recv_errs+net.send_errs+net.recv_drop+net.send_drop
    #        print t, summed
            network_overall.append("{time},{recv_bytes},{send_bytes},{recv_packets},{send_packets},{errors}" \
                                       .format(time         = int(t*1000),
                                               recv_bytes   = summed.recv_bytes / PROBE_INTERVAL,
                                               send_bytes   = summed.send_bytes / PROBE_INTERVAL,
                                               recv_packets = summed.recv_packets / PROBE_INTERVAL,
                                               send_packets = summed.send_packets / PROBE_INTERVAL,
                                               errors = (summed.recv_errs + summed.send_errs + \
                                                             summed.recv_drop + summed.send_drop) / PROBE_INTERVAL)
                                   )

        # all network adapters, plot heatmap according to net/recv_bytes + send_bytes
        for idx, x in enumerate(data_by_all_hosts):
            for idy, y in enumerate(filter_dict_with_prefixes(x, "net", "!net/total").values()):
                try:
                    pos = network_count[(idx, idy, x['hostname'])]
                except:
                    pos =  len(network_count)
                    network_count[(idx, idy, x['hostname'])] = pos
                network_heatmap.append("{time},{pos},{value},{host},{networkid}" \
                                       .format(time  = int(t*1000),
                                               pos   = pos*2,
                                               value = y.recv_bytes / PROBE_INTERVAL,
                                               host  = x['hostname'],
                                               networkid = y.label+".recv"))
                network_heatmap.append("{time},{pos},{value},{host},{networkid}" \
                                       .format(time  = int(t*1000),
                                               pos   = pos*2+1,
                                               value = y.send_bytes / PROBE_INTERVAL,
                                               host  = x['hostname'],
                                               networkid = y.label+".send"))

    with open(samedir("chart-template.html")) as f:
        template = f.read()

    variables = locals()
    def my_replace(match):
        match = match.group()[1:-1]
        if match.endswith('heatmap') or match.endswith('overall'):
            return "\n".join(variables[match])
        elif match =='events':
            return "\n".join(events)
        elif match == 'probe_interval':
            return str(PROBE_INTERVAL * 1000)
        elif match == 'workload_name':
            return workload_title
        else:
            return '{%s}' % match

    with open(report_fn, 'w') as f:
        f.write(re.sub(r'{\w+}', my_replace, template))

def show_usage():
    log("""Usage:
    monitor.py <workload_title> <parent_pid> <log_path.log> <benchlog_fn.log> <report_path.html> <monitor_node_name1> ... <monitor_node_nameN>
""")

if __name__=="__main__":
    if len(sys.argv)<6:
        log(sys.argv)
        show_usage()
        sys.exit(1)

#    log(sys.argv)
    global log_path
    global report_path
    global workload_title
    global bench_log_path
    global na

    workload_title = sys.argv[1]
    parent_pid = sys.argv[2]
    log_path = sys.argv[3]
    bench_log_path = sys.argv[4]
    report_path = sys.argv[5]
    nodes_to_monitor = sys.argv[6:]
    pid=os.fork()
    if pid:                               #parent
        print pid
    else:                                 #child
        os.close(0)
        os.close(1)
        os.close(2)
#        log("child process start")
        signal.signal(signal.SIGTERM, sig_term_handler)
        start_monitor(log_path, nodes_to_monitor)
        while  os.path.exists("/proc/%s" % parent_pid):
            sleep(1)
        # parent lost, stop!
        signal.signal(signal.SIGTERM, signal.SIG_IGN)
        na.stop()
        generate_report(workload_title, log_path, bench_log_path, report_path)

HiBench成长笔记——(9) 分析源码monitor.py的更多相关文章

  1. HiBench成长笔记——(10) 分析源码execute_with_log.py

    #!/usr/bin/env python2 # Licensed to the Apache Software Foundation (ASF) under one or more # contri ...

  2. HiBench成长笔记——(8) 分析源码workload_functions.sh

    workload_functions.sh 是测试程序的入口,粘连了监控程序 monitor.py 和 主运行程序: #!/bin/bash # Licensed to the Apache Soft ...

  3. HiBench成长笔记——(11) 分析源码run.sh

    #!/bin/bash # Licensed to the Apache Software Foundation (ASF) under one or more # contributor licen ...

  4. HiBench成长笔记——(5) HiBench-Spark-SQL-Scan源码分析

    run.sh #!/bin/bash # Licensed to the Apache Software Foundation (ASF) under one or more # contributo ...

  5. memcached学习笔记——存储命令源码分析下篇

    上一篇回顾:<memcached学习笔记——存储命令源码分析上篇>通过分析memcached的存储命令源码的过程,了解了memcached如何解析文本命令和mencached的内存管理机制 ...

  6. memcached学习笔记——存储命令源码分析上篇

    原创文章,转载请标明,谢谢. 上一篇分析过memcached的连接模型,了解memcached是如何高效处理客户端连接,这一篇分析memcached源码中的process_update_command ...

  7. [转]【安卓笔记】AsyncTask源码剖析

    [转][安卓笔记]AsyncTask源码剖析 http://blog.csdn.net/chdjj/article/details/39122547 前言: 初学AsyncTask时,就想研究下它的实 ...

  8. Hadoop学习笔记(10) ——搭建源码学习环境

    Hadoop学习笔记(10) ——搭建源码学习环境 上一章中,我们对整个hadoop的目录及源码目录有了一个初步的了解,接下来计划深入学习一下这头神象作品了.但是看代码用什么,难不成gedit?,单步 ...

  9. 【Azure 应用服务】Azure Function App使用SendGrid发送邮件遇见异常消息The operation was canceled,分析源码逐步最终源端

    问题描述 在使用Azure Function App的SendGrid Binging功能,调用SendGrid服务器发送邮件功能时,有时候遇见间歇性,偶发性异常.在重新触发SendGrid部分的Fu ...

随机推荐

  1. http协议学习 —— post请求方法提交application/x-www-form-urlencoded类型的数据格式

    先推荐一篇很不错的文章:https://imququ.com/post/four-ways-to-post-data-in-http.html 说一下,如果是自己编写底层,那么要注意了,不能只有提交数 ...

  2. python3.6.5修改print的颜色

    开头部分:\033[显示方式;前景色;背景色m +想要输出的内容:\033[0m      注意:开头部分的三个参数:显示方式,前景色,背景色是可选参数,具体参数效果见下文,可以只写其中的某一个:参数 ...

  3. 02.当构造参数过多时使用builder模式

    前言 <Effective Java>中文第三版,是一本关于Java基础的书,这本书不止一次有人推荐我看.其中包括我很喜欢的博客园博主五月的仓颉,他曾在自己的博文<给Java程序猿们 ...

  4. np.ndarray与PIL.Image对象相互转换

    Image对象有crop功能,也就是图像切割功能,但是使用opencv读取图像的时候,图像转换为了np.adarray类型,该类型无法使用crop功能,需要进行类型转换,所以使用下面的转换方式进行转换 ...

  5. 【快学springboot】SpringBoot整合Mybatis Plus

    原创声明 本文首发于头条号[Happyjava].Happy的掘金地址:https://juejin.im/user/5cc2895df265da03a630ddca,Happy的个人博客:http: ...

  6. GIT使用教程——命令详解

    $ git init 当前目录建立GIT可以管理的仓库(版本库),生成一个.git的隐藏文件夹 $ git add <filename> 将工作区的文件修改添加到版本库的暂存区 $ git ...

  7. HDU 5587:Array

    Array  Accepts: 118  Submissions: 232  Time Limit: 2000/1000 MS (Java/Others)  Memory Limit: 131072/ ...

  8. JS 表单相关

    var title = $("#subjects option:selected").text();

  9. 2月送书福利:ASP.NET Core开发实战

    大家都知道我有一个公众号“恰童鞋骚年”,在公众号2020年第一天发布的推文<2020年,请让我重新介绍我自己>中,我曾说到我会在2020年中每个月为所有关注“恰童鞋骚年”公众号的童鞋们送一 ...

  10. 一键设置Fluent环境变量小程序

    使用视频教程优酷播放地址: https://v.youku.com/v_show/id_XNDU2MTkwNDg5Mg==.html?spm=a2hzp.8244740.0.0 一键设置环境变量小软件 ...