parserTimingReport Namespace Reference

Functions
def	calc_MinMaxAvgRMS (items, remove_first=True, f_time=lambda x:x[0], f_evt_num=lambda x:x[1])
def	calcRMS (items, avg)
def	extractRSS_VSIZE (line1, line2, record_number)
def	loadTimeLog (log_filename, maxsize_rad=0)
def	manual_run ()
def	perf_profile ()
def	processModuleTimeLogData (modules_timelog, groupBy="module_name")
	mod_data["stats"] =calc_MinMaxAvgRMS(f_time = lambda x: x["time"], f_evt_num = lambda x: x["event_number"], items = times_bymod[mod_name]) More...

Function Documentation

def parserTimingReport.calc_MinMaxAvgRMS	(		items,
			remove_first = True,
			f_time = lambda x: x[0],
			f_evt_num = lambda x: x[1]
	)

returns a dict of avg, min, max, rms 

Definition at line 142 of file parserTimingReport.py.

References calcRMS(), objects.autophobj.float, genParticles_cff.map, SiStripPI.max, and min().

Referenced by processModuleTimeLogData().

def calc_MinMaxAvgRMS(items, remove_first = True, f_time = lambda x: x[0], f_evt_num = lambda x: x[1],):
    """ returns a dict of avg, min, max, rms """
    # save the cpu time of first event before removing the first result!
    cpu_time_first = f_time(items[0])

    if len(items) > 1 and remove_first == True:
        items.remove(items[0]) #TODO: if there is only one event - we have a problem -> do we eliminate the whole module?
        # TODO: it removes it completely from all the data because we do not save/ do not copy it

    items_time = map(f_time, items)
    min_value = min(items_time)
    max_value = max(items_time)
    max_index = items_time.index(max_value)
    avg_value = float(sum(items_time)) / float(len(items_time))
    rms_value = calcRMS(items_time,avg_value)

    return {"min":  min_value, "max": max_value, "cputime_first": cpu_time_first,
            "rms": rms_value, "avg": avg_value,
            "event_number_of_max": f_evt_num(items[max_index])}
    
    

def parserTimingReport.calcRMS	(		items,
			avg
	)

returns RootMeanSquare  of items in a list 

Definition at line 135 of file parserTimingReport.py.

Referenced by calc_MinMaxAvgRMS().

def calcRMS(items,avg):
    """ returns RootMeanSquare  of items in a list """ 
    # sqrt(sum(x^2))
    # Not statistics RMS... "physics" RMS, i.e. standard deviation: sqrt(sum((x-avg)**2)/N)
    # return math.sqrt(reduce(lambda x: (x - avg)**2, items) / len(items))  
    return math.sqrt(sum([(x-avg)**2 for x in items])/len(items))

def parserTimingReport.extractRSS_VSIZE	(		line1,
			line2,
			record_number
	)

>>> extractRSS_VSIZE("%MSG-w MemoryCheck:  PostModule 19-Jun-2009 13:06:08 CEST Run: 1 Event: 1", \
             "MemoryCheck: event : VSIZE 923.07 0 RSS 760.25 0")
(('1', '760.25'), ('1', '923.07'))

Definition at line 30 of file parserTimingReport.py.

References split, and digitizers_cfi.strip.

Referenced by loadTimeLog().

def extractRSS_VSIZE(line1, line2, record_number):
    """ 
    >>> extractRSS_VSIZE("%MSG-w MemoryCheck:  PostModule 19-Jun-2009 13:06:08 CEST Run: 1 Event: 1", \
                 "MemoryCheck: event : VSIZE 923.07 0 RSS 760.25 0")
    (('1', '760.25'), ('1', '923.07'))
    """

    if ("Run" in line1) and  ("Event" in line1): # the first line
        event_number = line1.split('Event:')[1].strip() 
    else: return False

    """ it's first or second MemoryCheck line """
    if ("VSIZE" in line2) and ("RSS" in line2): # the second line
        RSS = line2.split("RSS")[1].strip().split(" ")[0].strip() #changed partition into split for backward compatability with py2.3
        VSIZE = line2.split("RSS")[0].strip().split("VSIZE")[1].strip().split(" ")[0].strip()
        #Hack to return the record number instea of event number for now... can always switch back of add event number on top
        #return ((event_number, RSS), (event_number, VSIZE))
        return ((record_number, RSS), (record_number, VSIZE))
    else: return False

def parserTimingReport.loadTimeLog	(		log_filename,
			maxsize_rad = 0
	)

gets the timing data from the logfile
 returns 4 lists:

    * ModuleTime data (event_number, module_label, module_name, seconds) and
    * EventTime data
        - with granularity of event (initial - not processed data)
    * RSS per event
    * VSIZE per event

Definition at line 51 of file parserTimingReport.py.

References extractRSS_VSIZE(), objects.autophobj.float, createfilelist.int, and str.

Referenced by manual_run(), perf_profile(), and cmsPerfSuiteHarvest.process_timesize_dir().

def loadTimeLog(log_filename, maxsize_rad = 0): #TODO: remove maxsize to read, used for debugging
    """ gets the timing data from the logfile
     returns 4 lists:

        * ModuleTime data (event_number, module_label, module_name, seconds) and
        * EventTime data
            - with granularity of event (initial - not processed data)
        * RSS per event
        * VSIZE per event
     """
    # ----- format of logfile ----
    # Report columns headings for modules: eventnum runnum modulelabel modulename timetakeni"
    # e.g. TimeModule> 1 1 csctfDigis CSCTFUnpacker 0.0624561

    mod_data = []
    evt_data = []
    rss_data = []
    vsize_data = []
    # open file and read it and fill the structure!
    logfile = open(log_filename, 'r')
    
    # get only the lines which have time report data
    #TODO: reading and processing line by line might speed up the process!
                
    memcheck_line1 = False

    record_number=0
    last_record=0
    last_event=0
    for line in logfile:
        if 'TimeModule>' in line.strip():
            line = line.strip()
            line_content_list = line.split(' ')[0:]
            #Hack to avoid issues with the non-consecutive run numbers:
            event_number = int(line_content_list[1])
            if event_number != last_event:
                record_number=record_number+1
                last_event=event_number
                # module label and name were mixed up in the original doc
            module_label = str(line_content_list[4])
            module_name = str(line_content_list[3])
            seconds = float(line_content_list[5])
            #For now let's try to switch to the record_number... if we need to also have the event_number we can always add it back.
            #mod_data.append((event_number, module_label, module_name, seconds))
            mod_data.append((record_number, module_label, module_name, seconds))
        if 'TimeEvent>' in line.strip():
            line = line.strip()
            line_content_list = line.split(' ')[0:]
            #Hack to avoid issues with the non-consecutive run numbers:
            event_number = int(line_content_list[1])
            if event_number != last_event:
                record_number=record_number+1
                last_event=event_number
                # module label and name were mixed up in the original doc
            time_seconds = str(line_content_list[3])
            
            #TODO: what are the other [last two] numbers? Real time? smf else? TimeEvent> 1 1 15.3982 13.451 13.451
            #For now let's try to switch to the record_number... if we need to also have the event_number we can always add it back.
            #evt_data.append((event_number, time_seconds))
            evt_data.append((record_number, time_seconds))
        """ 
            %MSG-w MemoryCheck:  PostModule 19-Jun-2009 13:06:08 CEST Run: 1 Event: 1
            MemoryCheck: event : VSIZE 923.07 0 RSS 760.25 0
        """
        if 'MemoryCheck:' in line.strip():
            # this is the first line out of two
            if (not memcheck_line1):
                memcheck_line1 = line.strip()
            else:
                #FIXME (eventually)
                #Hacking in the record_number extracted from the TimeEvent and TimeModule parsing... NOT ROBUST...
                (rss, vsize) = extractRSS_VSIZE(memcheck_line1, line.strip(), record_number)
                rss_data.append(rss)
                vsize_data.append(vsize)
        else: 
            memcheck_line1 = False                                                                                                                                              

    logfile.close()
    
    return (mod_data, evt_data, rss_data, vsize_data)

def parserTimingReport.manual_run

(

)

Definition at line 246 of file parserTimingReport.py.

References cmssw_exportdb_xml.export_xml(), FileNamesHelper.getJobID_fromTimeReportLogName(), loadTimeLog(), edm.print(), and processModuleTimeLogData().

def manual_run():
    timelog_f = "TTBAR__RAW2DIGI,RECO_TimingReport.log"
    timelog_f = "TTBAR__GEN,SIM,DIGI,L1,DIGI2RAW,HLT_TimingReport.log"  
    #TODO: get STEP name from filename
    release_files = {
             
             "CMSSW_3_1_0_pre9": 
             (
             "CMSSW_3_1_0_pre9/MINBIAS__RAW2DIGI,RECO_TimingReport.log", 
              "CMSSW_3_1_0_pre9/TTBAR__RAW2DIGI,RECO_TimingReport.log")
             ## "CMSSW_3_1_0_pre10": 
             }
    for release, files in release_files.items():
        print("Processing release: %s" % release)
        for timelog_f in files:
            print("Processing file: %s" % timelog_f)
            
            # TODO: automaticaly detect type of report file!!!
            (mod_timelog, evt_timelog, rss_data, vsize_data) =loadTimeLog(timelog_f)
            
            mod_timelog= processModuleTimeLogData(mod_timelog, groupBy = "module_label")
            print("Number of modules grouped by (module_label): %s" % len(mod_timelog))

            (candle, step, pileup_type, conditions, event_content) = getJobID_fromTimeReportLogName(timelog_f)
            
            """ We could get release from the path but that's quite ugly! """
            export_xml(jobID = jobID, release=release, timelog_result=(mod_timelog, evt_timelog, rss_data, vsize_data)) 

""" use to run performance profiling """

def parserTimingReport.perf_profile

(

)

Definition at line 275 of file parserTimingReport.py.

References cmssw_exportdb_xml.export_xml(), FileNamesHelper.getJobID_fromTimeReportLogName(), loadTimeLog(), processModuleTimeLogData(), and MCScenario_CRAFT1_22X.write_xml().

def perf_profile():
    timelog_f = "test_data/TTBAR__RAW2DIGI,RECO_TimingReport.log"
    (modules_timelog, evt_timelog, rss_data, vsize_data) = loadTimeLog(timelog_f)   

    mod_timelog= processModuleTimeLogData(modules_timelog, groupBy = "module_label")

    (candle, step, pileup_type, conditions, event_content) = getJobID_fromTimeReportLogName(timelog_f)
    
    xmldoc = minidom.Document()
    export_xml(step = step, candle = candle, release="test", timelog_result=(mod_timelog, evt_timelog, rss_data, vsize_data), xml_doc = xmldoc) 
    write_xml(xmldoc, "test_xml_output.xml")
        

def parserTimingReport.processModuleTimeLogData	(		modules_timelog,
			groupBy = "module_name"
	)

mod_data["stats"] =calc_MinMaxAvgRMS(f_time = lambda x: x["time"], f_evt_num = lambda x: x["event_number"], items = times_bymod[mod_name])

Processes the timelog data grouping events by module and calculates min, max, avg, rms 
Returns data as a list of dicts like: !

 {
    <module_name>: 
        {name:, label:, 
            stats: {num_events, avg, min, max, rms} 
 } 

mod_data["stats"]["num_events"] = len(times_bymod[mod_name])

times_bymod[mod_name] = mod_data Let's rewrite this using the dictionary we now have without any logical change (could do with some...):

Definition at line 163 of file parserTimingReport.py.

References mps_setup.append, calc_MinMaxAvgRMS(), relativeConstraints.keys, and update.

Referenced by manual_run(), perf_profile(), and cmsPerfSuiteHarvest.process_timesize_dir().

def processModuleTimeLogData(modules_timelog, groupBy = "module_name"):
    """ Processes the timelog data grouping events by module and calculates min, max, avg, rms 
    Returns data as a list of dicts like: !
    
     {
        <module_name>: 
            {name:, label:, 
                stats: {num_events, avg, min, max, rms} 
     } 
     
     """
    # group by module_name, we save a list for each module name
    times_bymod = {}
    
    # print "Num of useful TimeLog lines: %s" % len(modules_timelog)
    
    for time_data in modules_timelog:
        (event_number, module_label, module_name, seconds) = time_data
        
        # group times of modules By label or name, TODO: maybe both 
        if groupBy == "module_label":
            key = module_label
        else:
            if groupBy =="name+label": 
                key = module_name + "_" + module_label
            else:
                key = module_name

            
        try:
            # is the list for current module initialized?
            times_bymod[key]
        except KeyError:
            #Changing this from a list to a dict (see comments below):
            #times_bymod[key] = []
            times_bymod[key] = {}
        #Running out of memory!
        #times_bymod[key].append({"label": module_label, "name": module_name, "time": seconds, "event_number": event_number})
        #Let's do it right:
        #Instead of times_bymod[key]=[{"label": module_label, "name": module_name, "time": seconds, "event_number": event_number}]
        #let's do times_bymod[key]={"module_label":{"module_name":[(seconds,event_number)]}} so we do not repeat label and name and especially they are not a pair of key/value
        #During the first event all the keys will be initialized, then from event 2 on it will be just appending the (seconds,event_number) tuple to the list with the appropriate keys:

        #Check/Set up the module label dict:
        try:
            times_bymod[key][module_label]
        except KeyError:
            times_bymod[key].update({module_label:{}})
        
        #Check/Set up the module name dict:
        try:
            times_bymod[key][module_label][module_name]
        except KeyError:
            times_bymod[key][module_label].update({module_name:[]})
        
        #We're now ready to add the info as a tuple in the list!
        times_bymod[key][module_label][module_name].append((seconds,event_number))
        
        
    # calculate Min,Max, Avg, RMS for each module and in this way get the final data to be imported
    ##for mod_name in times_bymod.keys():
    ##  #copy needed data
    ##  #mod_data = {"label": times_bymod[mod_name][0]["label"], "name": times_bymod[mod_name][0]["name"]}
    ##  #New data structure:
    ##  mod_data = {"label":times_bymod[mod_name].keys()[0],"name":times_bymod[mod_name][times_bymod[mod_name].keys()[0]].keys()[0]}
    ##  # add statistical data
    
    for key in times_bymod.keys():
        for label in times_bymod[key].keys():
            mod_data={'label':label}
            for name in times_bymod[key][label].keys():
                mod_data.update({'name':name})
                mod_data['stats']= calc_MinMaxAvgRMS(f_time= lambda x:x[0],f_evt_num=lambda x:x[1],items=times_bymod[key][label][name])
                mod_data['stats']['num_events']=len(times_bymod[key][label][name])
        times_bymod[key]=mod_data
    return times_bymod