def draw_top_functions(data, event, top_n, outfile, **kwargs):
"""Draw top N functions on one oprofile event
@param data a dictionary of oprofile data, { thread: oprofile_data, ... }
@param event event name
@param top_n only draw top N functions
@param outfile output file path
Optional args:
@param title the title of the plot (default: 'Oprofile (EVENT_NAME)')
@param xlabel the label on x-axes (default: 'Number of Threads')
@param ylabel the label on y-axes (default: 'Samples (%)')
@param show_all If set to True, shows all functions occured on any oprofile
outputs. Otherwise, it only shows the common functions occured on all
oprofile outputs. The default value is False.
@param threshold Only output the functions that have values larger than the
threshold
@param loc set legend location.
@param ncol set the number of columns of legend.
"""
# Preprocess optional args
title = kwargs.get('title', 'Oprofile (%s)' % event)
xlabel = kwargs.get('xlabel', '# of Cores')
ylabel = kwargs.get('ylabel', 'Samples (%)')
show_all = kwargs.get('show_all', False)
threshold = kwargs.get('threshold', 0)
loc = kwargs.get('loc', 'upper left')
ncol = kwargs.get('ncol', 2)
top_n_data = {}
for thd, op_data in data.iteritems():
top_n_data[thd] = get_top_n_funcs_in_oprofile(op_data, event, top_n)
curves = trans_top_data_to_curves(top_n_data, show_all=show_all,
threshold=threshold)
mfsplot.plot(curves, title, xlabel, ylabel, outfile, ncol=ncol, loc=loc)
def plot_lock_result(args):
"""Plot lockstat results
"""
def _merge_lock_data(curves_by_name, key, lc):
if key not in curves_by_name:
curves_by_name[key] = (lc[0], np.array(lc[1]), key)
else:
curves_by_name[key] = (lc[0], curves_by_name[key][1] + lc[1], key)
outdir = output_dir(args.dir)
files = glob.glob(args.dir + '/*_lockstat.txt')
result = analysis.Result()
test = ''
for filename in files:
fields = parse_filename(os.path.basename(filename))
test = fields[0]
# print(fields)
if test == 'ncpu':
fs = fields[2]
workload = fields[3]
x_value = int(fields[6])
else:
fs = fields[1]
workload = fields[2]
if test == 'multifs':
x_value = int(fields[3])
else:
x_value = int(fields[5])
lock_data = perftest.parse_lockstat_data(filename)
result[fs, workload, x_value] = lock_data
xlabel = '# of cores'
ylabel = 'Samples'
xticks = None
ylim = None
if test == 'multifs':
xlabel = '# of Disks'
xticks = [[1, 2, 3, 4], [1, 2, 3, 4]]
xlim = (0, 5)
output_prefix = os.path.join(outdir, os.path.basename(args.dir))
for fs in result:
for wl in result[fs]:
plot_data = {}
first_nproc = list(result[fs, wl].keys())[0]
first_func = list(result[fs, wl, first_nproc].keys())[0]
fields = list(result[fs, wl, first_nproc, first_func].keys())
for nproc in result[fs, wl]:
for field in fields:
if field not in plot_data:
plot_data[field] = {}
top_n = 10
top_lock_data = perftest.get_top_n_locks(
result[fs, wl, nproc], field, top_n)
# print(top_lock_data)
plot_data[field][nproc] = top_lock_data
for field in plot_data:
top_lock_curves = perftest.trans_top_data_to_curves(
plot_data[field], top_n=5)
# if not top_lock_curves:
# continue
top_curves_by_name = {}
for lc in top_lock_curves:
if lc[2].startswith('cpufreq_'):
continue
if ')' in lc[2]:
lc = (lc[0], lc[1], lc[2].split(')')[0])
key = lc[2]
if lc[2].startswith('dentry->'):
key = key.split('.')[0]
elif lc[2].startswith('journal->j_state_lock'):
key = 'journal->j_state_lock'
elif key.startswith('type->i_mutex_dir_key'):
key = 'i_mutex_dir_key'
_merge_lock_data(top_curves_by_name, key, lc)
top_curves = list(top_curves_by_name.values())
# print(top_curves)
if not top_curves:
continue
outfile = output_prefix + \
'_%s_%s_%s_lockstat.%s' % (fs, wl, field, args.ext)
plot.plot(top_curves, 'Lockstat (%s)' % field,
xlabel, ylabel, outfile, xticks=xticks, xlim=xlim)
def plot_top_perf_functions(data, event, top_n, outfile, **kwargs):
"""Plot the event curves for the top functions observed from Linux perf
tool.
@param data a dictionary of perf data, { thread: perf_data, ...}. The key
of this directory is the number of process/thread/cpus to observed the
data. The keys of this directory will be used as x axis of the figure.
@param event event name
@param top_n only draw top N functions.
@param outfile the output file path.
Optional args:
@param title the title of the plot (default: 'Perf (EVENT_NAME)')
@param xlabel the label on x-axes (default: '# of Cores')
@param ylabel the label on y-axes (default: 'Samples (%)')
@param show_all If set to True, shows all functions occured on any oprofile
outputs. Otherwise, it only shows the common functions occured on all
oprofile outputs. The default value is False.
@param threshold Only output the functions that have values larger than the
threshold
@param loc set legend location.
@param ncol set the number of columns of legend.
"""
# Preprocess optional args
title = kwargs.get('title', 'Perf (%s)' % event)
xlabel = kwargs.get('xlabel', '# of Cores')
ylabel = kwargs.get('ylabel', 'Samples (%)')
show_all = kwargs.get('show_all', False)
threshold = kwargs.get('threshold', 0)
loc = kwargs.get('loc', 'upper left')
ncol = kwargs.get('ncol', 2)
plot_data = data[event]
keys = sorted(plot_data.keys())
func_names = set()
for v in plot_data.values():
func_names |= v.keys()
curve_features = []
for func in func_names:
yvalues = []
for x in keys:
try:
yvalues.append(plot_data[x][func])
except KeyError:
yvalues.append(0)
if not show_all and threshold > 0 and max(yvalues) < threshold:
continue
curve_features.append((max(yvalues), (keys, yvalues, func)))
# Find top n curves
curves = []
curve_features.sort()
curve_features.reverse()
num_features = min(len(curve_features), top_n)
for curve in curve_features[:num_features]:
curves.append(curve[1])
mfsplot.plot(curves, title, xlabel, ylabel, outfile, ncol=ncol, loc=loc,
ylim=(0, 0.5))
