tool: save test parameters in mixed read/write benchmark script.

This commit is contained in:
Wilson Wang 2021-05-26 11:48:36 -07:00
parent 71934ff244
commit 8389ab8751
2 changed files with 168 additions and 27 deletions

View File

@ -1,13 +1,12 @@
#!/usr/bin/env python3
import six
import sys
import os
import argparse
import logging
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.colors as colors
logging.basicConfig(format='[%(levelname)s %(asctime)s %(name)s] %(message)s')
logger = logging.getLogger(__name__)
@ -24,6 +23,9 @@ def parse_args():
help='second input data files in csv format. (optional)')
parser.add_argument('-t', '--title', dest='title', type=str, required=True,
help='plot graph title string')
parser.add_argument('-z', '--zero-centered', dest='zero', type=bool, required=False,
help='plot the improvement graph with white color represents 0.0',
default=True)
parser.add_argument('-o', '--output-image', dest='output', type=str, required=True,
help='output image filename')
return parser.parse_args()
@ -42,33 +44,142 @@ def load_data_files(*args):
res = []
try:
for df in df_list:
new_df = df[['ratio', 'conn_size', 'value_size']].copy()
param_df = df[df['type'] == 'PARAM']
param_str = ''
if len(param_df) != 0:
param_str = param_df['comment'].iloc[0]
new_df = df[df['type'] == 'DATA'][['ratio', 'conn_size', 'value_size']].copy()
cols = [x for x in df.columns if x.find('iter') != -1]
tmp = [df[x].str.split(':') for x in cols]
tmp = [df[df['type'] == 'DATA'][x].str.split(':') for x in cols]
read_df = [x.apply(lambda x: float(x[0])) for x in tmp]
read_avg = sum(read_df)/len(read_df)
read_avg = sum(read_df) / len(read_df)
new_df['read'] = read_avg
write_df = [x.apply(lambda x: float(x[1])) for x in tmp]
write_avg = sum(write_df)/len(write_df)
write_avg = sum(write_df) / len(write_df)
new_df['write'] = write_avg
new_df['ratio'] = new_df['ratio'].astype(float)
new_df['conn_size'] = new_df['conn_size'].astype(int)
new_df['value_size'] = new_df['value_size'].astype(int)
res.append(new_df)
res.append({
'dataframe': new_df,
'param': param_str
})
except Exception as e:
logger.error(str(e))
sys.exit(1)
return res
# This is copied directly from matplotlib source code. Some early versions of matplotlib
# do not have CenteredNorm class
class CenteredNorm(colors.Normalize):
def __init__(self, vcenter=0, halfrange=None, clip=False):
"""
Normalize symmetrical data around a center (0 by default).
Unlike `TwoSlopeNorm`, `CenteredNorm` applies an equal rate of change
around the center.
Useful when mapping symmetrical data around a conceptual center
e.g., data that range from -2 to 4, with 0 as the midpoint, and
with equal rates of change around that midpoint.
Parameters
----------
vcenter : float, default: 0
The data value that defines ``0.5`` in the normalization.
halfrange : float, optional
The range of data values that defines a range of ``0.5`` in the
normalization, so that *vcenter* - *halfrange* is ``0.0`` and
*vcenter* + *halfrange* is ``1.0`` in the normalization.
Defaults to the largest absolute difference to *vcenter* for
the values in the dataset.
Examples
--------
This maps data values -2 to 0.25, 0 to 0.5, and 4 to 1.0
(assuming equal rates of change above and below 0.0):
>>> import matplotlib.colors as mcolors
>>> norm = mcolors.CenteredNorm(halfrange=4.0)
>>> data = [-2., 0., 4.]
>>> norm(data)
array([0.25, 0.5 , 1. ])
"""
self._vcenter = vcenter
self.vmin = None
self.vmax = None
# calling the halfrange setter to set vmin and vmax
self.halfrange = halfrange
self.clip = clip
def _set_vmin_vmax(self):
"""
Set *vmin* and *vmax* based on *vcenter* and *halfrange*.
"""
self.vmax = self._vcenter + self._halfrange
self.vmin = self._vcenter - self._halfrange
def autoscale(self, A):
"""
Set *halfrange* to ``max(abs(A-vcenter))``, then set *vmin* and *vmax*.
"""
A = np.asanyarray(A)
self._halfrange = max(self._vcenter-A.min(),
A.max()-self._vcenter)
self._set_vmin_vmax()
def autoscale_None(self, A):
"""Set *vmin* and *vmax*."""
A = np.asanyarray(A)
if self._halfrange is None and A.size:
self.autoscale(A)
@property
def vcenter(self):
return self._vcenter
@vcenter.setter
def vcenter(self, vcenter):
self._vcenter = vcenter
if self.vmax is not None:
# recompute halfrange assuming vmin and vmax represent
# min and max of data
self._halfrange = max(self._vcenter-self.vmin,
self.vmax-self._vcenter)
self._set_vmin_vmax()
@property
def halfrange(self):
return self._halfrange
@halfrange.setter
def halfrange(self, halfrange):
if halfrange is None:
self._halfrange = None
self.vmin = None
self.vmax = None
else:
self._halfrange = abs(halfrange)
def __call__(self, value, clip=None):
if self._halfrange is not None:
# enforce symmetry, reset vmin and vmax
self._set_vmin_vmax()
return super().__call__(value, clip=clip)
def plot_data(title, *args):
if len(args) == 1:
figsize = (12, 16)
df0 = args[0]
fig = plt.figure(figsize=figsize)
fig_size = (12, 16)
df0 = args[0]['dataframe']
df0param = args[0]['param']
fig = plt.figure(figsize=fig_size)
count = 0
for val, df in df0.groupby('ratio'):
count += 1
@ -81,50 +192,69 @@ def plot_data(title, *args):
plt.xlabel('Connections Amount')
plt.colorbar()
plt.tight_layout()
fig.suptitle('{}\n{}'.format(title, df0param))
elif len(args) == 2:
figsize = (12, 26)
df0 = args[0]
df1 = args[1]
fig = plt.figure(figsize=figsize)
fig_size = (12, 26)
df0 = args[0]['dataframe']
df0param = args[0]['param']
df1 = args[1]['dataframe']
df1param = args[1]['param']
fig = plt.figure(figsize=fig_size)
count = 0
delta_df = df1.copy()
delta_df[['read', 'write']] = (df1[['read', 'write']] - df0[['read', 'write']])/df0[['read', 'write']]
delta_df[['read', 'write']] = ((df1[['read', 'write']] - df0[['read', 'write']]) /
df0[['read', 'write']]) * 100
for tmp in [df0, df1, delta_df]:
count += 1
count2 = count
for val, df in tmp.groupby('ratio'):
plt.subplot(8, 3, count2)
norm = None
if count2 % 3 == 0:
cmap_name = 'bwr'
if params.zero:
norm = CenteredNorm()
else:
cmap_name = 'viridis'
plt.tripcolor(df['conn_size'], df['value_size'], df['read'] + df['write'], cmap=plt.get_cmap(cmap_name))
plt.tripcolor(df['conn_size'], df['value_size'], df['read'] + df['write'],
norm=norm,
cmap=plt.get_cmap(cmap_name))
if count2 == 1:
plt.title('{}\nR/W Ratio {:.4f}'.format(os.path.basename(params.input_file_a), val))
plt.title('{}\nR/W Ratio {:.4f}'.format(
os.path.basename(params.input_file_a),
val))
elif count2 == 2:
plt.title('{}\nR/W Ratio {:.4f}'.format(os.path.basename(params.input_file_b), val))
plt.title('{}\nR/W Ratio {:.4f}'.format(
os.path.basename(params.input_file_b),
val))
elif count2 == 3:
plt.title('Delta\nR/W Ratio {:.4f}'.format(val))
plt.title('Gain\nR/W Ratio {:.4f}'.format(val))
else:
plt.title('R/W Ratio {:.4f}'.format(val))
plt.yscale('log', base=2)
plt.ylabel('Value Size')
plt.xscale('log', base=2)
plt.xlabel('Connections Amount')
plt.colorbar()
if count2 % 3 == 0:
plt.colorbar(format='%.2f%%')
else:
plt.colorbar()
plt.tight_layout()
count2 += 3
fig.suptitle('{}\n{} {}\n{} {}'.format(
title, os.path.basename(params.input_file_a), df0param,
os.path.basename(params.input_file_b), df1param))
else:
raise Exception('invalid plot input data')
fig.suptitle(title)
fig.subplots_adjust(top=0.95)
fig.subplots_adjust(top=0.93)
plt.savefig(params.output)
def plot_data_3d(df, title):
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(projection='3d')
ax.scatter(df['conn_size'], df['value_size'], 1/(1+1/df['ratio']), c=df['read'] + df['write'])
ax.scatter(df['conn_size'], df['value_size'], 1 / (1 + 1 / df['ratio']), c=df['read'] + df['write'])
ax.set_title('{}'.format(title))
ax.set_zlabel('R/W Ratio')
ax.set_ylabel('Value Size')

View File

@ -14,6 +14,8 @@ BACKEND_SIZE="$((20 * 1024 * 1024 * 1024))"
RANGE_RESULT_LIMIT=100
CLIENT_PORT="23790"
COMMIT=
ETCD_ROOT_DIR="$(cd $(dirname $0) && pwd)/../.."
ETCD_BIN_DIR="${ETCD_ROOT_DIR}/bin"
ETCD_BIN="${ETCD_BIN_DIR}/etcd"
@ -47,9 +49,17 @@ function check_prerequisite() {
echo "file ${OUTPUT_FILE} already exists."
exit 1
fi
pushd ${ETCD_ROOT_DIR} > /dev/null
COMMIT=$(git log --pretty=format:'%h' -n 1)
if [ $? -ne 0 ]; then
COMMIT=N/A
fi
popd > /dev/null
cat >"${OUTPUT_FILE}" <<EOF
ratio,conn_size,value_size$(for i in $(seq 1 ${REPEAT_COUNT});do echo -n ",iter$i"; done)
type,ratio,conn_size,value_size$(for i in $(seq 1 ${REPEAT_COUNT});do echo -n ",iter$i"; done),comment
PARAM,,,$(for i in $(seq 1 ${REPEAT_COUNT});do echo -n ","; done),"key_size=${KEY_SIZE},key_space_size=${KEY_SPACE_SIZE},backend_size=${BACKEND_SIZE},range_limit=${RANGE_RESULT_LIMIT},commit=${COMMIT}"
EOF
}
function run_etcd_server() {
@ -97,7 +107,6 @@ function kill_etcd_server() {
sleep 5
}
check_prerequisite
while getopts ":w:c:p:l:vh" OPTION; do
case $OPTION in
@ -128,6 +137,8 @@ while getopts ":w:c:p:l:vh" OPTION; do
done
shift "$((${OPTIND} - 1))"
check_prerequisite
pushd "${WORKING_DIR}" > /dev/null
# progress stats management
@ -162,7 +173,7 @@ for RATIO_STR in ${RATIO_LIST}; do
init_etcd_db
START=$(date +%s)
LINE="${RATIO},${CONN_CLI_COUNT},${VALUE_SIZE}"
LINE="DATA,${RATIO},${CONN_CLI_COUNT},${VALUE_SIZE}"
echo -n "run with setting [${LINE}]"
for i in $(seq ${REPEAT_COUNT}); do
echo -n "."