tools: add mixed read-write performance evaluation scripts

tools/rw-heatmaps/plot_data.py

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+#!/usr/bin/env python3
+import six
+import sys
+import os
+import argparse
+import logging
+import pandas as pd
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+
+logging.basicConfig(format='[%(levelname)s %(asctime)s %(name)s] %(message)s')
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+
+params = None
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='plot graph using mixed read/write result file.')
+    parser.add_argument('input_file_a', type=str,
+                        help='first input data files in csv format. (required)')
+    parser.add_argument('input_file_b', type=str, nargs='?',
+                        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('-o', '--output-image', dest='output', type=str, required=True,
+                        help='output image filename')
+    return parser.parse_args()
+
+
+def load_data_files(*args):
+    df_list = []
+    try:
+        for i in args:
+            if i is not None:
+                logger.debug('loading csv file {}'.format(i))
+                df_list.append(pd.read_csv(i))
+    except FileNotFoundError as e:
+        logger.error(str(e))
+        sys.exit(1)
+    res = []
+    try:
+        for df in df_list:
+            new_df = df[['ratio', 'conn_size', 'value_size']].copy()
+            tmp = [df[x].str.split(':') for x in ['1', '2', '3', '4', '5']]
+
+            read_df = [x.apply(lambda x: float(x[0])) for x in tmp]
+            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)
+            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)
+    except Exception as e:
+        logger.error(str(e))
+        sys.exit(1)
+    return res
+
+
+def plot_data(title, *args):
+    if len(args) == 1:
+        figsize = (12, 16)
+        df0 = args[0]
+        fig = plt.figure(figsize=figsize)
+        count = 0
+        for val, df in df0.groupby('ratio'):
+            count += 1
+            plt.subplot(4, 2, count)
+            plt.tripcolor(df['conn_size'], df['value_size'], df['read'] + df['write'])
+            plt.title('R/W Ratio {:.2f}'.format(val))
+            plt.yscale('log', base=2)
+            plt.ylabel('Value Size')
+            plt.xscale('log', base=2)
+            plt.xlabel('Connections Amount')
+            plt.colorbar()
+            plt.tight_layout()
+    elif len(args) == 2:
+        figsize = (12, 26)
+        df0 = args[0]
+        df1 = args[1]
+        fig = plt.figure(figsize=figsize)
+        count = 0
+        delta_df = df1.copy()
+        delta_df[['read', 'write']] = (df1[['read', 'write']] - df0[['read', 'write']])/df0[['read', 'write']]
+        for tmp in [df0, df1, delta_df]:
+            count += 1
+            count2 = count
+            for val, df in tmp.groupby('ratio'):
+                plt.subplot(8, 3, count2)
+                if count2 % 3 == 0:
+                    cmap_name = 'bwr'
+                else:
+                    cmap_name = 'viridis'
+                plt.tripcolor(df['conn_size'], df['value_size'], df['read'] + df['write'], cmap=plt.get_cmap(cmap_name))
+                if count2 == 1:
+                    plt.title('{}\nR/W Ratio {:.2f}'.format(os.path.basename(params.input_file_a), val))
+                elif count2 == 2:
+                    plt.title('{}\nR/W Ratio {:.2f}'.format(os.path.basename(params.input_file_b), val))
+                elif count2 == 3:
+                    plt.title('Delta\nR/W Ratio {:.2f}'.format(val))
+                else:
+                    plt.title('R/W Ratio {:.2f}'.format(val))
+                plt.yscale('log', base=2)
+                plt.ylabel('Value Size')
+                plt.xscale('log', base=2)
+                plt.xlabel('Connections Amount')
+                plt.colorbar()
+                plt.tight_layout()
+                count2 += 3
+    else:
+        raise Exception('invalid plot input data')
+    fig.suptitle(title)
+    fig.subplots_adjust(top=0.95)
+    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.set_title('{}'.format(title))
+    ax.set_zlabel('R/W Ratio')
+    ax.set_ylabel('Value Size')
+    ax.set_xlabel('Connections Amount')
+    plt.show()
+
+
+def main():
+    global params
+    logging.basicConfig()
+    params = parse_args()
+    result = load_data_files(params.input_file_a, params.input_file_b)
+    plot_data(params.title, *result)
+
+
+if __name__ == '__main__':
+    main()