Added e2e benchmark (#897)

Author: akharche

benchmarks/exchange_benchmark.py

@@ -0,0 +1,97 @@
+# *****************************************************************************
+# Copyright (c) 2020, Intel Corporation All rights reserved.
+# Licensed 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 pandas as pd
+import numba
+from contextlib import redirect_stdout
+import sys
+import os
+import time
+
+import warnings
+
+warnings.simplefilter("ignore")
+
+# New York Stock Exchange dataset
+# Load Data from Kaggle platform https://www.kaggle.com/dgawlik/nyse#prices.csv
+
+out = sys.stdout
+
+
+def numba_jit(*args, **kwargs):
+    kwargs.update({'nopython': True, 'parallel': True})
+    return numba.jit(*args, **kwargs)
+
+
+def process_data():
+    t_all = time.time()
+    df = pd.read_csv('prices.csv')
+
+    res = (df['open'] + df['close']).sum()
+
+    aver_volume = df["volume"].sum() / df["volume"].size
+
+    df['open'].fillna(-1, inplace=True)
+    df['close'].fillna(-1, inplace=True)
+    df['low'].fillna(-1, inplace=True)
+    df['high'].fillna(-1, inplace=True)
+    df['volume'].fillna(-1, inplace=True)
+
+    res = df['open'].max(skipna=True)
+
+    abs_series = df['high'].abs()
+
+    res = abs_series.min(skipna=True)
+
+    res = df['low'].floordiv(100000)
+    res = df['high'].floordiv(100)
+    res = df['volume'].floordiv(100)
+
+    res = df['open'].map(lambda x: x**2)
+
+    res = df['low'].std()
+
+    end_time = time.time() - t_all
+
+    return df, res, end_time
+
+
+sdc_process_data = numba_jit(process_data)
+
+
+def main():
+    print("Run Pandas...")
+    t_start = time.time()
+    process_data()
+    print("TOTAL Pandas time: ", time.time() - t_start)
+
+    f = open(os.devnull, 'w')
+
+    with redirect_stdout(f):
+        t_start = time.time()
+        sdc_process_data()  # Warming up
+        t_end = time.time() - t_start
+    print("SDC WARM_UP time: ", t_end)
+
+    print("Run SDC...")
+    t_start = time.time()
+    df1, res, end_time = sdc_process_data()
+    t_total = time.time() - t_start
+    print("NO boxing SDC time: ", end_time)
+    print("TOTAL SDC time: ", t_total)
+
+
+if __name__ == "__main__":
+    main()