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October 9, 2020 19:45
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Generate data files for h2o benchmark https://github.com/h2oai/db-benchmark
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import subprocess | |
import pandas as pd | |
columns = ["task", "data", "nrow" , "k", "na", "sort", "active"] | |
dtypes = {x: str for x in columns} | |
data = pd.read_csv("_control/data.csv", names=columns, dtype=dtypes) | |
for index, row in data.iterrows(): | |
if row["active"] != "1": | |
continue | |
if row["task"] == "groupby": | |
script = ["Rscript", "_data/groupby-datagen.R"] | |
elif row["task"] == "join": | |
script = ["Rscript", "_data/join-datagen.R"] | |
else: | |
raise Exception("Unknown task type {}".format(row["task"])) | |
script.extend([str(row["nrow"]), str(row["k"]), str(row["na"]), str(row["sort"])]) | |
print(script) | |
try: | |
process = subprocess.Popen(script, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) | |
output = process.communicate() | |
except OSError: | |
print("Failed to start ", script) | |
raise | |
print(str(output[0].strip().decode())) | |
print("Command returned", process.returncode) |
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