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yangdsh
2019-12-05 06:20:33 +00:00
committed by Dana Van Aken
parent 5579d8d94f
commit 1250732add
3 changed files with 6 additions and 5 deletions
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2
server/analysis/ddpg/ddpg.py
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@@ -3,7 +3,7 @@
#
# Copyright (c) 2017-18, Carnegie Mellon University Database Group
#
# from: https://github.com/KqSMea8/use_default
# from: https://github.com/KqSMea8/CDBTune
# Zhang, Ji, et al. "An end-to-end automatic cloud database tuning system using
# deep reinforcement learning." Proceedings of the 2019 International Conference
# on Management of Data. ACM, 2019

4
server/website/website/settings/constants.py
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@@ -52,11 +52,11 @@ DEFAULT_LEARNING_RATE = 0.01
# a small bias when using training data points as starting points.
GPR_EPS = 0.001
DEFAULT_RIDGE = 0.01
DEFAULT_RIDGE = 1.00
DEFAULT_EPSILON = 1e-6
DEFAULT_SIGMA_MULTIPLIER = 3.0
DEFAULT_SIGMA_MULTIPLIER = 1.0
DEFAULT_MU_MULTIPLIER = 1.0

5
server/website/website/tasks/async_tasks.py
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@@ -670,8 +670,9 @@ def configuration_recommendation(recommendation_input):
epsilon=DEFAULT_EPSILON,
max_iter=MAX_ITER,
sigma_multiplier=DEFAULT_SIGMA_MULTIPLIER,
mu_multiplier=DEFAULT_MU_MULTIPLIER)
model.fit(X_scaled, y_scaled, X_min, X_max, ridge=DEFAULT_RIDGE)
mu_multiplier=DEFAULT_MU_MULTIPLIER,
ridge=DEFAULT_RIDGE)
model.fit(X_scaled, y_scaled, X_min, X_max)
res = model.predict(X_samples, constraint_helper=constraint_helper)
best_config_idx = np.argmin(res.minl.ravel())