renaissance-movie-lens_0
[2024-11-20T23:25:15.237Z] Running test renaissance-movie-lens_0 ...
[2024-11-20T23:25:15.237Z] ===============================================
[2024-11-20T23:25:16.162Z] renaissance-movie-lens_0 Start Time: Wed Nov 20 23:25:15 2024 Epoch Time (ms): 1732145115159
[2024-11-20T23:25:16.163Z] variation: NoOptions
[2024-11-20T23:25:16.163Z] JVM_OPTIONS:
[2024-11-20T23:25:16.163Z] { \
[2024-11-20T23:25:16.163Z] echo ""; echo "TEST SETUP:"; \
[2024-11-20T23:25:16.163Z] echo "Nothing to be done for setup."; \
[2024-11-20T23:25:16.163Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17321442911007/renaissance-movie-lens_0"; \
[2024-11-20T23:25:16.163Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17321442911007/renaissance-movie-lens_0"; \
[2024-11-20T23:25:16.163Z] echo ""; echo "TESTING:"; \
[2024-11-20T23:25:16.163Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17321442911007/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-20T23:25:16.163Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17321442911007/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-20T23:25:16.163Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-20T23:25:16.163Z] echo "Nothing to be done for teardown."; \
[2024-11-20T23:25:16.163Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17321442911007/TestTargetResult";
[2024-11-20T23:25:16.163Z]
[2024-11-20T23:25:16.163Z] TEST SETUP:
[2024-11-20T23:25:16.163Z] Nothing to be done for setup.
[2024-11-20T23:25:16.163Z]
[2024-11-20T23:25:16.163Z] TESTING:
[2024-11-20T23:25:19.105Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-20T23:25:21.006Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-11-20T23:25:25.054Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-20T23:25:25.979Z] Training: 60056, validation: 20285, test: 19854
[2024-11-20T23:25:25.979Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-20T23:25:25.979Z] GC before operation: completed in 55.149 ms, heap usage 71.055 MB -> 39.433 MB.
[2024-11-20T23:25:33.967Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:25:39.228Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:25:42.229Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:25:46.293Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:25:48.206Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:25:51.152Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:25:53.064Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:25:54.978Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:25:54.978Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:25:55.909Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:25:55.909Z] Movies recommended for you:
[2024-11-20T23:25:55.909Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:25:55.909Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:25:55.909Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29760.542 ms) ======
[2024-11-20T23:25:55.909Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-20T23:25:55.909Z] GC before operation: completed in 116.234 ms, heap usage 829.026 MB -> 56.600 MB.
[2024-11-20T23:25:59.974Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:26:02.561Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:26:06.620Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:26:09.582Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:26:11.495Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:26:13.411Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:26:15.325Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:26:17.242Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:26:17.242Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:26:17.242Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:26:18.177Z] Movies recommended for you:
[2024-11-20T23:26:18.177Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:26:18.177Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:26:18.177Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21911.994 ms) ======
[2024-11-20T23:26:18.177Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-20T23:26:18.177Z] GC before operation: completed in 113.343 ms, heap usage 356.269 MB -> 56.553 MB.
[2024-11-20T23:26:21.137Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:26:24.161Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:26:27.124Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:26:30.087Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:26:31.992Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:26:34.071Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:26:35.980Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:26:37.884Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:26:37.884Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:26:37.884Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:26:37.884Z] Movies recommended for you:
[2024-11-20T23:26:37.884Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:26:37.884Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:26:37.884Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20329.990 ms) ======
[2024-11-20T23:26:37.884Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-20T23:26:37.884Z] GC before operation: completed in 102.409 ms, heap usage 308.643 MB -> 53.685 MB.
[2024-11-20T23:26:41.965Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:26:43.875Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:26:46.820Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:26:49.772Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:26:50.699Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:26:52.604Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:26:54.509Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:26:56.417Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:26:57.345Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:26:57.345Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:26:57.345Z] Movies recommended for you:
[2024-11-20T23:26:57.345Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:26:57.345Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:26:57.345Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18919.766 ms) ======
[2024-11-20T23:26:57.345Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-20T23:26:57.345Z] GC before operation: completed in 112.287 ms, heap usage 301.477 MB -> 54.036 MB.
[2024-11-20T23:27:00.297Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:27:02.203Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:27:05.146Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:27:07.754Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:27:09.665Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:27:11.572Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:27:12.501Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:27:14.413Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:27:15.342Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:27:15.342Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:27:15.342Z] Movies recommended for you:
[2024-11-20T23:27:15.342Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:27:15.342Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:27:15.342Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17987.235 ms) ======
[2024-11-20T23:27:15.342Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-20T23:27:15.342Z] GC before operation: completed in 102.115 ms, heap usage 347.552 MB -> 54.143 MB.
[2024-11-20T23:27:18.286Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:27:21.236Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:27:23.146Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:27:26.090Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:27:27.999Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:27:29.913Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:27:31.819Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:27:33.740Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:27:33.740Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:27:33.740Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:27:33.740Z] Movies recommended for you:
[2024-11-20T23:27:33.740Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:27:33.740Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:27:33.740Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18659.613 ms) ======
[2024-11-20T23:27:33.740Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-20T23:27:34.667Z] GC before operation: completed in 111.356 ms, heap usage 555.804 MB -> 57.552 MB.
[2024-11-20T23:27:37.615Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:27:39.520Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:27:42.462Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:27:45.404Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:27:46.330Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:27:48.257Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:27:50.164Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:27:52.070Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:27:52.070Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:27:52.070Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:27:52.997Z] Movies recommended for you:
[2024-11-20T23:27:52.997Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:27:52.997Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:27:52.997Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18392.859 ms) ======
[2024-11-20T23:27:52.997Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-20T23:27:52.997Z] GC before operation: completed in 110.376 ms, heap usage 306.787 MB -> 54.326 MB.
[2024-11-20T23:27:55.936Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:27:57.841Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:28:00.785Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:28:03.728Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:28:04.656Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:28:06.563Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:28:08.478Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:28:10.124Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:28:11.054Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:28:11.054Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:28:11.054Z] Movies recommended for you:
[2024-11-20T23:28:11.054Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:28:11.054Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:28:11.054Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18220.978 ms) ======
[2024-11-20T23:28:11.054Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-20T23:28:11.054Z] GC before operation: completed in 117.347 ms, heap usage 348.463 MB -> 54.706 MB.
[2024-11-20T23:28:13.999Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:28:16.942Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:28:18.856Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:28:21.801Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:28:23.702Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:28:24.630Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:28:26.542Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:28:28.449Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:28:29.377Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:28:29.377Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:28:29.377Z] Movies recommended for you:
[2024-11-20T23:28:29.377Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:28:29.377Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:28:29.377Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18194.092 ms) ======
[2024-11-20T23:28:29.377Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-20T23:28:29.377Z] GC before operation: completed in 109.652 ms, heap usage 350.662 MB -> 54.469 MB.
[2024-11-20T23:28:32.318Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:28:35.305Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:28:38.248Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:28:40.152Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:28:42.163Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:28:44.065Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:28:45.969Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:28:46.896Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:28:47.823Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:28:47.823Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:28:47.823Z] Movies recommended for you:
[2024-11-20T23:28:47.823Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:28:47.823Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:28:47.823Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18638.116 ms) ======
[2024-11-20T23:28:47.823Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-20T23:28:47.823Z] GC before operation: completed in 104.662 ms, heap usage 518.679 MB -> 58.021 MB.
[2024-11-20T23:28:50.763Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:28:53.703Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:28:56.646Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:28:58.553Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:29:00.461Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:29:02.420Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:29:04.322Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:29:05.248Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:29:06.174Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:29:06.174Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:29:06.174Z] Movies recommended for you:
[2024-11-20T23:29:06.174Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:29:06.174Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:29:06.174Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18128.429 ms) ======
[2024-11-20T23:29:06.174Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-20T23:29:06.174Z] GC before operation: completed in 102.234 ms, heap usage 353.500 MB -> 54.231 MB.
[2024-11-20T23:29:09.119Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:29:12.732Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:29:14.637Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:29:17.577Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:29:18.520Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:29:20.441Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:29:22.345Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:29:24.249Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:29:24.249Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:29:24.249Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:29:24.249Z] Movies recommended for you:
[2024-11-20T23:29:24.249Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:29:24.249Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:29:24.249Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18130.891 ms) ======
[2024-11-20T23:29:24.249Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-20T23:29:24.249Z] GC before operation: completed in 106.399 ms, heap usage 535.486 MB -> 57.847 MB.
[2024-11-20T23:29:27.203Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:29:30.145Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:29:33.088Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:29:35.645Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:29:37.551Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:29:38.483Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:29:40.391Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:29:42.296Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:29:43.225Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:29:43.225Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:29:43.225Z] Movies recommended for you:
[2024-11-20T23:29:43.225Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:29:43.225Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:29:43.225Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18403.523 ms) ======
[2024-11-20T23:29:43.225Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-20T23:29:43.225Z] GC before operation: completed in 107.364 ms, heap usage 353.560 MB -> 54.723 MB.
[2024-11-20T23:29:46.162Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:29:48.135Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:29:51.078Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:29:54.018Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:29:54.947Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:29:56.858Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:29:58.772Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:30:00.680Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:30:01.606Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:30:01.606Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:30:01.606Z] Movies recommended for you:
[2024-11-20T23:30:01.606Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:30:01.606Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:30:01.606Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18357.200 ms) ======
[2024-11-20T23:30:01.606Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-20T23:30:01.606Z] GC before operation: completed in 112.826 ms, heap usage 725.282 MB -> 57.976 MB.
[2024-11-20T23:30:04.545Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:30:06.452Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:30:09.393Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:30:12.340Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:30:13.342Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:30:15.244Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:30:17.146Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:30:19.052Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:30:19.052Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:30:19.052Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:30:19.052Z] Movies recommended for you:
[2024-11-20T23:30:19.052Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:30:19.052Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:30:19.052Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17867.306 ms) ======
[2024-11-20T23:30:19.052Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-20T23:30:19.979Z] GC before operation: completed in 105.594 ms, heap usage 308.253 MB -> 54.559 MB.
[2024-11-20T23:30:21.883Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:30:24.830Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:30:27.777Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:30:29.684Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:30:31.599Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:30:33.508Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:30:35.416Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:30:36.365Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:30:37.295Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:30:37.295Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:30:37.295Z] Movies recommended for you:
[2024-11-20T23:30:37.295Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:30:37.295Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:30:37.295Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17785.931 ms) ======
[2024-11-20T23:30:37.295Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-20T23:30:37.295Z] GC before operation: completed in 113.260 ms, heap usage 513.167 MB -> 58.000 MB.
[2024-11-20T23:30:40.240Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:30:42.187Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:30:45.132Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:30:47.037Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:30:48.941Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:30:50.845Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:30:52.750Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:30:53.677Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:30:54.608Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:30:54.608Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:30:54.608Z] Movies recommended for you:
[2024-11-20T23:30:54.608Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:30:54.608Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:30:54.608Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17230.687 ms) ======
[2024-11-20T23:30:54.608Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-20T23:30:54.608Z] GC before operation: completed in 106.532 ms, heap usage 580.114 MB -> 57.931 MB.
[2024-11-20T23:30:57.551Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:30:59.899Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:31:02.841Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:31:04.749Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:31:06.653Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:31:08.559Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:31:10.465Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:31:11.394Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:31:12.323Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:31:12.323Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:31:12.323Z] Movies recommended for you:
[2024-11-20T23:31:12.323Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:31:12.323Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:31:12.323Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17615.619 ms) ======
[2024-11-20T23:31:12.323Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-20T23:31:12.323Z] GC before operation: completed in 110.763 ms, heap usage 232.207 MB -> 54.554 MB.
[2024-11-20T23:31:15.267Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:31:18.210Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:31:20.116Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:31:23.063Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:31:24.974Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:31:25.903Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:31:27.829Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:31:29.736Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:31:29.736Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:31:29.736Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:31:30.664Z] Movies recommended for you:
[2024-11-20T23:31:30.664Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:31:30.664Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:31:30.664Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17859.495 ms) ======
[2024-11-20T23:31:30.664Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-20T23:31:30.664Z] GC before operation: completed in 108.835 ms, heap usage 350.443 MB -> 54.805 MB.
[2024-11-20T23:31:33.786Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:31:35.696Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:31:38.642Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:31:40.547Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:31:42.594Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:31:44.497Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:31:45.424Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:31:47.330Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:31:48.256Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-20T23:31:48.256Z] The best model improves the baseline by 14.43%.
[2024-11-20T23:31:48.256Z] Movies recommended for you:
[2024-11-20T23:31:48.256Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T23:31:48.256Z] There is no way to check that no silent failure occurred.
[2024-11-20T23:31:48.256Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17614.510 ms) ======
[2024-11-20T23:31:50.161Z] -----------------------------------
[2024-11-20T23:31:50.161Z] renaissance-movie-lens_0_PASSED
[2024-11-20T23:31:50.161Z] -----------------------------------
[2024-11-20T23:31:50.161Z]
[2024-11-20T23:31:50.161Z] TEST TEARDOWN:
[2024-11-20T23:31:50.161Z] Nothing to be done for teardown.
[2024-11-20T23:31:50.161Z] renaissance-movie-lens_0 Finish Time: Wed Nov 20 23:31:49 2024 Epoch Time (ms): 1732145509297