renaissance-movie-lens_0
[2024-11-08T00:15:11.902Z] Running test renaissance-movie-lens_0 ...
[2024-11-08T00:15:11.903Z] ===============================================
[2024-11-08T00:15:11.903Z] renaissance-movie-lens_0 Start Time: Thu Nov 7 18:15:11 2024 Epoch Time (ms): 1731024911514
[2024-11-08T00:15:11.903Z] variation: NoOptions
[2024-11-08T00:15:11.903Z] JVM_OPTIONS:
[2024-11-08T00:15:11.903Z] { \
[2024-11-08T00:15:11.903Z] echo ""; echo "TEST SETUP:"; \
[2024-11-08T00:15:11.903Z] echo "Nothing to be done for setup."; \
[2024-11-08T00:15:11.903Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310240134879/renaissance-movie-lens_0"; \
[2024-11-08T00:15:11.903Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310240134879/renaissance-movie-lens_0"; \
[2024-11-08T00:15:11.903Z] echo ""; echo "TESTING:"; \
[2024-11-08T00:15:11.903Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/jdk8u442-b02/bin/..//bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310240134879/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-08T00:15:11.903Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310240134879/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-08T00:15:11.903Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-08T00:15:11.903Z] echo "Nothing to be done for teardown."; \
[2024-11-08T00:15:11.903Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310240134879/TestTargetResult";
[2024-11-08T00:15:11.903Z]
[2024-11-08T00:15:11.903Z] TEST SETUP:
[2024-11-08T00:15:11.903Z] Nothing to be done for setup.
[2024-11-08T00:15:11.903Z]
[2024-11-08T00:15:11.903Z] TESTING:
[2024-11-08T00:15:14.959Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-08T00:15:16.474Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-11-08T00:15:20.499Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-08T00:15:20.499Z] Training: 60056, validation: 20285, test: 19854
[2024-11-08T00:15:20.499Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-08T00:15:21.196Z] GC before operation: completed in 223.305 ms, heap usage 101.322 MB -> 28.850 MB.
[2024-11-08T00:15:26.413Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:15:30.481Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:15:33.589Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:15:35.780Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:15:37.991Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:15:39.410Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:15:40.835Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:15:43.071Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:15:43.071Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:15:43.071Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:15:43.751Z] Movies recommended for you:
[2024-11-08T00:15:43.751Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:15:43.751Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:15:43.751Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22637.559 ms) ======
[2024-11-08T00:15:43.751Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-08T00:15:43.751Z] GC before operation: completed in 385.347 ms, heap usage 134.848 MB -> 49.469 MB.
[2024-11-08T00:15:46.835Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:15:49.934Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:15:52.181Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:15:54.944Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:15:56.499Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:15:57.908Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:15:59.337Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:16:01.604Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:16:02.289Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:16:02.289Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:16:02.289Z] Movies recommended for you:
[2024-11-08T00:16:02.289Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:16:02.289Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:16:02.289Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18202.096 ms) ======
[2024-11-08T00:16:02.289Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-08T00:16:02.289Z] GC before operation: completed in 286.274 ms, heap usage 347.850 MB -> 45.533 MB.
[2024-11-08T00:16:05.370Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:16:07.591Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:16:10.668Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:16:12.866Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:16:14.296Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:16:15.711Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:16:17.115Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:16:18.553Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:16:19.230Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:16:19.230Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:16:19.230Z] Movies recommended for you:
[2024-11-08T00:16:19.230Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:16:19.230Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:16:19.230Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16705.176 ms) ======
[2024-11-08T00:16:19.230Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-08T00:16:19.230Z] GC before operation: completed in 224.347 ms, heap usage 686.177 MB -> 73.123 MB.
[2024-11-08T00:16:21.437Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:16:23.660Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:16:25.902Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:16:28.139Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:16:29.566Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:16:30.977Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:16:32.398Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:16:33.828Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:16:34.521Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:16:34.521Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:16:34.521Z] Movies recommended for you:
[2024-11-08T00:16:34.521Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:16:34.521Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:16:34.521Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15220.396 ms) ======
[2024-11-08T00:16:34.521Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-08T00:16:34.521Z] GC before operation: completed in 184.006 ms, heap usage 677.867 MB -> 76.209 MB.
[2024-11-08T00:16:37.596Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:16:39.805Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:16:42.038Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:16:44.265Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:16:45.691Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:16:47.135Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:16:48.562Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:16:49.988Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:16:49.988Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:16:49.988Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:16:49.988Z] Movies recommended for you:
[2024-11-08T00:16:49.988Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:16:49.988Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:16:49.988Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15486.230 ms) ======
[2024-11-08T00:16:49.988Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-08T00:16:50.676Z] GC before operation: completed in 169.741 ms, heap usage 650.416 MB -> 74.960 MB.
[2024-11-08T00:16:52.909Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:16:55.120Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:16:57.322Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:16:59.540Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:17:00.948Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:17:02.378Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:17:03.805Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:17:05.229Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:17:05.904Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:17:05.904Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:17:05.904Z] Movies recommended for you:
[2024-11-08T00:17:05.904Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:17:05.904Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:17:05.904Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15354.724 ms) ======
[2024-11-08T00:17:05.904Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-08T00:17:05.904Z] GC before operation: completed in 191.745 ms, heap usage 320.783 MB -> 75.253 MB.
[2024-11-08T00:17:08.098Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:17:10.384Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:17:12.592Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:17:15.663Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:17:16.345Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:17:17.799Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:17:19.206Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:17:20.628Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:17:21.325Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:17:21.325Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:17:21.325Z] Movies recommended for you:
[2024-11-08T00:17:21.325Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:17:21.325Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:17:21.325Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15431.519 ms) ======
[2024-11-08T00:17:21.325Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-08T00:17:21.325Z] GC before operation: completed in 148.700 ms, heap usage 234.571 MB -> 63.009 MB.
[2024-11-08T00:17:23.543Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:17:25.760Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:17:28.860Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:17:30.276Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:17:31.703Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:17:33.124Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:17:35.329Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:17:36.751Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:17:36.751Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:17:36.751Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:17:36.751Z] Movies recommended for you:
[2024-11-08T00:17:36.751Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:17:36.751Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:17:36.751Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15240.768 ms) ======
[2024-11-08T00:17:36.751Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-08T00:17:36.751Z] GC before operation: completed in 173.080 ms, heap usage 562.186 MB -> 54.911 MB.
[2024-11-08T00:17:38.956Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:17:41.168Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:17:44.257Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:17:45.673Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:17:47.096Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:17:48.521Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:17:49.939Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:17:51.375Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:17:52.053Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:17:52.053Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:17:52.053Z] Movies recommended for you:
[2024-11-08T00:17:52.053Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:17:52.053Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:17:52.053Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15011.492 ms) ======
[2024-11-08T00:17:52.053Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-08T00:17:52.053Z] GC before operation: completed in 172.545 ms, heap usage 645.430 MB -> 76.825 MB.
[2024-11-08T00:17:54.255Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:17:56.457Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:17:58.676Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:18:00.883Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:18:02.299Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:18:03.714Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:18:05.149Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:18:06.571Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:18:06.571Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:18:07.249Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:18:07.249Z] Movies recommended for you:
[2024-11-08T00:18:07.249Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:18:07.249Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:18:07.249Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14942.647 ms) ======
[2024-11-08T00:18:07.249Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-08T00:18:07.249Z] GC before operation: completed in 246.786 ms, heap usage 613.281 MB -> 76.595 MB.
[2024-11-08T00:18:09.462Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:18:11.692Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:18:13.906Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:18:16.114Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:18:17.541Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:18:18.960Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:18:20.391Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:18:21.814Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:18:22.508Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:18:22.508Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:18:22.508Z] Movies recommended for you:
[2024-11-08T00:18:22.508Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:18:22.508Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:18:22.508Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15177.303 ms) ======
[2024-11-08T00:18:22.508Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-08T00:18:22.508Z] GC before operation: completed in 151.958 ms, heap usage 600.981 MB -> 76.054 MB.
[2024-11-08T00:18:24.733Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:18:26.971Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:18:29.661Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:18:31.900Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:18:33.307Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:18:34.717Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:18:36.137Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:18:37.562Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:18:37.562Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:18:37.562Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:18:37.562Z] Movies recommended for you:
[2024-11-08T00:18:37.562Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:18:37.562Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:18:37.562Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15169.448 ms) ======
[2024-11-08T00:18:37.562Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-08T00:18:38.240Z] GC before operation: completed in 173.118 ms, heap usage 190.461 MB -> 75.337 MB.
[2024-11-08T00:18:40.460Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:18:42.668Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:18:44.881Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:18:47.104Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:18:48.551Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:18:49.978Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:18:51.412Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:18:52.836Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:18:53.513Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:18:53.513Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:18:53.513Z] Movies recommended for you:
[2024-11-08T00:18:53.513Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:18:53.513Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:18:53.513Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15533.546 ms) ======
[2024-11-08T00:18:53.513Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-08T00:18:53.513Z] GC before operation: completed in 164.048 ms, heap usage 594.902 MB -> 76.634 MB.
[2024-11-08T00:18:55.742Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:18:57.964Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:19:01.062Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:19:02.479Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:19:03.890Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:19:05.323Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:19:06.731Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:19:08.154Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:19:08.845Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:19:08.845Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:19:08.845Z] Movies recommended for you:
[2024-11-08T00:19:08.845Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:19:08.845Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:19:08.845Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15099.096 ms) ======
[2024-11-08T00:19:08.845Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-08T00:19:08.845Z] GC before operation: completed in 164.681 ms, heap usage 698.128 MB -> 76.486 MB.
[2024-11-08T00:19:11.054Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:19:13.265Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:19:15.476Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:19:17.993Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:19:19.398Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:19:20.821Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:19:22.242Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:19:23.655Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:19:23.655Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:19:23.655Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:19:23.655Z] Movies recommended for you:
[2024-11-08T00:19:23.655Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:19:23.655Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:19:23.655Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14802.495 ms) ======
[2024-11-08T00:19:23.655Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-08T00:19:23.655Z] GC before operation: completed in 160.398 ms, heap usage 714.011 MB -> 76.734 MB.
[2024-11-08T00:19:25.869Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:19:28.078Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:19:31.153Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:19:32.594Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:19:34.826Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:19:35.523Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:19:36.946Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:19:38.368Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:19:39.053Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:19:39.053Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:19:39.053Z] Movies recommended for you:
[2024-11-08T00:19:39.053Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:19:39.053Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:19:39.053Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15060.639 ms) ======
[2024-11-08T00:19:39.053Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-08T00:19:39.053Z] GC before operation: completed in 177.152 ms, heap usage 309.836 MB -> 75.559 MB.
[2024-11-08T00:19:41.261Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:19:43.487Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:19:45.700Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:19:47.919Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:19:49.347Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:19:50.765Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:19:52.202Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:19:53.622Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:19:54.306Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:19:54.306Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:19:54.306Z] Movies recommended for you:
[2024-11-08T00:19:54.306Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:19:54.306Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:19:54.306Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15027.827 ms) ======
[2024-11-08T00:19:54.306Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-08T00:19:54.306Z] GC before operation: completed in 174.514 ms, heap usage 632.404 MB -> 76.651 MB.
[2024-11-08T00:19:56.508Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:19:58.737Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:20:00.951Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:20:03.175Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:20:05.380Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:20:06.058Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:20:07.480Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:20:08.913Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:20:09.591Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:20:09.592Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:20:09.592Z] Movies recommended for you:
[2024-11-08T00:20:09.592Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:20:09.592Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:20:09.592Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15154.542 ms) ======
[2024-11-08T00:20:09.592Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-08T00:20:09.592Z] GC before operation: completed in 133.579 ms, heap usage 194.126 MB -> 75.262 MB.
[2024-11-08T00:20:11.873Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:20:14.086Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:20:16.310Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:20:18.625Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:20:20.037Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:20:21.445Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:20:22.875Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:20:24.308Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:20:24.308Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-08T00:20:24.308Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:20:24.985Z] Movies recommended for you:
[2024-11-08T00:20:24.985Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:20:24.985Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:20:24.985Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15096.496 ms) ======
[2024-11-08T00:20:24.985Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-08T00:20:24.985Z] GC before operation: completed in 161.403 ms, heap usage 627.460 MB -> 76.931 MB.
[2024-11-08T00:20:27.193Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T00:20:29.406Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T00:20:31.609Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T00:20:33.808Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T00:20:35.244Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T00:20:36.534Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T00:20:37.959Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T00:20:39.368Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T00:20:39.369Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-08T00:20:39.369Z] The best model improves the baseline by 14.43%.
[2024-11-08T00:20:39.369Z] Movies recommended for you:
[2024-11-08T00:20:39.369Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T00:20:39.369Z] There is no way to check that no silent failure occurred.
[2024-11-08T00:20:39.369Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14671.452 ms) ======
[2024-11-08T00:20:40.794Z] -----------------------------------
[2024-11-08T00:20:40.794Z] renaissance-movie-lens_0_PASSED
[2024-11-08T00:20:40.794Z] -----------------------------------
[2024-11-08T00:20:40.794Z]
[2024-11-08T00:20:40.794Z] TEST TEARDOWN:
[2024-11-08T00:20:40.794Z] Nothing to be done for teardown.
[2024-11-08T00:20:40.794Z] renaissance-movie-lens_0 Finish Time: Thu Nov 7 18:20:40 2024 Epoch Time (ms): 1731025240441