renaissance-movie-lens_0
[2025-02-06T22:12:05.897Z] Running test renaissance-movie-lens_0 ...
[2025-02-06T22:12:05.897Z] ===============================================
[2025-02-06T22:12:05.897Z] renaissance-movie-lens_0 Start Time: Thu Feb 6 22:12:04 2025 Epoch Time (ms): 1738879924586
[2025-02-06T22:12:05.897Z] variation: NoOptions
[2025-02-06T22:12:05.897Z] JVM_OPTIONS:
[2025-02-06T22:12:05.897Z] { \
[2025-02-06T22:12:05.897Z] echo ""; echo "TEST SETUP:"; \
[2025-02-06T22:12:05.897Z] echo "Nothing to be done for setup."; \
[2025-02-06T22:12:05.897Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1738878823326/renaissance-movie-lens_0"; \
[2025-02-06T22:12:05.897Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1738878823326/renaissance-movie-lens_0"; \
[2025-02-06T22:12:05.897Z] echo ""; echo "TESTING:"; \
[2025-02-06T22:12:05.897Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1738878823326/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-06T22:12:05.897Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1738878823326/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-06T22:12:05.897Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-06T22:12:05.897Z] echo "Nothing to be done for teardown."; \
[2025-02-06T22:12:05.897Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1738878823326/TestTargetResult";
[2025-02-06T22:12:05.897Z]
[2025-02-06T22:12:05.897Z] TEST SETUP:
[2025-02-06T22:12:05.897Z] Nothing to be done for setup.
[2025-02-06T22:12:05.897Z]
[2025-02-06T22:12:05.897Z] TESTING:
[2025-02-06T22:12:10.363Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-06T22:12:13.786Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2025-02-06T22:12:19.391Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-06T22:12:20.165Z] Training: 60056, validation: 20285, test: 19854
[2025-02-06T22:12:20.165Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-06T22:12:20.165Z] GC before operation: completed in 247.261 ms, heap usage 234.537 MB -> 26.633 MB.
[2025-02-06T22:12:28.483Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:12:34.084Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:12:39.694Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:12:44.165Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:12:45.760Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:12:49.222Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:12:51.700Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:12:54.198Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:12:54.198Z] 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.
[2025-02-06T22:12:54.198Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:12:54.198Z] Movies recommended for you:
[2025-02-06T22:12:54.198Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:12:54.198Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:12:54.198Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (34415.362 ms) ======
[2025-02-06T22:12:54.198Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-06T22:12:54.966Z] GC before operation: completed in 281.128 ms, heap usage 124.516 MB -> 46.445 MB.
[2025-02-06T22:12:59.436Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:13:03.049Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:13:07.517Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:13:11.990Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:13:14.463Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:13:16.932Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:13:19.403Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:13:21.880Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:13:21.880Z] 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.
[2025-02-06T22:13:22.654Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:13:22.654Z] Movies recommended for you:
[2025-02-06T22:13:22.654Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:13:22.654Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:13:22.654Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (27609.357 ms) ======
[2025-02-06T22:13:22.654Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-06T22:13:22.654Z] GC before operation: completed in 195.259 ms, heap usage 234.915 MB -> 47.195 MB.
[2025-02-06T22:13:27.109Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:13:30.550Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:13:35.013Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:13:39.483Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:13:41.960Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:13:44.448Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:13:46.215Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:13:48.705Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:13:49.481Z] 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.
[2025-02-06T22:13:49.481Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:13:49.481Z] Movies recommended for you:
[2025-02-06T22:13:49.481Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:13:49.481Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:13:49.482Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (26685.700 ms) ======
[2025-02-06T22:13:49.482Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-06T22:13:49.482Z] GC before operation: completed in 217.381 ms, heap usage 238.979 MB -> 44.653 MB.
[2025-02-06T22:13:53.985Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:13:57.412Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:14:01.942Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:14:06.432Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:14:08.906Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:14:10.518Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:14:12.984Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:14:15.468Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:14:15.468Z] 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.
[2025-02-06T22:14:16.277Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:14:16.277Z] Movies recommended for you:
[2025-02-06T22:14:16.277Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:14:16.277Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:14:16.277Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (26479.704 ms) ======
[2025-02-06T22:14:16.277Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-06T22:14:16.277Z] GC before operation: completed in 239.603 ms, heap usage 343.878 MB -> 45.527 MB.
[2025-02-06T22:14:20.743Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:14:24.187Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:14:28.650Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:14:33.125Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:14:35.607Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:14:38.080Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:14:39.669Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:14:42.156Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:14:42.928Z] 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.
[2025-02-06T22:14:42.928Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:14:42.928Z] Movies recommended for you:
[2025-02-06T22:14:42.928Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:14:42.928Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:14:42.928Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (26687.985 ms) ======
[2025-02-06T22:14:42.928Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-06T22:14:42.928Z] GC before operation: completed in 217.544 ms, heap usage 278.143 MB -> 46.966 MB.
[2025-02-06T22:14:47.395Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:14:50.818Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:14:55.296Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:14:59.765Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:15:01.356Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:15:03.832Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:15:06.311Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:15:08.784Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:15:09.552Z] 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.
[2025-02-06T22:15:09.552Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:15:09.552Z] Movies recommended for you:
[2025-02-06T22:15:09.552Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:15:09.552Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:15:09.552Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (26330.313 ms) ======
[2025-02-06T22:15:09.552Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-06T22:15:09.552Z] GC before operation: completed in 228.518 ms, heap usage 222.012 MB -> 54.346 MB.
[2025-02-06T22:15:14.026Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:15:18.506Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:15:22.971Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:15:26.389Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:15:28.855Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:15:31.336Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:15:32.971Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:15:36.402Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:15:36.402Z] 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.
[2025-02-06T22:15:36.402Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:15:36.402Z] Movies recommended for you:
[2025-02-06T22:15:36.402Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:15:36.402Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:15:36.402Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (26748.701 ms) ======
[2025-02-06T22:15:36.402Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-06T22:15:36.402Z] GC before operation: completed in 222.479 ms, heap usage 365.582 MB -> 47.581 MB.
[2025-02-06T22:15:40.871Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:15:45.349Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:15:49.821Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:15:53.249Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:15:55.721Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:15:58.201Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:16:00.668Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:16:03.185Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:16:03.186Z] 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.
[2025-02-06T22:16:03.186Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:16:03.186Z] Movies recommended for you:
[2025-02-06T22:16:03.186Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:16:03.186Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:16:03.186Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (26656.297 ms) ======
[2025-02-06T22:16:03.186Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-06T22:16:03.954Z] GC before operation: completed in 235.598 ms, heap usage 438.082 MB -> 75.143 MB.
[2025-02-06T22:16:08.431Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:16:11.852Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:16:16.322Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:16:20.778Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:16:22.374Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:16:24.852Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:16:27.698Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:16:30.205Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:16:30.205Z] 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.
[2025-02-06T22:16:30.205Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:16:30.205Z] Movies recommended for you:
[2025-02-06T22:16:30.205Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:16:30.205Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:16:30.205Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (26949.783 ms) ======
[2025-02-06T22:16:30.205Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-06T22:16:30.974Z] GC before operation: completed in 181.483 ms, heap usage 391.358 MB -> 47.478 MB.
[2025-02-06T22:16:34.399Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:16:38.879Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:16:43.342Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:16:47.803Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:16:49.392Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:16:51.872Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:16:54.347Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:16:56.829Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:16:56.829Z] 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.
[2025-02-06T22:16:57.621Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:16:57.621Z] Movies recommended for you:
[2025-02-06T22:16:57.621Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:16:57.621Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:16:57.621Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26630.375 ms) ======
[2025-02-06T22:16:57.621Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-06T22:16:57.621Z] GC before operation: completed in 268.283 ms, heap usage 433.291 MB -> 75.215 MB.
[2025-02-06T22:17:02.111Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:17:05.555Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:17:10.018Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:17:14.484Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:17:16.072Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:17:18.542Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:17:21.038Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:17:23.519Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:17:23.519Z] 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.
[2025-02-06T22:17:23.519Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:17:24.290Z] Movies recommended for you:
[2025-02-06T22:17:24.290Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:17:24.290Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:17:24.290Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (26425.837 ms) ======
[2025-02-06T22:17:24.290Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-06T22:17:24.290Z] GC before operation: completed in 186.362 ms, heap usage 388.580 MB -> 43.920 MB.
[2025-02-06T22:17:28.758Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:17:32.189Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:17:36.842Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:17:40.266Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:17:42.737Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:17:45.219Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:17:47.693Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:17:50.179Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:17:50.179Z] 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.
[2025-02-06T22:17:50.179Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:17:50.951Z] Movies recommended for you:
[2025-02-06T22:17:50.951Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:17:50.951Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:17:50.951Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (26390.588 ms) ======
[2025-02-06T22:17:50.951Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-06T22:17:50.951Z] GC before operation: completed in 222.142 ms, heap usage 224.337 MB -> 74.139 MB.
[2025-02-06T22:17:55.421Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:17:58.857Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:18:03.326Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:18:07.801Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:18:10.283Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:18:12.790Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:18:15.274Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:18:16.881Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:18:17.651Z] 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.
[2025-02-06T22:18:17.651Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:18:17.651Z] Movies recommended for you:
[2025-02-06T22:18:17.651Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:18:17.651Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:18:17.651Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (26894.427 ms) ======
[2025-02-06T22:18:17.651Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-06T22:18:17.651Z] GC before operation: completed in 219.323 ms, heap usage 308.299 MB -> 55.350 MB.
[2025-02-06T22:18:22.146Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:18:26.621Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:18:30.060Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:18:34.525Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:18:37.016Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:18:39.486Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:18:41.957Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:18:44.470Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:18:44.470Z] 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.
[2025-02-06T22:18:44.470Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:18:44.470Z] Movies recommended for you:
[2025-02-06T22:18:44.470Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:18:44.470Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:18:44.470Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (26815.942 ms) ======
[2025-02-06T22:18:44.470Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-06T22:18:45.428Z] GC before operation: completed in 217.048 ms, heap usage 239.768 MB -> 47.316 MB.
[2025-02-06T22:18:48.851Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:18:53.320Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:18:57.782Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:19:02.258Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:19:03.854Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:19:06.334Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:19:08.814Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:19:11.297Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:19:12.065Z] 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.
[2025-02-06T22:19:12.065Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:19:12.065Z] Movies recommended for you:
[2025-02-06T22:19:12.065Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:19:12.065Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:19:12.065Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (26917.913 ms) ======
[2025-02-06T22:19:12.065Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-06T22:19:12.065Z] GC before operation: completed in 225.824 ms, heap usage 385.909 MB -> 74.997 MB.
[2025-02-06T22:19:16.541Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:19:21.008Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:19:25.483Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:19:28.907Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:19:31.381Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:19:33.862Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:19:36.332Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:19:38.811Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:19:38.811Z] 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.
[2025-02-06T22:19:38.811Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:19:38.811Z] Movies recommended for you:
[2025-02-06T22:19:38.811Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:19:38.811Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:19:38.811Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (27063.717 ms) ======
[2025-02-06T22:19:38.811Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-06T22:19:39.583Z] GC before operation: completed in 231.671 ms, heap usage 456.794 MB -> 75.008 MB.
[2025-02-06T22:19:44.053Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:19:47.487Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:19:51.954Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:19:56.592Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:19:59.066Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:20:01.551Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:20:04.028Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:20:06.518Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:20:06.518Z] 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.
[2025-02-06T22:20:06.518Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:20:06.518Z] Movies recommended for you:
[2025-02-06T22:20:06.518Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:20:06.518Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:20:06.518Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (27259.691 ms) ======
[2025-02-06T22:20:06.518Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-06T22:20:06.518Z] GC before operation: completed in 205.645 ms, heap usage 274.688 MB -> 55.106 MB.
[2025-02-06T22:20:10.981Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:20:15.455Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:20:19.946Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:20:23.383Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:20:25.858Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:20:28.332Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:20:30.799Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:20:33.284Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:20:33.284Z] 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.
[2025-02-06T22:20:34.100Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:20:34.100Z] Movies recommended for you:
[2025-02-06T22:20:34.100Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:20:34.100Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:20:34.100Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26922.956 ms) ======
[2025-02-06T22:20:34.100Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-06T22:20:34.100Z] GC before operation: completed in 232.907 ms, heap usage 404.266 MB -> 74.626 MB.
[2025-02-06T22:20:38.561Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:20:43.051Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:20:47.526Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:20:50.951Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:20:53.424Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:20:55.902Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:20:58.385Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:21:01.235Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:21:02.008Z] 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.
[2025-02-06T22:21:02.008Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:21:02.008Z] Movies recommended for you:
[2025-02-06T22:21:02.008Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:21:02.008Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:21:02.008Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27575.632 ms) ======
[2025-02-06T22:21:02.008Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-06T22:21:02.008Z] GC before operation: completed in 212.503 ms, heap usage 347.836 MB -> 74.602 MB.
[2025-02-06T22:21:06.470Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T22:21:09.902Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T22:21:14.372Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T22:21:18.860Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T22:21:21.342Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T22:21:23.836Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T22:21:26.314Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T22:21:28.813Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T22:21:28.813Z] 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.
[2025-02-06T22:21:28.813Z] The best model improves the baseline by 14.43%.
[2025-02-06T22:21:28.813Z] Movies recommended for you:
[2025-02-06T22:21:28.813Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T22:21:28.813Z] There is no way to check that no silent failure occurred.
[2025-02-06T22:21:28.813Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (26989.119 ms) ======
[2025-02-06T22:21:29.581Z] -----------------------------------
[2025-02-06T22:21:29.581Z] renaissance-movie-lens_0_PASSED
[2025-02-06T22:21:29.581Z] -----------------------------------
[2025-02-06T22:21:29.581Z]
[2025-02-06T22:21:29.581Z] TEST TEARDOWN:
[2025-02-06T22:21:29.581Z] Nothing to be done for teardown.
[2025-02-06T22:21:29.581Z] renaissance-movie-lens_0 Finish Time: Thu Feb 6 22:21:29 2025 Epoch Time (ms): 1738880489272