renaissance-movie-lens_0
[2025-02-25T22:11:15.138Z] Running test renaissance-movie-lens_0 ...
[2025-02-25T22:11:15.138Z] ===============================================
[2025-02-25T22:11:15.138Z] renaissance-movie-lens_0 Start Time: Tue Feb 25 22:11:13 2025 Epoch Time (ms): 1740521473648
[2025-02-25T22:11:15.138Z] variation: NoOptions
[2025-02-25T22:11:15.138Z] JVM_OPTIONS:
[2025-02-25T22:11:15.138Z] { \
[2025-02-25T22:11:15.138Z] echo ""; echo "TEST SETUP:"; \
[2025-02-25T22:11:15.138Z] echo "Nothing to be done for setup."; \
[2025-02-25T22:11:15.138Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17405198451349/renaissance-movie-lens_0"; \
[2025-02-25T22:11:15.138Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17405198451349/renaissance-movie-lens_0"; \
[2025-02-25T22:11:15.138Z] echo ""; echo "TESTING:"; \
[2025-02-25T22:11:15.138Z] "/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_17405198451349/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-25T22:11:15.138Z] 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_17405198451349/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-25T22:11:15.138Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-25T22:11:15.138Z] echo "Nothing to be done for teardown."; \
[2025-02-25T22:11:15.138Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17405198451349/TestTargetResult";
[2025-02-25T22:11:15.138Z]
[2025-02-25T22:11:15.138Z] TEST SETUP:
[2025-02-25T22:11:15.138Z] Nothing to be done for setup.
[2025-02-25T22:11:15.138Z]
[2025-02-25T22:11:15.138Z] TESTING:
[2025-02-25T22:11:34.396Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-25T22:11:37.834Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 16) threads.
[2025-02-25T22:11:44.767Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-25T22:11:44.767Z] Training: 60056, validation: 20285, test: 19854
[2025-02-25T22:11:44.767Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-25T22:11:44.767Z] GC before operation: completed in 276.267 ms, heap usage 114.410 MB -> 26.043 MB.
[2025-02-25T22:11:53.126Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:11:58.771Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:12:05.667Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:12:10.164Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:12:12.647Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:12:16.127Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:12:18.608Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:12:22.066Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:12:22.066Z] 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.
[2025-02-25T22:12:22.066Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:12:22.066Z] Movies recommended for you:
[2025-02-25T22:12:22.066Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:12:22.066Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:12:22.066Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (37713.828 ms) ======
[2025-02-25T22:12:22.066Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-25T22:12:22.840Z] GC before operation: completed in 305.396 ms, heap usage 308.035 MB -> 46.550 MB.
[2025-02-25T22:12:27.322Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:12:31.811Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:12:37.455Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:12:43.700Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:12:45.307Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:12:47.789Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:12:51.277Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:12:53.761Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:12:53.761Z] 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.
[2025-02-25T22:12:54.539Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:12:54.539Z] Movies recommended for you:
[2025-02-25T22:12:54.539Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:12:54.539Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:12:54.539Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (31705.314 ms) ======
[2025-02-25T22:12:54.539Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-25T22:12:54.539Z] GC before operation: completed in 308.859 ms, heap usage 195.576 MB -> 45.915 MB.
[2025-02-25T22:13:00.173Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:13:03.971Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:13:09.618Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:13:14.116Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:13:17.564Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:13:20.047Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:13:22.535Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:13:25.975Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:13:25.975Z] 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.
[2025-02-25T22:13:25.975Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:13:25.975Z] Movies recommended for you:
[2025-02-25T22:13:25.975Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:13:25.975Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:13:25.975Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (31413.155 ms) ======
[2025-02-25T22:13:25.975Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-25T22:13:25.975Z] GC before operation: completed in 269.752 ms, heap usage 177.521 MB -> 46.228 MB.
[2025-02-25T22:13:30.501Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:13:37.814Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:13:41.264Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:13:45.761Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:13:48.263Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:13:50.839Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:13:53.322Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:13:56.958Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:13:56.958Z] 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.
[2025-02-25T22:13:56.958Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:13:56.958Z] Movies recommended for you:
[2025-02-25T22:13:56.958Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:13:56.958Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:13:56.958Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (30673.438 ms) ======
[2025-02-25T22:13:56.958Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-25T22:13:56.958Z] GC before operation: completed in 214.777 ms, heap usage 257.748 MB -> 46.757 MB.
[2025-02-25T22:14:01.442Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:14:05.923Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:14:11.788Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:14:16.285Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:14:18.777Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:14:21.260Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:14:23.756Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:14:26.248Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:14:27.037Z] 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.
[2025-02-25T22:14:27.037Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:14:27.037Z] Movies recommended for you:
[2025-02-25T22:14:27.037Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:14:27.037Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:14:27.037Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (29794.499 ms) ======
[2025-02-25T22:14:27.037Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-25T22:14:27.037Z] GC before operation: completed in 232.056 ms, heap usage 241.760 MB -> 74.080 MB.
[2025-02-25T22:14:31.534Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:14:36.013Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:14:41.649Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:14:46.146Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:14:48.637Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:14:51.128Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:14:53.607Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:14:57.066Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:14:57.066Z] 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.
[2025-02-25T22:14:57.066Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:14:57.838Z] Movies recommended for you:
[2025-02-25T22:14:57.838Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:14:57.838Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:14:57.838Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (30260.777 ms) ======
[2025-02-25T22:14:57.838Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-25T22:14:57.838Z] GC before operation: completed in 259.797 ms, heap usage 386.621 MB -> 47.208 MB.
[2025-02-25T22:15:02.376Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:15:06.890Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:15:12.535Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:15:17.026Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:15:19.509Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:15:21.997Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:15:24.484Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:15:26.973Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:15:27.749Z] 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.
[2025-02-25T22:15:27.749Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:15:27.749Z] Movies recommended for you:
[2025-02-25T22:15:27.749Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:15:27.749Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:15:27.749Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (30079.419 ms) ======
[2025-02-25T22:15:27.749Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-25T22:15:27.749Z] GC before operation: completed in 215.523 ms, heap usage 339.384 MB -> 74.416 MB.
[2025-02-25T22:15:32.264Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:15:36.767Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:15:42.392Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:15:46.937Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:15:49.423Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:15:51.909Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:15:55.364Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:15:57.855Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:15:57.855Z] 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.
[2025-02-25T22:15:57.855Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:15:57.855Z] Movies recommended for you:
[2025-02-25T22:15:57.855Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:15:57.855Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:15:57.855Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (29950.758 ms) ======
[2025-02-25T22:15:57.855Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-25T22:15:57.855Z] GC before operation: completed in 218.911 ms, heap usage 437.755 MB -> 75.222 MB.
[2025-02-25T22:16:02.354Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:16:08.004Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:16:21.808Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:16:27.435Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:16:30.884Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:16:33.367Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:16:40.282Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:16:43.721Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:16:43.721Z] 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.
[2025-02-25T22:16:43.721Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:16:43.721Z] Movies recommended for you:
[2025-02-25T22:16:43.721Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:16:43.721Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:16:43.721Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (45546.436 ms) ======
[2025-02-25T22:16:43.721Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-25T22:16:43.721Z] GC before operation: completed in 268.840 ms, heap usage 279.222 MB -> 74.678 MB.
[2025-02-25T22:16:49.365Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:16:54.037Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:16:59.696Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:17:04.180Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:17:06.661Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:17:09.160Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:17:12.608Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:17:16.082Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:17:16.082Z] 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.
[2025-02-25T22:17:16.082Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:17:16.082Z] Movies recommended for you:
[2025-02-25T22:17:16.082Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:17:16.082Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:17:16.083Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (32113.602 ms) ======
[2025-02-25T22:17:16.083Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-25T22:17:16.083Z] GC before operation: completed in 227.343 ms, heap usage 286.769 MB -> 51.634 MB.
[2025-02-25T22:17:20.594Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:17:26.216Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:17:31.851Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:17:36.332Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:17:40.371Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:17:43.922Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:17:45.524Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:17:48.022Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:17:49.257Z] 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.
[2025-02-25T22:17:49.257Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:17:49.257Z] Movies recommended for you:
[2025-02-25T22:17:49.257Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:17:49.257Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:17:49.257Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (32531.914 ms) ======
[2025-02-25T22:17:49.257Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-25T22:17:49.257Z] GC before operation: completed in 208.869 ms, heap usage 257.208 MB -> 61.839 MB.
[2025-02-25T22:17:53.702Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:17:58.192Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:18:05.096Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:18:08.545Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:18:11.027Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:18:14.476Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:18:16.983Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:18:19.477Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:18:19.477Z] 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.
[2025-02-25T22:18:19.477Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:18:20.252Z] Movies recommended for you:
[2025-02-25T22:18:20.252Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:18:20.252Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:18:20.252Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (30857.054 ms) ======
[2025-02-25T22:18:20.252Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-25T22:18:20.252Z] GC before operation: completed in 301.941 ms, heap usage 460.092 MB -> 74.855 MB.
[2025-02-25T22:18:24.739Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:18:29.217Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:18:36.123Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:18:40.609Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:18:43.097Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:18:45.585Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:18:49.044Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:18:51.528Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:18:51.528Z] 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.
[2025-02-25T22:18:51.528Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:18:52.303Z] Movies recommended for you:
[2025-02-25T22:18:52.303Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:18:52.303Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:18:52.303Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (31727.416 ms) ======
[2025-02-25T22:18:52.303Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-25T22:18:52.303Z] GC before operation: completed in 189.179 ms, heap usage 233.998 MB -> 47.549 MB.
[2025-02-25T22:18:56.861Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:19:01.367Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:19:08.465Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:19:13.161Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:19:15.646Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:19:18.181Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:19:21.624Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:19:24.105Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:19:24.105Z] 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.
[2025-02-25T22:19:24.105Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:19:24.883Z] Movies recommended for you:
[2025-02-25T22:19:24.883Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:19:24.883Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:19:24.883Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (32397.738 ms) ======
[2025-02-25T22:19:24.883Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-25T22:19:24.883Z] GC before operation: completed in 199.563 ms, heap usage 157.489 MB -> 73.976 MB.
[2025-02-25T22:19:29.379Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:19:35.037Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:19:41.967Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:19:46.477Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:19:48.972Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:19:51.457Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:19:54.914Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:19:57.406Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:19:58.182Z] 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.
[2025-02-25T22:19:58.182Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:19:58.182Z] Movies recommended for you:
[2025-02-25T22:19:58.182Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:19:58.182Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:19:58.182Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (33154.734 ms) ======
[2025-02-25T22:19:58.182Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-25T22:19:58.182Z] GC before operation: completed in 290.834 ms, heap usage 445.615 MB -> 75.183 MB.
[2025-02-25T22:20:02.677Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:20:08.311Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:20:17.049Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:20:20.525Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:20:23.014Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:20:25.509Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:20:31.146Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:20:33.675Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:20:34.448Z] 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.
[2025-02-25T22:20:34.449Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:20:34.449Z] Movies recommended for you:
[2025-02-25T22:20:34.449Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:20:34.449Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:20:34.449Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (36207.045 ms) ======
[2025-02-25T22:20:34.449Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-25T22:20:34.449Z] GC before operation: completed in 246.757 ms, heap usage 389.093 MB -> 52.393 MB.
[2025-02-25T22:20:38.950Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:20:44.643Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:20:52.970Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:20:57.446Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:21:00.900Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:21:03.429Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:21:14.236Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:21:15.851Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:21:15.851Z] 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.
[2025-02-25T22:21:15.851Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:21:16.634Z] Movies recommended for you:
[2025-02-25T22:21:16.634Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:21:16.634Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:21:16.634Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (41536.880 ms) ======
[2025-02-25T22:21:16.634Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-25T22:21:16.634Z] GC before operation: completed in 238.250 ms, heap usage 169.444 MB -> 74.982 MB.
[2025-02-25T22:21:21.123Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:21:26.758Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:21:32.404Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:21:36.892Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:21:40.435Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:21:42.934Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:21:46.388Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:21:48.894Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:21:49.667Z] 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.
[2025-02-25T22:21:49.667Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:21:49.667Z] Movies recommended for you:
[2025-02-25T22:21:49.667Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:21:49.667Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:21:49.667Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (33105.121 ms) ======
[2025-02-25T22:21:49.667Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-25T22:21:49.667Z] GC before operation: completed in 253.539 ms, heap usage 313.699 MB -> 75.303 MB.
[2025-02-25T22:21:55.293Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:21:59.805Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:22:08.148Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:22:13.773Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:22:16.269Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:22:18.766Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:22:24.401Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:22:26.893Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:22:27.666Z] 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.
[2025-02-25T22:22:27.666Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:22:27.666Z] Movies recommended for you:
[2025-02-25T22:22:27.666Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:22:27.666Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:22:27.666Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (37527.857 ms) ======
[2025-02-25T22:22:27.666Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-25T22:22:27.666Z] GC before operation: completed in 190.503 ms, heap usage 290.973 MB -> 67.459 MB.
[2025-02-25T22:22:34.049Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:22:37.539Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:22:44.450Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:22:48.944Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:22:52.379Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:22:54.873Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:22:57.712Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:23:00.192Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:23:00.974Z] 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.
[2025-02-25T22:23:00.974Z] The best model improves the baseline by 14.43%.
[2025-02-25T22:23:00.974Z] Movies recommended for you:
[2025-02-25T22:23:00.974Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:23:00.974Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:23:00.974Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (33377.161 ms) ======
[2025-02-25T22:23:02.594Z] -----------------------------------
[2025-02-25T22:23:02.594Z] renaissance-movie-lens_0_PASSED
[2025-02-25T22:23:02.594Z] -----------------------------------
[2025-02-25T22:23:02.594Z]
[2025-02-25T22:23:02.594Z] TEST TEARDOWN:
[2025-02-25T22:23:02.594Z] Nothing to be done for teardown.
[2025-02-25T22:23:02.594Z] renaissance-movie-lens_0 Finish Time: Tue Feb 25 22:23:02 2025 Epoch Time (ms): 1740522182014