renaissance-movie-lens_0
[2025-03-05T23:32:34.724Z] Running test renaissance-movie-lens_0 ...
[2025-03-05T23:32:34.724Z] ===============================================
[2025-03-05T23:32:34.724Z] renaissance-movie-lens_0 Start Time: Wed Mar 5 23:32:33 2025 Epoch Time (ms): 1741217553966
[2025-03-05T23:32:34.724Z] variation: NoOptions
[2025-03-05T23:32:34.724Z] JVM_OPTIONS:
[2025-03-05T23:32:34.724Z] { \
[2025-03-05T23:32:34.724Z] echo ""; echo "TEST SETUP:"; \
[2025-03-05T23:32:34.724Z] echo "Nothing to be done for setup."; \
[2025-03-05T23:32:34.724Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1741215762743/renaissance-movie-lens_0"; \
[2025-03-05T23:32:34.724Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1741215762743/renaissance-movie-lens_0"; \
[2025-03-05T23:32:34.724Z] echo ""; echo "TESTING:"; \
[2025-03-05T23:32:34.725Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1741215762743/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-03-05T23:32:34.725Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1741215762743/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-03-05T23:32:34.725Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-03-05T23:32:34.725Z] echo "Nothing to be done for teardown."; \
[2025-03-05T23:32:34.725Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_1741215762743/TestTargetResult";
[2025-03-05T23:32:34.725Z]
[2025-03-05T23:32:34.725Z] TEST SETUP:
[2025-03-05T23:32:34.725Z] Nothing to be done for setup.
[2025-03-05T23:32:34.725Z]
[2025-03-05T23:32:34.725Z] TESTING:
[2025-03-05T23:33:10.310Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-03-05T23:33:12.800Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 16) threads.
[2025-03-05T23:33:18.432Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-03-05T23:33:19.206Z] Training: 60056, validation: 20285, test: 19854
[2025-03-05T23:33:19.206Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-03-05T23:33:19.206Z] GC before operation: completed in 59.056 ms, heap usage 325.990 MB -> 37.315 MB.
[2025-03-05T23:33:27.597Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:33:31.045Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:33:35.533Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:33:40.014Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:33:41.613Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:33:43.221Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:33:46.654Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:33:49.150Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:33:49.150Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:33:49.150Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:33:49.150Z] Movies recommended for you:
[2025-03-05T23:33:49.150Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:33:49.150Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:33:49.150Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (30418.730 ms) ======
[2025-03-05T23:33:49.150Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-03-05T23:33:49.942Z] GC before operation: completed in 127.344 ms, heap usage 773.935 MB -> 53.602 MB.
[2025-03-05T23:33:53.389Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:33:55.886Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:34:01.511Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:34:04.021Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:34:06.538Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:34:08.143Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:34:10.641Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:34:13.149Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:34:13.149Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:34:13.149Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:34:13.149Z] Movies recommended for you:
[2025-03-05T23:34:13.149Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:34:13.149Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:34:13.149Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23505.753 ms) ======
[2025-03-05T23:34:13.149Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-03-05T23:34:13.149Z] GC before operation: completed in 114.043 ms, heap usage 652.198 MB -> 54.551 MB.
[2025-03-05T23:34:16.586Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:34:20.052Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:34:28.376Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:34:30.884Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:34:33.378Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:34:35.883Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:34:38.363Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:34:40.856Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:34:40.856Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:34:40.856Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:34:40.856Z] Movies recommended for you:
[2025-03-05T23:34:40.856Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:34:40.856Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:34:40.856Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (27958.913 ms) ======
[2025-03-05T23:34:40.856Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-03-05T23:34:41.627Z] GC before operation: completed in 119.207 ms, heap usage 404.499 MB -> 54.730 MB.
[2025-03-05T23:34:44.114Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:34:47.558Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:34:51.017Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:34:54.477Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:34:56.076Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:34:57.675Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:35:00.153Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:35:01.761Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:35:02.535Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:35:02.535Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:35:02.535Z] Movies recommended for you:
[2025-03-05T23:35:02.535Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:35:02.535Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:35:02.535Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21090.434 ms) ======
[2025-03-05T23:35:02.535Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-03-05T23:35:02.535Z] GC before operation: completed in 134.679 ms, heap usage 565.677 MB -> 55.165 MB.
[2025-03-05T23:35:05.991Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:35:08.849Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:35:14.480Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:35:16.972Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:35:19.475Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:35:21.072Z] RMSE (validation) = 1.117495376637101 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:35:24.516Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:35:26.116Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:35:26.116Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:35:26.116Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:35:26.116Z] Movies recommended for you:
[2025-03-05T23:35:26.116Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:35:26.116Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:35:26.116Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (23639.777 ms) ======
[2025-03-05T23:35:26.116Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-03-05T23:35:26.116Z] GC before operation: completed in 107.649 ms, heap usage 358.836 MB -> 51.897 MB.
[2025-03-05T23:35:29.560Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:35:32.056Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:35:40.372Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:35:43.809Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:35:46.291Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:35:48.775Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:35:53.256Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:35:54.891Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:35:55.672Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:35:55.672Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:35:55.672Z] Movies recommended for you:
[2025-03-05T23:35:55.672Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:35:55.672Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:35:55.672Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (29350.707 ms) ======
[2025-03-05T23:35:55.672Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-03-05T23:35:55.672Z] GC before operation: completed in 121.725 ms, heap usage 312.826 MB -> 51.875 MB.
[2025-03-05T23:35:59.131Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:36:01.618Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:36:06.101Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:36:08.584Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:36:11.066Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:36:12.674Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:36:15.173Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:36:16.782Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:36:17.564Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:36:17.564Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:36:17.564Z] Movies recommended for you:
[2025-03-05T23:36:17.564Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:36:17.564Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:36:17.565Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21653.627 ms) ======
[2025-03-05T23:36:17.565Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-03-05T23:36:17.565Z] GC before operation: completed in 111.749 ms, heap usage 307.916 MB -> 52.050 MB.
[2025-03-05T23:36:21.054Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:36:23.543Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:36:29.191Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:36:31.675Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:36:33.277Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:36:34.874Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:36:38.317Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:36:39.925Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:36:39.925Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:36:39.925Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:36:40.698Z] Movies recommended for you:
[2025-03-05T23:36:40.698Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:36:40.698Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:36:40.698Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22829.458 ms) ======
[2025-03-05T23:36:40.698Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-03-05T23:36:40.698Z] GC before operation: completed in 142.216 ms, heap usage 631.457 MB -> 55.746 MB.
[2025-03-05T23:36:43.178Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:36:47.719Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:37:01.560Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:37:05.014Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:37:13.319Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:37:16.773Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:37:20.227Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:37:21.836Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:37:21.836Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:37:21.836Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:37:22.609Z] Movies recommended for you:
[2025-03-05T23:37:22.609Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:37:22.609Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:37:22.609Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (41772.451 ms) ======
[2025-03-05T23:37:22.609Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-03-05T23:37:22.609Z] GC before operation: completed in 119.141 ms, heap usage 598.382 MB -> 55.560 MB.
[2025-03-05T23:37:25.096Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:37:28.575Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:37:35.498Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:37:38.018Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:37:39.827Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:37:41.431Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:37:47.064Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:37:48.847Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:37:48.847Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:37:48.847Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:37:48.847Z] Movies recommended for you:
[2025-03-05T23:37:48.847Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:37:48.847Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:37:48.847Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26796.483 ms) ======
[2025-03-05T23:37:48.847Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-03-05T23:37:49.619Z] GC before operation: completed in 126.697 ms, heap usage 807.012 MB -> 55.965 MB.
[2025-03-05T23:37:53.069Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:37:57.602Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:38:07.541Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:38:10.048Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:38:12.534Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:38:15.032Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:38:26.749Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:38:27.526Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:38:27.526Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:38:27.526Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:38:27.526Z] Movies recommended for you:
[2025-03-05T23:38:27.526Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:38:27.526Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:38:27.526Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (38556.156 ms) ======
[2025-03-05T23:38:27.526Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-03-05T23:38:28.300Z] GC before operation: completed in 113.092 ms, heap usage 508.643 MB -> 55.333 MB.
[2025-03-05T23:38:30.798Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:38:36.440Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:38:44.795Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:38:47.293Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:38:48.892Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:38:50.494Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:38:53.940Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:38:55.555Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:38:56.329Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:38:56.329Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:38:56.329Z] Movies recommended for you:
[2025-03-05T23:38:56.329Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:38:56.329Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:38:56.329Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (28140.424 ms) ======
[2025-03-05T23:38:56.329Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-03-05T23:38:56.329Z] GC before operation: completed in 132.375 ms, heap usage 431.425 MB -> 52.261 MB.
[2025-03-05T23:38:59.781Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:39:02.279Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:39:07.935Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:39:10.428Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:39:12.911Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:39:14.526Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:39:17.021Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:39:19.513Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:39:19.513Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:39:19.513Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:39:19.513Z] Movies recommended for you:
[2025-03-05T23:39:19.513Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:39:19.513Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:39:19.513Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (23369.469 ms) ======
[2025-03-05T23:39:19.513Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-03-05T23:39:19.513Z] GC before operation: completed in 133.334 ms, heap usage 312.900 MB -> 52.326 MB.
[2025-03-05T23:39:22.954Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:39:25.445Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:39:37.180Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:39:40.641Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:39:44.098Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:39:45.694Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:39:48.184Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:39:50.668Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:39:50.668Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:39:50.668Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:39:50.668Z] Movies recommended for you:
[2025-03-05T23:39:50.668Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:39:50.668Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:39:50.668Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (30983.975 ms) ======
[2025-03-05T23:39:50.668Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-03-05T23:39:50.668Z] GC before operation: completed in 122.205 ms, heap usage 263.295 MB -> 51.978 MB.
[2025-03-05T23:39:54.490Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:39:56.992Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:40:04.111Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:40:06.629Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:40:08.239Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:40:09.844Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:40:12.422Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:40:14.955Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:40:14.955Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:40:14.955Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:40:14.955Z] Movies recommended for you:
[2025-03-05T23:40:14.955Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:40:14.955Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:40:14.955Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (24125.967 ms) ======
[2025-03-05T23:40:14.955Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-03-05T23:40:14.955Z] GC before operation: completed in 143.537 ms, heap usage 87.002 MB -> 52.955 MB.
[2025-03-05T23:40:18.403Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:40:21.846Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:40:35.630Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:40:39.070Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:40:40.668Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:40:45.168Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:41:11.055Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:41:13.549Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:41:13.549Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:41:13.549Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:41:13.549Z] Movies recommended for you:
[2025-03-05T23:41:13.549Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:41:13.549Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:41:13.549Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (58517.954 ms) ======
[2025-03-05T23:41:13.549Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-03-05T23:41:13.549Z] GC before operation: completed in 149.941 ms, heap usage 98.097 MB -> 56.007 MB.
[2025-03-05T23:41:17.026Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:41:19.525Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:41:26.443Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:41:28.926Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:41:31.424Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:41:33.063Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:41:38.963Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:41:41.450Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:41:42.224Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:41:42.224Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:41:42.224Z] Movies recommended for you:
[2025-03-05T23:41:42.224Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:41:42.224Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:41:42.224Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (28294.357 ms) ======
[2025-03-05T23:41:42.224Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-03-05T23:41:42.224Z] GC before operation: completed in 148.030 ms, heap usage 263.357 MB -> 52.089 MB.
[2025-03-05T23:41:45.681Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:41:48.187Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:41:56.526Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:41:59.018Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:42:00.619Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:42:02.221Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:42:06.710Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:42:08.339Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:42:08.339Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:42:08.339Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:42:08.339Z] Movies recommended for you:
[2025-03-05T23:42:08.339Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:42:08.340Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:42:08.340Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26434.741 ms) ======
[2025-03-05T23:42:08.340Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-03-05T23:42:09.113Z] GC before operation: completed in 144.749 ms, heap usage 626.192 MB -> 55.686 MB.
[2025-03-05T23:42:11.605Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:42:17.228Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:42:39.417Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:42:40.191Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:42:42.675Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:42:44.272Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:42:48.932Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:42:50.531Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:42:50.531Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:42:50.531Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:42:50.531Z] Movies recommended for you:
[2025-03-05T23:42:50.531Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:42:50.531Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:42:50.531Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42012.582 ms) ======
[2025-03-05T23:42:50.531Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-03-05T23:42:51.310Z] GC before operation: completed in 129.760 ms, heap usage 788.679 MB -> 56.141 MB.
[2025-03-05T23:42:53.974Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T23:42:57.437Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T23:43:07.351Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T23:43:10.811Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T23:43:12.411Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T23:43:14.015Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T23:43:18.510Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T23:43:20.110Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T23:43:20.110Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T23:43:20.110Z] The best model improves the baseline by 14.43%.
[2025-03-05T23:43:20.110Z] Movies recommended for you:
[2025-03-05T23:43:20.110Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T23:43:20.110Z] There is no way to check that no silent failure occurred.
[2025-03-05T23:43:20.110Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (29197.918 ms) ======
[2025-03-05T23:43:20.883Z] -----------------------------------
[2025-03-05T23:43:20.883Z] renaissance-movie-lens_0_PASSED
[2025-03-05T23:43:20.883Z] -----------------------------------
[2025-03-05T23:43:20.883Z]
[2025-03-05T23:43:20.883Z] TEST TEARDOWN:
[2025-03-05T23:43:20.883Z] Nothing to be done for teardown.
[2025-03-05T23:43:20.883Z] renaissance-movie-lens_0 Finish Time: Wed Mar 5 23:43:20 2025 Epoch Time (ms): 1741218200711