renaissance-movie-lens_0
[2025-02-12T21:55:07.418Z] Running test renaissance-movie-lens_0 ...
[2025-02-12T21:55:07.418Z] ===============================================
[2025-02-12T21:55:07.418Z] renaissance-movie-lens_0 Start Time: Wed Feb 12 21:55:06 2025 Epoch Time (ms): 1739397306326
[2025-02-12T21:55:07.418Z] variation: NoOptions
[2025-02-12T21:55:07.418Z] JVM_OPTIONS:
[2025-02-12T21:55:07.418Z] { \
[2025-02-12T21:55:07.418Z] echo ""; echo "TEST SETUP:"; \
[2025-02-12T21:55:07.418Z] echo "Nothing to be done for setup."; \
[2025-02-12T21:55:07.418Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17393964736666/renaissance-movie-lens_0"; \
[2025-02-12T21:55:07.418Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17393964736666/renaissance-movie-lens_0"; \
[2025-02-12T21:55:07.418Z] echo ""; echo "TESTING:"; \
[2025-02-12T21:55:07.418Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17393964736666/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-12T21:55:07.418Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17393964736666/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-12T21:55:07.418Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-12T21:55:07.418Z] echo "Nothing to be done for teardown."; \
[2025-02-12T21:55:07.418Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17393964736666/TestTargetResult";
[2025-02-12T21:55:07.418Z]
[2025-02-12T21:55:07.418Z] TEST SETUP:
[2025-02-12T21:55:07.418Z] Nothing to be done for setup.
[2025-02-12T21:55:07.418Z]
[2025-02-12T21:55:07.418Z] TESTING:
[2025-02-12T21:55:09.379Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-12T21:55:11.364Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-02-12T21:55:14.453Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-12T21:55:14.453Z] Training: 60056, validation: 20285, test: 19854
[2025-02-12T21:55:14.453Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-12T21:55:14.453Z] GC before operation: completed in 55.831 ms, heap usage 121.679 MB -> 37.165 MB.
[2025-02-12T21:55:19.886Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:22.914Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:25.957Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:27.918Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:29.881Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:30.839Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:32.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:36.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:36.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:55:36.008Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:55:36.008Z] Movies recommended for you:
[2025-02-12T21:55:36.008Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:36.008Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:36.008Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20264.089 ms) ======
[2025-02-12T21:55:36.008Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-12T21:55:36.008Z] GC before operation: completed in 75.992 ms, heap usage 175.559 MB -> 54.416 MB.
[2025-02-12T21:55:37.134Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:40.164Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:42.155Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:45.183Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:46.140Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:47.096Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:49.056Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:51.020Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:51.020Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:55:51.020Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:55:51.020Z] Movies recommended for you:
[2025-02-12T21:55:51.020Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:51.020Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:51.020Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16106.144 ms) ======
[2025-02-12T21:55:51.020Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-12T21:55:51.020Z] GC before operation: completed in 74.615 ms, heap usage 334.007 MB -> 49.882 MB.
[2025-02-12T21:55:52.983Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:56.017Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:57.986Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:59.953Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:00.912Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:02.937Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:03.895Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:04.856Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:04.857Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:56:04.857Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:56:05.821Z] Movies recommended for you:
[2025-02-12T21:56:05.821Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:05.821Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:05.821Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14301.182 ms) ======
[2025-02-12T21:56:05.821Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-12T21:56:05.821Z] GC before operation: completed in 68.193 ms, heap usage 281.222 MB -> 50.195 MB.
[2025-02-12T21:56:06.949Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:09.994Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:11.954Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:13.917Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:15.895Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:17.028Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:17.985Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:18.944Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:19.901Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:56:19.901Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:56:19.901Z] Movies recommended for you:
[2025-02-12T21:56:19.901Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:19.901Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:19.901Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14286.990 ms) ======
[2025-02-12T21:56:19.901Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-12T21:56:19.901Z] GC before operation: completed in 75.308 ms, heap usage 231.845 MB -> 50.386 MB.
[2025-02-12T21:56:21.865Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:23.840Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:26.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:28.854Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:29.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:31.785Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:32.742Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:33.698Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:34.653Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:56:34.653Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:56:34.653Z] Movies recommended for you:
[2025-02-12T21:56:34.653Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:34.653Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:34.653Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14649.629 ms) ======
[2025-02-12T21:56:34.653Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-12T21:56:34.653Z] GC before operation: completed in 65.826 ms, heap usage 187.625 MB -> 50.686 MB.
[2025-02-12T21:56:36.768Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:38.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:40.695Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:42.655Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:44.616Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:45.571Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:46.526Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:47.490Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:48.447Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:56:48.447Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:56:48.447Z] Movies recommended for you:
[2025-02-12T21:56:48.447Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:48.447Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:48.447Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13807.076 ms) ======
[2025-02-12T21:56:48.447Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-12T21:56:48.447Z] GC before operation: completed in 85.463 ms, heap usage 75.017 MB -> 50.458 MB.
[2025-02-12T21:56:50.417Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:52.380Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:54.345Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:56.308Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:57.264Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:58.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:00.315Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:01.280Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:01.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:57:01.280Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:57:01.280Z] Movies recommended for you:
[2025-02-12T21:57:01.280Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:01.280Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:01.280Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13116.134 ms) ======
[2025-02-12T21:57:01.280Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-12T21:57:01.280Z] GC before operation: completed in 96.737 ms, heap usage 88.228 MB -> 50.610 MB.
[2025-02-12T21:57:03.258Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:05.236Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:07.208Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:09.172Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:10.129Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:12.092Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:13.056Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:14.021Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:14.021Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:57:14.021Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:57:14.979Z] Movies recommended for you:
[2025-02-12T21:57:14.979Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:14.979Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:14.979Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12895.081 ms) ======
[2025-02-12T21:57:14.979Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-12T21:57:14.979Z] GC before operation: completed in 67.136 ms, heap usage 75.142 MB -> 50.917 MB.
[2025-02-12T21:57:15.942Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:18.974Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:20.947Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:22.911Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:23.869Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:24.827Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:25.790Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:27.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:27.752Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:57:27.752Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:57:27.752Z] Movies recommended for you:
[2025-02-12T21:57:27.752Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:27.752Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:27.752Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13198.331 ms) ======
[2025-02-12T21:57:27.752Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-12T21:57:27.752Z] GC before operation: completed in 71.270 ms, heap usage 86.179 MB -> 50.767 MB.
[2025-02-12T21:57:29.715Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:31.677Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:34.702Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:35.665Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:36.624Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:37.579Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:38.534Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:40.546Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:40.546Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:57:40.546Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:57:40.546Z] Movies recommended for you:
[2025-02-12T21:57:40.546Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:40.546Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:40.546Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12616.076 ms) ======
[2025-02-12T21:57:40.546Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-12T21:57:40.546Z] GC before operation: completed in 63.850 ms, heap usage 330.345 MB -> 51.049 MB.
[2025-02-12T21:57:42.511Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:44.485Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:46.447Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:48.409Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:49.369Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:50.404Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:52.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:53.325Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:53.325Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:57:53.325Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:57:53.325Z] Movies recommended for you:
[2025-02-12T21:57:53.325Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:53.325Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:53.325Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13015.451 ms) ======
[2025-02-12T21:57:53.325Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-12T21:57:53.325Z] GC before operation: completed in 67.090 ms, heap usage 298.874 MB -> 50.844 MB.
[2025-02-12T21:57:55.287Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:57.251Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:59.214Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:01.182Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:02.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:03.094Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:05.056Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:06.016Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:06.016Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:58:06.016Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:58:06.016Z] Movies recommended for you:
[2025-02-12T21:58:06.016Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:06.016Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:06.016Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12605.594 ms) ======
[2025-02-12T21:58:06.016Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-12T21:58:06.016Z] GC before operation: completed in 60.829 ms, heap usage 338.786 MB -> 51.052 MB.
[2025-02-12T21:58:07.980Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:09.958Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:11.949Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:13.913Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:14.870Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:16.841Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:17.799Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:18.757Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:18.757Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:58:18.757Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:58:18.757Z] Movies recommended for you:
[2025-02-12T21:58:18.757Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:18.757Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:18.757Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12881.255 ms) ======
[2025-02-12T21:58:18.757Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-12T21:58:18.757Z] GC before operation: completed in 71.682 ms, heap usage 196.505 MB -> 51.151 MB.
[2025-02-12T21:58:20.721Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:22.687Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:24.650Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:26.621Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:28.589Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:29.545Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:30.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:31.460Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:31.460Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:58:31.460Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:58:32.419Z] Movies recommended for you:
[2025-02-12T21:58:32.420Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:32.420Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:32.420Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12772.318 ms) ======
[2025-02-12T21:58:32.420Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-12T21:58:32.420Z] GC before operation: completed in 73.141 ms, heap usage 128.707 MB -> 50.730 MB.
[2025-02-12T21:58:35.646Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:35.646Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:37.610Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:39.576Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:40.533Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:41.502Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:43.477Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:44.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:44.437Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:58:44.437Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:58:44.437Z] Movies recommended for you:
[2025-02-12T21:58:44.437Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:44.437Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:44.437Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12473.506 ms) ======
[2025-02-12T21:58:44.437Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-12T21:58:44.437Z] GC before operation: completed in 78.509 ms, heap usage 87.239 MB -> 50.955 MB.
[2025-02-12T21:58:46.402Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:48.485Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:50.451Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:52.413Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:53.372Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:54.328Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:56.292Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:57.249Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:57.249Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:58:57.249Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:58:57.249Z] Movies recommended for you:
[2025-02-12T21:58:57.249Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:57.249Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:57.250Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12965.712 ms) ======
[2025-02-12T21:58:57.250Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-12T21:58:57.250Z] GC before operation: completed in 76.023 ms, heap usage 84.204 MB -> 51.013 MB.
[2025-02-12T21:58:59.214Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:59:01.180Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:59:04.209Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:59:05.164Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:59:07.137Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:59:08.094Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:59:09.053Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:59:10.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:59:10.965Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:59:10.965Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:59:10.965Z] Movies recommended for you:
[2025-02-12T21:59:10.965Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:59:10.965Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:59:10.965Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13001.342 ms) ======
[2025-02-12T21:59:10.965Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-12T21:59:10.965Z] GC before operation: completed in 78.563 ms, heap usage 85.222 MB -> 50.783 MB.
[2025-02-12T21:59:12.937Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:59:14.906Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:59:16.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:59:18.865Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:59:19.821Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:59:20.796Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:59:21.752Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:59:23.720Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:59:23.720Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:59:23.720Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:59:23.720Z] Movies recommended for you:
[2025-02-12T21:59:23.720Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:59:23.720Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:59:23.720Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13028.073 ms) ======
[2025-02-12T21:59:23.720Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-12T21:59:23.720Z] GC before operation: completed in 77.361 ms, heap usage 87.342 MB -> 50.888 MB.
[2025-02-12T21:59:25.691Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:59:27.657Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:59:29.636Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:59:32.662Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:59:32.662Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:59:33.622Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:59:35.590Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:59:36.550Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:59:36.550Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:59:36.550Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:59:36.550Z] Movies recommended for you:
[2025-02-12T21:59:36.550Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:59:36.550Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:59:36.550Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12810.264 ms) ======
[2025-02-12T21:59:36.550Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-12T21:59:36.550Z] GC before operation: completed in 80.716 ms, heap usage 73.148 MB -> 54.392 MB.
[2025-02-12T21:59:38.515Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:59:40.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:59:42.491Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:59:44.458Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:59:45.426Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:59:46.382Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:59:47.339Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:59:48.305Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:59:49.265Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-12T21:59:49.265Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:59:49.265Z] Movies recommended for you:
[2025-02-12T21:59:49.265Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:59:49.265Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:59:49.265Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12380.051 ms) ======
[2025-02-12T21:59:49.266Z] -----------------------------------
[2025-02-12T21:59:49.266Z] renaissance-movie-lens_0_PASSED
[2025-02-12T21:59:49.266Z] -----------------------------------
[2025-02-12T21:59:49.266Z]
[2025-02-12T21:59:49.266Z] TEST TEARDOWN:
[2025-02-12T21:59:49.266Z] Nothing to be done for teardown.
[2025-02-12T21:59:49.266Z] renaissance-movie-lens_0 Finish Time: Wed Feb 12 21:59:49 2025 Epoch Time (ms): 1739397589115