[2025-10-17T15:10:00.679Z] Running test renaissance-movie-lens_0 ... [2025-10-17T15:10:00.679Z] =============================================== [2025-10-17T15:10:00.679Z] renaissance-movie-lens_0 Start Time: Fri Oct 17 15:09:59 2025 Epoch Time (ms): 1760713799563 [2025-10-17T15:10:00.679Z] variation: NoOptions [2025-10-17T15:10:00.679Z] JVM_OPTIONS: [2025-10-17T15:10:00.679Z] { \ [2025-10-17T15:10:00.679Z] echo ""; echo "TEST SETUP:"; \ [2025-10-17T15:10:00.679Z] echo "Nothing to be done for setup."; \ [2025-10-17T15:10:00.679Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17607123476251/renaissance-movie-lens_0"; \ [2025-10-17T15:10:00.679Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17607123476251/renaissance-movie-lens_0"; \ [2025-10-17T15:10:00.679Z] echo ""; echo "TESTING:"; \ [2025-10-17T15:10:00.679Z] "/home/jenkins/workspace/Test_openjdk25_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_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17607123476251/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-10-17T15:10:00.679Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17607123476251/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-10-17T15:10:00.679Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-10-17T15:10:00.679Z] echo "Nothing to be done for teardown."; \ [2025-10-17T15:10:00.679Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17607123476251/TestTargetResult"; [2025-10-17T15:10:00.679Z] [2025-10-17T15:10:00.679Z] TEST SETUP: [2025-10-17T15:10:00.679Z] Nothing to be done for setup. [2025-10-17T15:10:00.679Z] [2025-10-17T15:10:00.679Z] TESTING: [2025-10-17T15:10:00.679Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-10-17T15:10:00.679Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/output_17607123476251/renaissance-movie-lens_0/launcher-150959-9218384751662650702/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-10-17T15:10:00.679Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-10-17T15:10:00.679Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-10-17T15:10:04.841Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-10-17T15:10:13.006Z] 15:10:11.475 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-10-17T15:10:13.961Z] Got 100004 ratings from 671 users on 9066 movies. [2025-10-17T15:10:14.917Z] Training: 60056, validation: 20285, test: 19854 [2025-10-17T15:10:14.917Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-10-17T15:10:14.917Z] GC before operation: completed in 172.305 ms, heap usage 229.278 MB -> 75.643 MB. [2025-10-17T15:10:20.308Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:10:24.483Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:10:27.520Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:10:29.480Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:10:31.446Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:10:33.407Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:10:35.369Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:10:36.324Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:10:37.280Z] 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. [2025-10-17T15:10:37.280Z] The best model improves the baseline by 14.52%. [2025-10-17T15:10:37.280Z] Top recommended movies for user id 72: [2025-10-17T15:10:37.280Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:10:37.280Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:10:37.280Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:10:37.280Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:10:37.280Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:10:37.280Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22242.626 ms) ====== [2025-10-17T15:10:37.280Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-10-17T15:10:37.280Z] GC before operation: completed in 166.914 ms, heap usage 457.535 MB -> 96.611 MB. [2025-10-17T15:10:40.307Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:10:42.266Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:10:45.291Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:10:48.318Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:10:49.272Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:10:51.413Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:10:52.412Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:10:54.372Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:10:54.372Z] 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. [2025-10-17T15:10:54.372Z] The best model improves the baseline by 14.52%. [2025-10-17T15:10:54.372Z] Top recommended movies for user id 72: [2025-10-17T15:10:54.372Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:10:54.372Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:10:54.372Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:10:54.372Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:10:54.372Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:10:54.372Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17271.803 ms) ====== [2025-10-17T15:10:54.372Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-10-17T15:10:54.372Z] GC before operation: completed in 135.648 ms, heap usage 450.320 MB -> 88.772 MB. [2025-10-17T15:10:58.128Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:10:59.083Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:11:02.112Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:11:04.166Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:11:06.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:11:07.080Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:11:09.050Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:11:10.006Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:11:10.960Z] 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. [2025-10-17T15:11:10.960Z] The best model improves the baseline by 14.52%. [2025-10-17T15:11:10.960Z] Top recommended movies for user id 72: [2025-10-17T15:11:10.960Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:11:10.960Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:11:10.960Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:11:10.960Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:11:10.960Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:11:10.960Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16071.450 ms) ====== [2025-10-17T15:11:10.960Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-10-17T15:11:10.960Z] GC before operation: completed in 137.143 ms, heap usage 446.122 MB -> 89.557 MB. [2025-10-17T15:11:13.985Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:11:15.943Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:11:17.906Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:11:20.933Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:11:22.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:11:23.848Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:11:25.811Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:11:26.766Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:11:26.766Z] 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. [2025-10-17T15:11:26.766Z] The best model improves the baseline by 14.52%. [2025-10-17T15:11:27.721Z] Top recommended movies for user id 72: [2025-10-17T15:11:27.721Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:11:27.721Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:11:27.721Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:11:27.721Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:11:27.721Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:11:27.721Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16445.925 ms) ====== [2025-10-17T15:11:27.721Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-10-17T15:11:27.721Z] GC before operation: completed in 141.986 ms, heap usage 371.750 MB -> 89.768 MB. [2025-10-17T15:11:29.680Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:11:31.643Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:11:34.688Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:11:36.652Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:11:38.613Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:11:39.569Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:11:40.524Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:11:42.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:11:42.486Z] 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. [2025-10-17T15:11:42.486Z] The best model improves the baseline by 14.52%. [2025-10-17T15:11:42.486Z] Top recommended movies for user id 72: [2025-10-17T15:11:42.486Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:11:42.486Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:11:42.486Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:11:42.486Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:11:42.486Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:11:42.486Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15158.659 ms) ====== [2025-10-17T15:11:42.486Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-10-17T15:11:42.486Z] GC before operation: completed in 128.569 ms, heap usage 234.432 MB -> 89.401 MB. [2025-10-17T15:11:45.514Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:11:47.490Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:11:49.454Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:11:51.413Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:11:53.376Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:11:54.333Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:11:56.302Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:11:57.257Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:11:57.257Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-10-17T15:11:57.257Z] The best model improves the baseline by 14.52%. [2025-10-17T15:11:57.257Z] Top recommended movies for user id 72: [2025-10-17T15:11:57.257Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:11:57.257Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:11:57.257Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:11:57.257Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:11:57.257Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:11:57.257Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14875.591 ms) ====== [2025-10-17T15:11:57.257Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-10-17T15:11:58.212Z] GC before operation: completed in 161.566 ms, heap usage 256.531 MB -> 89.827 MB. [2025-10-17T15:11:59.850Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:12:02.879Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:12:04.840Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:12:06.802Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:12:08.762Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:12:09.717Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:12:11.678Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:12:12.636Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:12:12.636Z] 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. [2025-10-17T15:12:13.597Z] The best model improves the baseline by 14.52%. [2025-10-17T15:12:13.597Z] Top recommended movies for user id 72: [2025-10-17T15:12:13.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:12:13.597Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:12:13.597Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:12:13.597Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:12:13.597Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:12:13.598Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15412.657 ms) ====== [2025-10-17T15:12:13.598Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-10-17T15:12:13.598Z] GC before operation: completed in 159.890 ms, heap usage 375.201 MB -> 89.967 MB. [2025-10-17T15:12:15.560Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:12:18.588Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:12:20.548Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:12:22.511Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:12:24.472Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:12:25.428Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:12:27.387Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:12:28.353Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:12:28.354Z] 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. [2025-10-17T15:12:28.354Z] The best model improves the baseline by 14.52%. [2025-10-17T15:12:29.315Z] Top recommended movies for user id 72: [2025-10-17T15:12:29.315Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:12:29.315Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:12:29.315Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:12:29.315Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:12:29.315Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:12:29.315Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15433.961 ms) ====== [2025-10-17T15:12:29.315Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-10-17T15:12:29.315Z] GC before operation: completed in 159.613 ms, heap usage 552.601 MB -> 93.617 MB. [2025-10-17T15:12:31.274Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:12:33.249Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:12:36.284Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:12:38.252Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:12:39.206Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:12:40.164Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:12:42.130Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:12:43.088Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:12:44.043Z] 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. [2025-10-17T15:12:44.043Z] The best model improves the baseline by 14.52%. [2025-10-17T15:12:44.043Z] Top recommended movies for user id 72: [2025-10-17T15:12:44.043Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:12:44.043Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:12:44.043Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:12:44.043Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:12:44.043Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:12:44.043Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14841.706 ms) ====== [2025-10-17T15:12:44.043Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-10-17T15:12:44.043Z] GC before operation: completed in 138.630 ms, heap usage 372.807 MB -> 90.000 MB. [2025-10-17T15:12:46.011Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:12:47.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:12:50.994Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:12:52.967Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:12:53.931Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:12:56.064Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:12:57.027Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:12:57.989Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:13:15.747Z] 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. [2025-10-17T15:13:15.747Z] The best model improves the baseline by 14.52%. [2025-10-17T15:13:15.747Z] Top recommended movies for user id 72: [2025-10-17T15:13:15.747Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:13:15.747Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:13:15.747Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:13:15.747Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:13:15.747Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:13:15.747Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14792.597 ms) ====== [2025-10-17T15:13:15.747Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-10-17T15:13:15.747Z] GC before operation: completed in 147.894 ms, heap usage 369.013 MB -> 90.240 MB. [2025-10-17T15:13:15.747Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:13:15.747Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:13:15.747Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:13:19.129Z] test-osuosl-centos74-ppc64le-2 seems to be removed or offline (java.lang.InterruptedException); will wait for 5 min 0 sec for it to come back online [2025-10-17T15:13:19.381Z] test-osuosl-centos74-ppc64le-2 is back online [2025-10-17T15:13:23.987Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:13:24.469Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:13:24.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:13:24.469Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:13:24.469Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:13:24.469Z] 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. [2025-10-17T15:13:24.469Z] The best model improves the baseline by 14.52%. [2025-10-17T15:13:24.469Z] Top recommended movies for user id 72: [2025-10-17T15:13:24.469Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:13:24.469Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:13:24.469Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:13:24.469Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:13:24.469Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:13:24.469Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15144.862 ms) ====== [2025-10-17T15:13:24.469Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-10-17T15:13:24.469Z] GC before operation: completed in 172.321 ms, heap usage 292.364 MB -> 89.924 MB. [2025-10-17T15:13:24.469Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:13:24.469Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:13:24.469Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:13:24.469Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:13:25.426Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:13:26.381Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:13:27.347Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:13:29.326Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:13:29.326Z] 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. [2025-10-17T15:13:29.326Z] The best model improves the baseline by 14.52%. [2025-10-17T15:13:29.326Z] Top recommended movies for user id 72: [2025-10-17T15:13:29.326Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:13:29.326Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:13:29.326Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:13:29.326Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:13:29.326Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:13:29.326Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15445.407 ms) ====== [2025-10-17T15:13:29.326Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-10-17T15:13:30.281Z] GC before operation: completed in 170.073 ms, heap usage 303.625 MB -> 90.109 MB. [2025-10-17T15:13:32.242Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:13:34.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:13:37.245Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:13:39.206Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:13:41.166Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:13:42.122Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:13:44.082Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:13:45.038Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:13:45.038Z] 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. [2025-10-17T15:13:45.038Z] The best model improves the baseline by 14.52%. [2025-10-17T15:13:45.993Z] Top recommended movies for user id 72: [2025-10-17T15:13:45.993Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:13:45.993Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:13:45.993Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:13:45.993Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:13:45.993Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:13:45.993Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15777.052 ms) ====== [2025-10-17T15:13:45.993Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-10-17T15:13:45.993Z] GC before operation: completed in 128.149 ms, heap usage 162.741 MB -> 90.035 MB. [2025-10-17T15:13:47.954Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:13:50.978Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:13:52.939Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:13:54.898Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:13:56.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:13:57.844Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:13:59.805Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:14:00.784Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:14:00.784Z] 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. [2025-10-17T15:14:00.784Z] The best model improves the baseline by 14.52%. [2025-10-17T15:14:00.784Z] Top recommended movies for user id 72: [2025-10-17T15:14:00.784Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:14:00.784Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:14:00.784Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:14:00.784Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:14:00.784Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:14:00.784Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15263.814 ms) ====== [2025-10-17T15:14:00.784Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-10-17T15:14:00.784Z] GC before operation: completed in 135.655 ms, heap usage 254.971 MB -> 89.969 MB. [2025-10-17T15:14:03.811Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:14:05.770Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:14:07.814Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:14:09.780Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:14:11.741Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:14:12.700Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:14:14.661Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:14:15.620Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:14:16.575Z] 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. [2025-10-17T15:14:16.575Z] The best model improves the baseline by 14.52%. [2025-10-17T15:14:16.575Z] Top recommended movies for user id 72: [2025-10-17T15:14:16.575Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:14:16.575Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:14:16.575Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:14:16.575Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:14:16.575Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:14:16.575Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15123.436 ms) ====== [2025-10-17T15:14:16.575Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-10-17T15:14:16.575Z] GC before operation: completed in 171.329 ms, heap usage 292.427 MB -> 90.256 MB. [2025-10-17T15:14:18.539Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:14:21.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:14:24.233Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:14:25.203Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:14:27.164Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:14:28.132Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:14:30.093Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:14:31.048Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:14:32.002Z] 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. [2025-10-17T15:14:32.002Z] The best model improves the baseline by 14.52%. [2025-10-17T15:14:32.002Z] Top recommended movies for user id 72: [2025-10-17T15:14:32.002Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:14:32.002Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:14:32.002Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:14:32.002Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:14:32.002Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:14:32.002Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15291.753 ms) ====== [2025-10-17T15:14:32.002Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-10-17T15:14:32.002Z] GC before operation: completed in 135.019 ms, heap usage 371.334 MB -> 90.194 MB. [2025-10-17T15:14:33.965Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:14:35.926Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:14:38.950Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:14:40.913Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:14:41.870Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:14:43.849Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:14:44.803Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:14:46.778Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:14:46.779Z] 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. [2025-10-17T15:14:46.779Z] The best model improves the baseline by 14.52%. [2025-10-17T15:14:46.779Z] Top recommended movies for user id 72: [2025-10-17T15:14:46.779Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:14:46.779Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:14:46.779Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:14:46.779Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:14:46.779Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:14:46.779Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15028.646 ms) ====== [2025-10-17T15:14:46.779Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-10-17T15:14:46.779Z] GC before operation: completed in 136.653 ms, heap usage 131.849 MB -> 90.779 MB. [2025-10-17T15:14:49.812Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:14:51.770Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:14:53.730Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:14:55.885Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:14:57.851Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:14:58.805Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:15:00.767Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:15:01.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:15:01.724Z] 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. [2025-10-17T15:15:01.724Z] The best model improves the baseline by 14.52%. [2025-10-17T15:15:01.724Z] Top recommended movies for user id 72: [2025-10-17T15:15:01.724Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:15:01.724Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:15:01.724Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:15:01.724Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:15:01.724Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:15:01.724Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14869.433 ms) ====== [2025-10-17T15:15:01.724Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-10-17T15:15:01.724Z] GC before operation: completed in 136.230 ms, heap usage 625.419 MB -> 93.736 MB. [2025-10-17T15:15:04.761Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:15:06.721Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:15:08.680Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:15:10.641Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:15:11.596Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:15:13.554Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:15:14.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:15:15.464Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:15:16.421Z] 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. [2025-10-17T15:15:16.421Z] The best model improves the baseline by 14.52%. [2025-10-17T15:15:16.421Z] Top recommended movies for user id 72: [2025-10-17T15:15:16.421Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:15:16.421Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:15:16.421Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:15:16.421Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:15:16.421Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:15:16.421Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14204.650 ms) ====== [2025-10-17T15:15:16.421Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-10-17T15:15:16.421Z] GC before operation: completed in 121.402 ms, heap usage 439.939 MB -> 90.376 MB. [2025-10-17T15:15:18.384Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-17T15:15:20.343Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-17T15:15:23.370Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-17T15:15:25.053Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-17T15:15:26.009Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-17T15:15:27.970Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-17T15:15:28.924Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-17T15:15:29.880Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-17T15:15:30.834Z] 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. [2025-10-17T15:15:30.834Z] The best model improves the baseline by 14.52%. [2025-10-17T15:15:30.834Z] Top recommended movies for user id 72: [2025-10-17T15:15:30.834Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-17T15:15:30.834Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-17T15:15:30.834Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-17T15:15:30.834Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-17T15:15:30.834Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-17T15:15:30.834Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14422.948 ms) ====== [2025-10-17T15:15:30.834Z] ----------------------------------- [2025-10-17T15:15:30.834Z] renaissance-movie-lens_0_PASSED [2025-10-17T15:15:30.834Z] ----------------------------------- [2025-10-17T15:15:31.791Z] [2025-10-17T15:15:31.791Z] TEST TEARDOWN: [2025-10-17T15:15:31.791Z] Nothing to be done for teardown. [2025-10-17T15:15:31.791Z] renaissance-movie-lens_0 Finish Time: Fri Oct 17 15:15:30 2025 Epoch Time (ms): 1760714130758