[2025-12-27T13:39:40.304Z] Running test renaissance-movie-lens_0 ... [2025-12-27T13:39:40.304Z] =============================================== [2025-12-27T13:39:40.304Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 13:39:39 2025 Epoch Time (ms): 1766842779480 [2025-12-27T13:39:40.304Z] variation: NoOptions [2025-12-27T13:39:40.304Z] JVM_OPTIONS: [2025-12-27T13:39:40.304Z] { \ [2025-12-27T13:39:40.304Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T13:39:40.304Z] echo "Nothing to be done for setup."; \ [2025-12-27T13:39:40.304Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668403328741/renaissance-movie-lens_0"; \ [2025-12-27T13:39:40.304Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668403328741/renaissance-movie-lens_0"; \ [2025-12-27T13:39:40.305Z] echo ""; echo "TESTING:"; \ [2025-12-27T13:39:40.305Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_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_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668403328741/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T13:39:40.305Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668403328741/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T13:39:40.305Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T13:39:40.305Z] echo "Nothing to be done for teardown."; \ [2025-12-27T13:39:40.305Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668403328741/TestTargetResult"; [2025-12-27T13:39:40.305Z] [2025-12-27T13:39:40.305Z] TEST SETUP: [2025-12-27T13:39:40.305Z] Nothing to be done for setup. [2025-12-27T13:39:40.305Z] [2025-12-27T13:39:40.305Z] TESTING: [2025-12-27T13:39:41.282Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T13:39:41.282Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/output_17668403328741/renaissance-movie-lens_0/launcher-133939-7386818529352308632/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T13:39:41.282Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T13:39:41.282Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T13:39:53.039Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-27T13:40:11.842Z] 13:40:10.489 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-27T13:40:14.986Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T13:40:15.960Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T13:40:15.960Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T13:40:15.960Z] GC before operation: completed in 196.518 ms, heap usage 282.723 MB -> 76.000 MB. [2025-12-27T13:40:32.236Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:40:40.658Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:40:49.196Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:40:59.543Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:41:04.378Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:41:10.276Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:41:14.928Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:41:19.226Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:41:20.217Z] 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. [2025-12-27T13:41:20.217Z] The best model improves the baseline by 14.52%. [2025-12-27T13:41:21.223Z] Top recommended movies for user id 72: [2025-12-27T13:41:21.223Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:41:21.223Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:41:21.223Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:41:21.223Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:41:21.223Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:41:21.223Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (64732.139 ms) ====== [2025-12-27T13:41:21.223Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T13:41:21.223Z] GC before operation: completed in 452.916 ms, heap usage 137.851 MB -> 86.345 MB. [2025-12-27T13:41:29.723Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:41:36.595Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:41:43.476Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:41:50.347Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:41:54.612Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:41:58.881Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:42:01.978Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:42:06.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:42:07.229Z] 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. [2025-12-27T13:42:07.229Z] The best model improves the baseline by 14.52%. [2025-12-27T13:42:07.229Z] Top recommended movies for user id 72: [2025-12-27T13:42:07.229Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:42:07.229Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:42:07.229Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:42:07.229Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:42:07.229Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:42:07.229Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45946.933 ms) ====== [2025-12-27T13:42:07.229Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T13:42:07.229Z] GC before operation: completed in 258.645 ms, heap usage 707.895 MB -> 92.515 MB. [2025-12-27T13:42:14.084Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:42:20.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:42:26.487Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:42:32.794Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:42:35.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:42:38.979Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:42:43.256Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:42:46.362Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:42:47.339Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T13:42:47.339Z] The best model improves the baseline by 14.52%. [2025-12-27T13:42:47.339Z] Top recommended movies for user id 72: [2025-12-27T13:42:47.339Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:42:47.339Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:42:47.339Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:42:47.339Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:42:47.339Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:42:47.339Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (40011.142 ms) ====== [2025-12-27T13:42:47.339Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T13:42:48.320Z] GC before operation: completed in 291.635 ms, heap usage 467.711 MB -> 89.804 MB. [2025-12-27T13:42:53.819Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:42:59.326Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:43:05.010Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:43:10.513Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:43:13.592Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:43:17.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:43:20.931Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:43:24.027Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:43:25.024Z] 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. [2025-12-27T13:43:25.024Z] The best model improves the baseline by 14.52%. [2025-12-27T13:43:25.024Z] Top recommended movies for user id 72: [2025-12-27T13:43:25.024Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:43:25.024Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:43:25.024Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:43:25.024Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:43:25.024Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:43:25.024Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (36967.308 ms) ====== [2025-12-27T13:43:25.024Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T13:43:25.024Z] GC before operation: completed in 245.344 ms, heap usage 184.677 MB -> 89.643 MB. [2025-12-27T13:43:30.681Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:43:37.551Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:43:43.065Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:43:48.061Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:43:51.156Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:43:54.248Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:43:57.344Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:44:00.661Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:44:00.661Z] 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. [2025-12-27T13:44:00.661Z] The best model improves the baseline by 14.52%. [2025-12-27T13:44:01.633Z] Top recommended movies for user id 72: [2025-12-27T13:44:01.633Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:44:01.633Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:44:01.633Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:44:01.633Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:44:01.633Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:44:01.633Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (36044.507 ms) ====== [2025-12-27T13:44:01.633Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T13:44:01.633Z] GC before operation: completed in 302.681 ms, heap usage 487.386 MB -> 89.994 MB. [2025-12-27T13:44:08.479Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:44:13.974Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:44:18.236Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:44:23.724Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:44:25.734Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:44:28.828Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:44:31.916Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:44:36.178Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:44:36.178Z] 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. [2025-12-27T13:44:36.178Z] The best model improves the baseline by 14.52%. [2025-12-27T13:44:36.178Z] Top recommended movies for user id 72: [2025-12-27T13:44:36.178Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:44:36.178Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:44:36.178Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:44:36.178Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:44:36.178Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:44:36.178Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (35038.368 ms) ====== [2025-12-27T13:44:36.178Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T13:44:37.173Z] GC before operation: completed in 337.645 ms, heap usage 533.136 MB -> 93.638 MB. [2025-12-27T13:44:42.657Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:44:46.906Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:44:52.395Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:44:57.886Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:45:01.023Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:45:04.129Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:45:08.405Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:45:11.512Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:45:12.497Z] 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. [2025-12-27T13:45:12.497Z] The best model improves the baseline by 14.52%. [2025-12-27T13:45:12.497Z] Top recommended movies for user id 72: [2025-12-27T13:45:12.497Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:45:12.497Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:45:12.497Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:45:12.497Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:45:12.497Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:45:12.497Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (35531.851 ms) ====== [2025-12-27T13:45:12.497Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T13:45:12.497Z] GC before operation: completed in 273.801 ms, heap usage 541.950 MB -> 93.566 MB. [2025-12-27T13:45:19.353Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:45:24.872Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:45:30.392Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:45:35.904Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:45:39.015Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:45:41.947Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:45:45.028Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:45:48.137Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:45:48.137Z] 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. [2025-12-27T13:45:48.137Z] The best model improves the baseline by 14.52%. [2025-12-27T13:45:48.137Z] Top recommended movies for user id 72: [2025-12-27T13:45:48.137Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:45:48.137Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:45:48.137Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:45:48.137Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:45:48.137Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:45:48.137Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (35749.456 ms) ====== [2025-12-27T13:45:48.137Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T13:45:49.118Z] GC before operation: completed in 328.965 ms, heap usage 528.147 MB -> 95.521 MB. [2025-12-27T13:45:54.671Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:45:58.934Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:46:05.795Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:46:10.056Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:46:14.399Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:46:17.478Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:46:20.575Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:46:23.645Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:46:24.631Z] 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. [2025-12-27T13:46:24.631Z] The best model improves the baseline by 14.52%. [2025-12-27T13:46:24.631Z] Top recommended movies for user id 72: [2025-12-27T13:46:24.631Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:46:24.631Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:46:24.631Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:46:24.631Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:46:24.631Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:46:24.631Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (35896.914 ms) ====== [2025-12-27T13:46:24.631Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T13:46:24.631Z] GC before operation: completed in 329.900 ms, heap usage 131.221 MB -> 91.312 MB. [2025-12-27T13:46:30.116Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:46:35.751Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:46:41.498Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:46:45.752Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:46:50.020Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:46:53.208Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:46:56.332Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:46:59.460Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:47:01.322Z] 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. [2025-12-27T13:47:01.322Z] The best model improves the baseline by 14.52%. [2025-12-27T13:47:01.322Z] Top recommended movies for user id 72: [2025-12-27T13:47:01.322Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:47:01.322Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:47:01.322Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:47:01.322Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:47:01.322Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:47:01.322Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (35540.145 ms) ====== [2025-12-27T13:47:01.322Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T13:47:01.322Z] GC before operation: completed in 288.430 ms, heap usage 359.916 MB -> 90.333 MB. [2025-12-27T13:47:05.577Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:47:09.820Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:47:14.263Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:47:18.495Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:47:21.580Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:47:23.583Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:47:26.860Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:47:30.016Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:47:30.016Z] 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. [2025-12-27T13:47:30.016Z] The best model improves the baseline by 14.52%. [2025-12-27T13:47:30.997Z] Top recommended movies for user id 72: [2025-12-27T13:47:30.997Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:47:30.997Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:47:30.997Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:47:30.997Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:47:30.997Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:47:30.997Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (29810.125 ms) ====== [2025-12-27T13:47:30.997Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T13:47:30.997Z] GC before operation: completed in 241.601 ms, heap usage 242.663 MB -> 89.895 MB. [2025-12-27T13:47:35.245Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:47:39.482Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:47:42.565Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:47:46.809Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:47:49.892Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:47:52.996Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:47:56.119Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:47:59.230Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:47:59.230Z] 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. [2025-12-27T13:47:59.230Z] The best model improves the baseline by 14.52%. [2025-12-27T13:48:00.300Z] Top recommended movies for user id 72: [2025-12-27T13:48:00.300Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:48:00.300Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:48:00.300Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:48:00.300Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:48:00.300Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:48:00.300Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (28876.722 ms) ====== [2025-12-27T13:48:00.300Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T13:48:00.300Z] GC before operation: completed in 260.322 ms, heap usage 422.028 MB -> 90.489 MB. [2025-12-27T13:48:04.644Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:48:10.421Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:48:14.738Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:48:19.183Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:48:22.264Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:48:25.429Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:48:28.522Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:48:32.908Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:48:32.908Z] 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. [2025-12-27T13:48:33.897Z] The best model improves the baseline by 14.52%. [2025-12-27T13:48:33.897Z] Top recommended movies for user id 72: [2025-12-27T13:48:33.897Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:48:33.897Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:48:33.897Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:48:33.897Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:48:33.897Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:48:33.897Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (33716.578 ms) ====== [2025-12-27T13:48:33.897Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T13:48:33.897Z] GC before operation: completed in 302.782 ms, heap usage 136.444 MB -> 90.079 MB. [2025-12-27T13:48:40.957Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:48:45.204Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:48:50.694Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:48:55.383Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:48:58.607Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:49:03.553Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:49:06.646Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:49:09.824Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:49:10.806Z] 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. [2025-12-27T13:49:10.806Z] The best model improves the baseline by 14.52%. [2025-12-27T13:49:10.806Z] Top recommended movies for user id 72: [2025-12-27T13:49:10.806Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:49:10.806Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:49:10.806Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:49:10.806Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:49:10.806Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:49:10.806Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (36799.839 ms) ====== [2025-12-27T13:49:10.806Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T13:49:10.806Z] GC before operation: completed in 314.890 ms, heap usage 165.568 MB -> 89.976 MB. [2025-12-27T13:49:16.415Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:49:22.260Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:49:27.741Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:49:32.218Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:49:35.397Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:49:38.573Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:49:41.770Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:49:44.861Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:49:45.830Z] 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. [2025-12-27T13:49:45.830Z] The best model improves the baseline by 14.52%. [2025-12-27T13:49:45.830Z] Top recommended movies for user id 72: [2025-12-27T13:49:45.830Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:49:45.830Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:49:45.830Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:49:45.830Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:49:45.830Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:49:45.830Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (34617.317 ms) ====== [2025-12-27T13:49:45.830Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T13:49:45.830Z] GC before operation: completed in 208.643 ms, heap usage 144.935 MB -> 90.971 MB. [2025-12-27T13:49:51.476Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:49:57.085Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:50:02.787Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:50:09.859Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:50:12.980Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:50:16.084Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:50:20.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:50:23.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:50:24.470Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T13:50:24.470Z] The best model improves the baseline by 14.52%. [2025-12-27T13:50:24.470Z] Top recommended movies for user id 72: [2025-12-27T13:50:24.470Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:50:24.470Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:50:24.470Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:50:24.470Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:50:24.470Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:50:24.470Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38730.924 ms) ====== [2025-12-27T13:50:24.470Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T13:50:25.453Z] GC before operation: completed in 308.069 ms, heap usage 171.189 MB -> 90.139 MB. [2025-12-27T13:50:30.957Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:50:35.953Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:50:41.481Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:50:45.928Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:50:49.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:50:51.158Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:50:54.265Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:50:57.554Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:50:57.554Z] 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. [2025-12-27T13:50:57.554Z] The best model improves the baseline by 14.52%. [2025-12-27T13:50:58.535Z] Top recommended movies for user id 72: [2025-12-27T13:50:58.535Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:50:58.535Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:50:58.535Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:50:58.535Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:50:58.535Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:50:58.535Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (33037.360 ms) ====== [2025-12-27T13:50:58.535Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T13:50:58.535Z] GC before operation: completed in 262.991 ms, heap usage 152.718 MB -> 90.307 MB. [2025-12-27T13:51:02.919Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:51:07.247Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:51:10.338Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:51:14.737Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:51:16.780Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:51:18.796Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:51:21.894Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:51:23.895Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:51:23.895Z] 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. [2025-12-27T13:51:23.895Z] The best model improves the baseline by 14.52%. [2025-12-27T13:51:24.876Z] Top recommended movies for user id 72: [2025-12-27T13:51:24.876Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:51:24.876Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:51:24.876Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:51:24.876Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:51:24.876Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:51:24.876Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26192.802 ms) ====== [2025-12-27T13:51:24.876Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T13:51:24.876Z] GC before operation: completed in 282.138 ms, heap usage 191.790 MB -> 90.074 MB. [2025-12-27T13:51:30.448Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:51:33.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:51:37.903Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:51:42.144Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:51:44.141Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:51:46.135Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:51:49.210Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:51:51.204Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:51:51.204Z] 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. [2025-12-27T13:51:51.204Z] The best model improves the baseline by 14.52%. [2025-12-27T13:51:51.204Z] Top recommended movies for user id 72: [2025-12-27T13:51:51.204Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:51:51.204Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:51:51.204Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:51:51.204Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:51:51.204Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:51:51.204Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (26696.447 ms) ====== [2025-12-27T13:51:51.204Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T13:51:52.174Z] GC before operation: completed in 305.155 ms, heap usage 256.868 MB -> 90.243 MB. [2025-12-27T13:51:55.257Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:51:59.492Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:52:03.793Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:52:08.017Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:52:10.010Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:52:12.011Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:52:15.093Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:52:17.104Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:52:17.104Z] 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. [2025-12-27T13:52:17.104Z] The best model improves the baseline by 14.52%. [2025-12-27T13:52:18.829Z] Top recommended movies for user id 72: [2025-12-27T13:52:18.829Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:52:18.829Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:52:18.829Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:52:18.829Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:52:18.829Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:52:18.829Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (25824.879 ms) ====== [2025-12-27T13:52:19.809Z] ----------------------------------- [2025-12-27T13:52:19.809Z] renaissance-movie-lens_0_PASSED [2025-12-27T13:52:19.809Z] ----------------------------------- [2025-12-27T13:52:19.809Z] [2025-12-27T13:52:19.809Z] TEST TEARDOWN: [2025-12-27T13:52:19.809Z] Nothing to be done for teardown. [2025-12-27T13:52:19.809Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 13:52:19 2025 Epoch Time (ms): 1766843539047