[2025-12-16T09:52:18.583Z] Running test renaissance-movie-lens_0 ... [2025-12-16T09:52:18.583Z] =============================================== [2025-12-16T09:52:18.583Z] renaissance-movie-lens_0 Start Time: Tue Dec 16 09:52:18 2025 Epoch Time (ms): 1765878738224 [2025-12-16T09:52:18.583Z] variation: NoOptions [2025-12-16T09:52:18.583Z] JVM_OPTIONS: [2025-12-16T09:52:18.583Z] { \ [2025-12-16T09:52:18.583Z] echo ""; echo "TEST SETUP:"; \ [2025-12-16T09:52:18.583Z] echo "Nothing to be done for setup."; \ [2025-12-16T09:52:18.583Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17658769299527/renaissance-movie-lens_0"; \ [2025-12-16T09:52:18.583Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17658769299527/renaissance-movie-lens_0"; \ [2025-12-16T09:52:18.583Z] echo ""; echo "TESTING:"; \ [2025-12-16T09:52:18.583Z] "/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_17658769299527/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-16T09:52:18.584Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17658769299527/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-16T09:52:18.584Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-16T09:52:18.584Z] echo "Nothing to be done for teardown."; \ [2025-12-16T09:52:18.584Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17658769299527/TestTargetResult"; [2025-12-16T09:52:18.584Z] [2025-12-16T09:52:18.584Z] TEST SETUP: [2025-12-16T09:52:18.584Z] Nothing to be done for setup. [2025-12-16T09:52:18.584Z] [2025-12-16T09:52:18.584Z] TESTING: [2025-12-16T09:52:19.371Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-16T09:52:19.371Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/output_17658769299527/renaissance-movie-lens_0/launcher-095218-13776619621394467225/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-16T09:52:19.371Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-16T09:52:19.371Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-16T09:52:26.219Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-16T09:52:36.718Z] 09:52:35.710 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-16T09:52:38.901Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-16T09:52:39.708Z] Training: 60056, validation: 20285, test: 19854 [2025-12-16T09:52:39.708Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-16T09:52:40.106Z] GC before operation: completed in 157.854 ms, heap usage 203.537 MB -> 75.772 MB. [2025-12-16T09:52:48.077Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:52:53.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:52:57.508Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:53:00.827Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:53:03.380Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:53:05.185Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:53:07.634Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:53:10.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:53:10.102Z] 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. [2025-12-16T09:53:10.102Z] The best model improves the baseline by 14.52%. [2025-12-16T09:53:10.479Z] Top recommended movies for user id 72: [2025-12-16T09:53:10.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:53:10.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:53:10.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:53:10.479Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:53:10.479Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:53:10.479Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (30639.565 ms) ====== [2025-12-16T09:53:10.479Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-16T09:53:10.858Z] GC before operation: completed in 161.878 ms, heap usage 603.074 MB -> 92.258 MB. [2025-12-16T09:53:14.964Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:53:17.609Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:53:20.947Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:53:24.218Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:53:26.712Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:53:28.667Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:53:31.163Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:53:32.981Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:53:33.344Z] 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. [2025-12-16T09:53:33.344Z] The best model improves the baseline by 14.52%. [2025-12-16T09:53:33.722Z] Top recommended movies for user id 72: [2025-12-16T09:53:33.722Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:53:33.722Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:53:33.722Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:53:33.722Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:53:33.722Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:53:33.722Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22882.016 ms) ====== [2025-12-16T09:53:33.722Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-16T09:53:33.722Z] GC before operation: completed in 151.169 ms, heap usage 537.083 MB -> 91.989 MB. [2025-12-16T09:53:36.946Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:53:41.073Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:53:44.449Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:53:47.058Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:53:48.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:53:51.455Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:53:53.379Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:53:55.229Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:53:55.597Z] 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. [2025-12-16T09:53:55.597Z] The best model improves the baseline by 14.52%. [2025-12-16T09:53:55.996Z] Top recommended movies for user id 72: [2025-12-16T09:53:55.996Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:53:55.996Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:53:55.996Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:53:55.996Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:53:55.996Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:53:55.996Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22040.964 ms) ====== [2025-12-16T09:53:55.996Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-16T09:53:55.996Z] GC before operation: completed in 150.562 ms, heap usage 297.040 MB -> 89.140 MB. [2025-12-16T09:53:59.213Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:54:02.409Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:54:04.938Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:54:08.145Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:54:10.655Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:54:12.502Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:54:14.972Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:54:16.797Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:54:16.797Z] 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. [2025-12-16T09:54:16.797Z] The best model improves the baseline by 14.52%. [2025-12-16T09:54:17.177Z] Top recommended movies for user id 72: [2025-12-16T09:54:17.177Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:54:17.177Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:54:17.177Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:54:17.177Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:54:17.177Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:54:17.177Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21085.070 ms) ====== [2025-12-16T09:54:17.177Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-16T09:54:17.177Z] GC before operation: completed in 156.143 ms, heap usage 383.900 MB -> 89.463 MB. [2025-12-16T09:54:20.407Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:54:23.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:54:26.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:54:30.110Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:54:31.997Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:54:33.821Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:54:35.706Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:54:38.242Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:54:38.242Z] 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. [2025-12-16T09:54:38.242Z] The best model improves the baseline by 14.52%. [2025-12-16T09:54:38.630Z] Top recommended movies for user id 72: [2025-12-16T09:54:38.630Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:54:38.630Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:54:38.630Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:54:38.630Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:54:38.630Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:54:38.630Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21284.983 ms) ====== [2025-12-16T09:54:38.630Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-16T09:54:38.630Z] GC before operation: completed in 148.953 ms, heap usage 121.083 MB -> 91.865 MB. [2025-12-16T09:54:41.966Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:54:45.172Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:54:48.418Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:54:51.623Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:54:53.459Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:54:55.287Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:54:57.149Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:54:58.991Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:54:59.420Z] 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. [2025-12-16T09:54:59.420Z] The best model improves the baseline by 14.52%. [2025-12-16T09:54:59.787Z] Top recommended movies for user id 72: [2025-12-16T09:54:59.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:54:59.787Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:54:59.787Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:54:59.787Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:54:59.787Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:54:59.787Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20993.672 ms) ====== [2025-12-16T09:54:59.787Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-16T09:54:59.787Z] GC before operation: completed in 150.063 ms, heap usage 448.964 MB -> 89.927 MB. [2025-12-16T09:55:02.976Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:55:06.211Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:55:09.459Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:55:11.921Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:55:13.751Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:55:15.579Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:55:17.457Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:55:19.963Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:55:19.963Z] 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. [2025-12-16T09:55:19.963Z] The best model improves the baseline by 14.52%. [2025-12-16T09:55:19.963Z] Top recommended movies for user id 72: [2025-12-16T09:55:19.963Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:55:19.963Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:55:19.963Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:55:19.963Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:55:19.963Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:55:19.963Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20245.348 ms) ====== [2025-12-16T09:55:19.963Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-16T09:55:20.334Z] GC before operation: completed in 157.019 ms, heap usage 373.685 MB -> 89.727 MB. [2025-12-16T09:55:23.559Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:55:26.040Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:55:29.417Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:55:32.617Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:55:34.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:55:35.837Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:55:37.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:55:39.518Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:55:39.886Z] 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. [2025-12-16T09:55:39.886Z] The best model improves the baseline by 14.52%. [2025-12-16T09:55:40.264Z] Top recommended movies for user id 72: [2025-12-16T09:55:40.264Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:55:40.264Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:55:40.264Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:55:40.264Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:55:40.265Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:55:40.265Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20032.424 ms) ====== [2025-12-16T09:55:40.265Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-16T09:55:40.265Z] GC before operation: completed in 146.038 ms, heap usage 356.294 MB -> 89.941 MB. [2025-12-16T09:55:43.463Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:55:45.932Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:55:49.237Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:55:51.725Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:55:53.573Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:55:54.863Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:55:56.712Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:55:58.560Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:55:58.972Z] 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. [2025-12-16T09:55:58.972Z] The best model improves the baseline by 14.52%. [2025-12-16T09:55:59.343Z] Top recommended movies for user id 72: [2025-12-16T09:55:59.343Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:55:59.343Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:55:59.343Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:55:59.343Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:55:59.343Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:55:59.343Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18899.762 ms) ====== [2025-12-16T09:55:59.343Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-16T09:55:59.343Z] GC before operation: completed in 148.103 ms, heap usage 488.829 MB -> 90.030 MB. [2025-12-16T09:56:02.691Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:56:05.195Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:56:08.390Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:56:11.093Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:56:12.945Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:56:14.752Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:56:16.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:56:19.056Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:56:19.056Z] 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. [2025-12-16T09:56:19.056Z] The best model improves the baseline by 14.52%. [2025-12-16T09:56:19.423Z] Top recommended movies for user id 72: [2025-12-16T09:56:19.423Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:56:19.423Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:56:19.423Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:56:19.423Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:56:19.423Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:56:19.423Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19926.296 ms) ====== [2025-12-16T09:56:19.423Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-16T09:56:19.423Z] GC before operation: completed in 145.194 ms, heap usage 371.371 MB -> 90.010 MB. [2025-12-16T09:56:22.657Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:56:25.871Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:56:29.197Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:56:31.667Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:56:33.496Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:56:35.331Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:56:37.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:56:39.059Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:56:39.443Z] 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. [2025-12-16T09:56:39.443Z] The best model improves the baseline by 14.52%. [2025-12-16T09:56:39.899Z] Top recommended movies for user id 72: [2025-12-16T09:56:39.899Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:56:39.899Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:56:39.899Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:56:39.899Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:56:39.899Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:56:39.899Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20251.224 ms) ====== [2025-12-16T09:56:39.899Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-16T09:56:39.899Z] GC before operation: completed in 169.552 ms, heap usage 542.701 MB -> 93.195 MB. [2025-12-16T09:56:43.078Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:56:45.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:56:48.788Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:56:51.249Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:56:53.099Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:56:55.053Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:56:56.881Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:56:58.722Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:56:59.129Z] 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. [2025-12-16T09:56:59.129Z] The best model improves the baseline by 14.52%. [2025-12-16T09:56:59.129Z] Top recommended movies for user id 72: [2025-12-16T09:56:59.129Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:56:59.129Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:56:59.129Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:56:59.129Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:56:59.129Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:56:59.129Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19288.087 ms) ====== [2025-12-16T09:56:59.129Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-16T09:56:59.562Z] GC before operation: completed in 149.354 ms, heap usage 472.993 MB -> 90.144 MB. [2025-12-16T09:57:02.756Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:57:05.263Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:57:08.511Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:57:10.958Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:57:13.470Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:57:15.298Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:57:17.136Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:57:18.971Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:57:18.971Z] 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. [2025-12-16T09:57:19.337Z] The best model improves the baseline by 14.52%. [2025-12-16T09:57:19.337Z] Top recommended movies for user id 72: [2025-12-16T09:57:19.337Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:57:19.337Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:57:19.337Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:57:19.337Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:57:19.337Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:57:19.337Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20043.279 ms) ====== [2025-12-16T09:57:19.337Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-16T09:57:19.730Z] GC before operation: completed in 145.262 ms, heap usage 126.980 MB -> 90.011 MB. [2025-12-16T09:57:22.904Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:57:25.413Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:57:28.728Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:57:31.261Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:57:32.546Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:57:34.387Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:57:35.741Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:57:37.620Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:57:38.015Z] 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. [2025-12-16T09:57:38.015Z] The best model improves the baseline by 14.52%. [2025-12-16T09:57:38.015Z] Top recommended movies for user id 72: [2025-12-16T09:57:38.015Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:57:38.015Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:57:38.015Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:57:38.015Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:57:38.015Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:57:38.015Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18550.022 ms) ====== [2025-12-16T09:57:38.015Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-16T09:57:38.390Z] GC before operation: completed in 145.609 ms, heap usage 261.567 MB -> 89.767 MB. [2025-12-16T09:57:41.607Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:57:44.088Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:57:47.397Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:57:49.964Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:57:51.799Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:57:53.614Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:57:55.450Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:57:57.338Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:57:57.338Z] 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. [2025-12-16T09:57:57.779Z] The best model improves the baseline by 14.52%. [2025-12-16T09:57:57.779Z] Top recommended movies for user id 72: [2025-12-16T09:57:57.779Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:57:57.779Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:57:57.779Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:57:57.779Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:57:57.779Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:57:57.779Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19501.260 ms) ====== [2025-12-16T09:57:57.779Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-16T09:57:57.779Z] GC before operation: completed in 146.032 ms, heap usage 365.687 MB -> 90.160 MB. [2025-12-16T09:58:01.027Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:58:04.219Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:58:07.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:58:09.939Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:58:11.804Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:58:13.738Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:58:15.583Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:58:17.416Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:58:17.786Z] 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. [2025-12-16T09:58:17.786Z] The best model improves the baseline by 14.52%. [2025-12-16T09:58:18.174Z] Top recommended movies for user id 72: [2025-12-16T09:58:18.174Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:58:18.174Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:58:18.174Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:58:18.174Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:58:18.174Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:58:18.174Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20168.463 ms) ====== [2025-12-16T09:58:18.174Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-16T09:58:18.174Z] GC before operation: completed in 149.995 ms, heap usage 380.886 MB -> 89.998 MB. [2025-12-16T09:58:21.421Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:58:23.954Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:58:27.266Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:58:30.466Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:58:31.753Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:58:33.564Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:58:35.461Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:58:37.321Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:58:37.715Z] 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. [2025-12-16T09:58:37.715Z] The best model improves the baseline by 14.52%. [2025-12-16T09:58:37.715Z] Top recommended movies for user id 72: [2025-12-16T09:58:37.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:58:37.715Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:58:37.715Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:58:37.715Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:58:37.715Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:58:37.715Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19548.517 ms) ====== [2025-12-16T09:58:37.715Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-16T09:58:37.715Z] GC before operation: completed in 148.043 ms, heap usage 481.357 MB -> 90.272 MB. [2025-12-16T09:58:41.056Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:58:43.544Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:58:46.005Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:58:49.216Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:58:50.508Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:58:52.354Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:58:53.625Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:58:55.429Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:58:55.834Z] 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. [2025-12-16T09:58:55.834Z] The best model improves the baseline by 14.52%. [2025-12-16T09:58:56.209Z] Top recommended movies for user id 72: [2025-12-16T09:58:56.209Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:58:56.209Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:58:56.209Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:58:56.209Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:58:56.209Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:58:56.209Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18171.763 ms) ====== [2025-12-16T09:58:56.209Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-16T09:58:56.209Z] GC before operation: completed in 158.611 ms, heap usage 115.601 MB -> 93.483 MB. [2025-12-16T09:58:59.420Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:59:01.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:59:05.195Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:59:08.382Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:59:10.212Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:59:11.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:59:13.790Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:59:15.595Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:59:15.972Z] 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. [2025-12-16T09:59:15.972Z] The best model improves the baseline by 14.52%. [2025-12-16T09:59:16.346Z] Top recommended movies for user id 72: [2025-12-16T09:59:16.346Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:59:16.346Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:59:16.346Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:59:16.346Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:59:16.346Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:59:16.346Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20142.520 ms) ====== [2025-12-16T09:59:16.346Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-16T09:59:16.346Z] GC before operation: completed in 147.475 ms, heap usage 258.793 MB -> 89.975 MB. [2025-12-16T09:59:19.535Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-16T09:59:22.706Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-16T09:59:25.971Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-16T09:59:28.405Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-16T09:59:30.205Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-16T09:59:32.120Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-16T09:59:33.926Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-16T09:59:35.775Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-16T09:59:35.775Z] 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. [2025-12-16T09:59:36.136Z] The best model improves the baseline by 14.52%. [2025-12-16T09:59:36.136Z] Top recommended movies for user id 72: [2025-12-16T09:59:36.136Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-16T09:59:36.136Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-16T09:59:36.136Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-16T09:59:36.136Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-16T09:59:36.136Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-16T09:59:36.136Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19656.394 ms) ====== [2025-12-16T09:59:36.899Z] ----------------------------------- [2025-12-16T09:59:36.899Z] renaissance-movie-lens_0_PASSED [2025-12-16T09:59:36.899Z] ----------------------------------- [2025-12-16T09:59:36.899Z] [2025-12-16T09:59:36.899Z] TEST TEARDOWN: [2025-12-16T09:59:36.899Z] Nothing to be done for teardown. [2025-12-16T09:59:36.899Z] renaissance-movie-lens_0 Finish Time: Tue Dec 16 09:59:36 2025 Epoch Time (ms): 1765879176624