[2025-12-13T12:58:46.231Z] Running test renaissance-movie-lens_0 ... [2025-12-13T12:58:46.231Z] =============================================== [2025-12-13T12:58:46.231Z] renaissance-movie-lens_0 Start Time: Sat Dec 13 12:58:45 2025 Epoch Time (ms): 1765630725415 [2025-12-13T12:58:46.231Z] variation: NoOptions [2025-12-13T12:58:46.231Z] JVM_OPTIONS: [2025-12-13T12:58:46.231Z] { \ [2025-12-13T12:58:46.231Z] echo ""; echo "TEST SETUP:"; \ [2025-12-13T12:58:46.231Z] echo "Nothing to be done for setup."; \ [2025-12-13T12:58:46.231Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656291926499/renaissance-movie-lens_0"; \ [2025-12-13T12:58:46.231Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656291926499/renaissance-movie-lens_0"; \ [2025-12-13T12:58:46.231Z] echo ""; echo "TESTING:"; \ [2025-12-13T12:58:46.231Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_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_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656291926499/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-13T12:58:46.231Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656291926499/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-13T12:58:46.231Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-13T12:58:46.231Z] echo "Nothing to be done for teardown."; \ [2025-12-13T12:58:46.231Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656291926499/TestTargetResult"; [2025-12-13T12:58:46.231Z] [2025-12-13T12:58:46.231Z] TEST SETUP: [2025-12-13T12:58:46.231Z] Nothing to be done for setup. [2025-12-13T12:58:46.231Z] [2025-12-13T12:58:46.231Z] TESTING: [2025-12-13T12:58:46.231Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-13T12:58:46.231Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/output_17656291926499/renaissance-movie-lens_0/launcher-125845-8784187795475762366/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-13T12:58:46.231Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-13T12:58:46.231Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-13T12:58:49.779Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-13T12:58:54.291Z] 12:58:53.341 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-12-13T12:58:55.519Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-13T12:58:56.125Z] Training: 60056, validation: 20285, test: 19854 [2025-12-13T12:58:56.125Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-13T12:58:56.125Z] GC before operation: completed in 115.093 ms, heap usage 227.949 MB -> 75.681 MB. [2025-12-13T12:58:59.698Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T12:59:02.402Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T12:59:05.120Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T12:59:07.043Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T12:59:08.278Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T12:59:09.838Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T12:59:11.062Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T12:59:12.311Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T12:59:12.908Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T12:59:12.908Z] The best model improves the baseline by 14.34%. [2025-12-13T12:59:12.908Z] Top recommended movies for user id 72: [2025-12-13T12:59:12.908Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T12:59:12.908Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T12:59:12.908Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T12:59:12.908Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T12:59:12.908Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T12:59:12.908Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (16957.672 ms) ====== [2025-12-13T12:59:12.908Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-13T12:59:12.908Z] GC before operation: completed in 150.288 ms, heap usage 130.655 MB -> 102.715 MB. [2025-12-13T12:59:14.881Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T12:59:17.581Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T12:59:19.515Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T12:59:21.450Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T12:59:22.675Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T12:59:23.904Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T12:59:25.132Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T12:59:26.386Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T12:59:26.386Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T12:59:26.386Z] The best model improves the baseline by 14.34%. [2025-12-13T12:59:26.386Z] Top recommended movies for user id 72: [2025-12-13T12:59:26.386Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T12:59:26.387Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T12:59:26.387Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T12:59:26.387Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T12:59:26.387Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T12:59:26.387Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (13493.413 ms) ====== [2025-12-13T12:59:26.387Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-13T12:59:26.387Z] GC before operation: completed in 110.879 ms, heap usage 158.245 MB -> 89.470 MB. [2025-12-13T12:59:28.320Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T12:59:30.251Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T12:59:32.176Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T12:59:34.119Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T12:59:35.355Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T12:59:36.578Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T12:59:37.809Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T12:59:38.397Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T12:59:38.987Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T12:59:38.987Z] The best model improves the baseline by 14.34%. [2025-12-13T12:59:38.987Z] Top recommended movies for user id 72: [2025-12-13T12:59:38.987Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T12:59:38.987Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T12:59:38.987Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T12:59:38.987Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T12:59:38.987Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T12:59:38.987Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (12314.067 ms) ====== [2025-12-13T12:59:38.987Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-13T12:59:38.987Z] GC before operation: completed in 149.590 ms, heap usage 165.618 MB -> 88.418 MB. [2025-12-13T12:59:40.924Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T12:59:42.870Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T12:59:45.187Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T12:59:46.424Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T12:59:47.664Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T12:59:48.891Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T12:59:50.123Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T12:59:51.348Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T12:59:51.957Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T12:59:51.957Z] The best model improves the baseline by 14.34%. [2025-12-13T12:59:51.957Z] Top recommended movies for user id 72: [2025-12-13T12:59:51.957Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T12:59:51.957Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T12:59:51.957Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T12:59:51.957Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T12:59:51.957Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T12:59:51.957Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (12875.142 ms) ====== [2025-12-13T12:59:51.957Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-13T12:59:51.957Z] GC before operation: completed in 113.894 ms, heap usage 167.031 MB -> 88.742 MB. [2025-12-13T12:59:53.881Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T12:59:56.596Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T12:59:58.533Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:00:00.457Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:00:01.706Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:00:03.153Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:00:03.748Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:00:04.981Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:00:05.571Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:00:05.571Z] The best model improves the baseline by 14.34%. [2025-12-13T13:00:05.571Z] Top recommended movies for user id 72: [2025-12-13T13:00:05.571Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:00:05.571Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:00:05.571Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:00:05.571Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:00:05.571Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:00:05.571Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13278.668 ms) ====== [2025-12-13T13:00:05.571Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-13T13:00:05.571Z] GC before operation: completed in 121.727 ms, heap usage 424.276 MB -> 89.111 MB. [2025-12-13T13:00:07.497Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:00:09.427Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:00:12.118Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:00:13.344Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:00:14.574Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:00:15.806Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:00:17.067Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:00:17.653Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:00:18.243Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:00:18.243Z] The best model improves the baseline by 14.34%. [2025-12-13T13:00:18.243Z] Top recommended movies for user id 72: [2025-12-13T13:00:18.243Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:00:18.243Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:00:18.243Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:00:18.243Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:00:18.243Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:00:18.243Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12632.337 ms) ====== [2025-12-13T13:00:18.243Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-13T13:00:18.243Z] GC before operation: completed in 127.346 ms, heap usage 299.530 MB -> 89.320 MB. [2025-12-13T13:00:20.174Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:00:22.122Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:00:24.046Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:00:25.980Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:00:27.208Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:00:27.796Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:00:29.025Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:00:30.320Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:00:30.320Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:00:30.320Z] The best model improves the baseline by 14.34%. [2025-12-13T13:00:30.320Z] Top recommended movies for user id 72: [2025-12-13T13:00:30.320Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:00:30.320Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:00:30.320Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:00:30.320Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:00:30.320Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:00:30.320Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12086.416 ms) ====== [2025-12-13T13:00:30.320Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-13T13:00:30.320Z] GC before operation: completed in 123.331 ms, heap usage 191.149 MB -> 89.000 MB. [2025-12-13T13:00:32.244Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:00:34.170Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:00:36.100Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:00:37.347Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:00:38.580Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:00:39.817Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:00:41.045Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:00:41.632Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:00:42.225Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:00:42.225Z] The best model improves the baseline by 14.34%. [2025-12-13T13:00:42.225Z] Top recommended movies for user id 72: [2025-12-13T13:00:42.225Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:00:42.225Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:00:42.225Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:00:42.225Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:00:42.225Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:00:42.225Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (11700.549 ms) ====== [2025-12-13T13:00:42.225Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-13T13:00:42.225Z] GC before operation: completed in 105.947 ms, heap usage 246.987 MB -> 89.367 MB. [2025-12-13T13:00:44.152Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:00:46.085Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:00:48.008Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:00:49.237Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:00:50.467Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:00:52.038Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:00:52.627Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:00:53.862Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:00:54.452Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:00:54.452Z] The best model improves the baseline by 14.34%. [2025-12-13T13:00:54.452Z] Top recommended movies for user id 72: [2025-12-13T13:00:54.452Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:00:54.452Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:00:54.452Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:00:54.452Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:00:54.452Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:00:54.452Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12175.445 ms) ====== [2025-12-13T13:00:54.452Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-13T13:00:54.452Z] GC before operation: completed in 93.150 ms, heap usage 111.713 MB -> 88.917 MB. [2025-12-13T13:00:56.391Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:00:59.096Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:01:01.022Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:01:03.028Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:01:04.269Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:01:05.498Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:01:06.741Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:01:07.977Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:01:07.977Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:01:07.977Z] The best model improves the baseline by 14.34%. [2025-12-13T13:01:08.577Z] Top recommended movies for user id 72: [2025-12-13T13:01:08.577Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:01:08.577Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:01:08.577Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:01:08.577Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:01:08.577Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:01:08.577Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13818.693 ms) ====== [2025-12-13T13:01:08.577Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-13T13:01:08.577Z] GC before operation: completed in 115.893 ms, heap usage 110.625 MB -> 89.104 MB. [2025-12-13T13:01:10.501Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:01:11.755Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:01:14.458Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:01:15.692Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:01:16.935Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:01:18.165Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:01:19.393Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:01:20.625Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:01:21.215Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:01:21.215Z] The best model improves the baseline by 14.34%. [2025-12-13T13:01:21.215Z] Top recommended movies for user id 72: [2025-12-13T13:01:21.215Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:01:21.215Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:01:21.215Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:01:21.215Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:01:21.215Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:01:21.215Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12663.012 ms) ====== [2025-12-13T13:01:21.215Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-13T13:01:21.215Z] GC before operation: completed in 126.901 ms, heap usage 423.695 MB -> 89.476 MB. [2025-12-13T13:01:23.437Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:01:25.366Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:01:27.292Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:01:29.225Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:01:29.813Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:01:31.050Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:01:32.274Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:01:32.866Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:01:33.458Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:01:33.458Z] The best model improves the baseline by 14.34%. [2025-12-13T13:01:33.458Z] Top recommended movies for user id 72: [2025-12-13T13:01:33.458Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:01:33.458Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:01:33.458Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:01:33.458Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:01:33.458Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:01:33.458Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12086.508 ms) ====== [2025-12-13T13:01:33.458Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-13T13:01:33.458Z] GC before operation: completed in 102.528 ms, heap usage 111.406 MB -> 89.174 MB. [2025-12-13T13:01:35.391Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:01:37.316Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:01:38.543Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:01:40.474Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:01:41.065Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:01:42.297Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:01:43.531Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:01:44.768Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:01:44.768Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:01:44.768Z] The best model improves the baseline by 14.34%. [2025-12-13T13:01:44.768Z] Top recommended movies for user id 72: [2025-12-13T13:01:44.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:01:44.768Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:01:44.768Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:01:44.768Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:01:44.768Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:01:44.768Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11523.362 ms) ====== [2025-12-13T13:01:44.768Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-13T13:01:45.355Z] GC before operation: completed in 145.112 ms, heap usage 216.225 MB -> 89.344 MB. [2025-12-13T13:01:47.291Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:01:48.517Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:01:50.442Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:01:51.674Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:01:52.974Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:01:53.562Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:01:54.792Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:01:55.654Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:01:56.311Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:01:56.311Z] The best model improves the baseline by 14.34%. [2025-12-13T13:01:56.311Z] Top recommended movies for user id 72: [2025-12-13T13:01:56.311Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:01:56.311Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:01:56.311Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:01:56.311Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:01:56.311Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:01:56.311Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (10892.556 ms) ====== [2025-12-13T13:01:56.311Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-13T13:01:56.311Z] GC before operation: completed in 105.091 ms, heap usage 300.605 MB -> 89.387 MB. [2025-12-13T13:01:58.247Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:01:59.480Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:02:01.415Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:02:02.653Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:02:03.880Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:02:04.476Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:02:05.708Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:02:06.949Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:02:06.949Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:02:06.949Z] The best model improves the baseline by 14.34%. [2025-12-13T13:02:06.949Z] Top recommended movies for user id 72: [2025-12-13T13:02:06.949Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:02:06.949Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:02:06.949Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:02:06.949Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:02:06.949Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:02:06.949Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (10821.051 ms) ====== [2025-12-13T13:02:06.949Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-13T13:02:06.949Z] GC before operation: completed in 96.604 ms, heap usage 202.830 MB -> 89.383 MB. [2025-12-13T13:02:08.886Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:02:10.109Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:02:12.040Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:02:13.963Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:02:14.560Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:02:15.789Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:02:17.014Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:02:17.601Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:02:17.601Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:02:17.601Z] The best model improves the baseline by 14.34%. [2025-12-13T13:02:18.190Z] Top recommended movies for user id 72: [2025-12-13T13:02:18.190Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:02:18.190Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:02:18.190Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:02:18.190Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:02:18.190Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:02:18.190Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (10833.964 ms) ====== [2025-12-13T13:02:18.190Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-13T13:02:18.190Z] GC before operation: completed in 92.315 ms, heap usage 229.107 MB -> 89.354 MB. [2025-12-13T13:02:19.418Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:02:21.344Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:02:23.272Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:02:25.199Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:02:26.793Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:02:27.381Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:02:28.617Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:02:29.209Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:02:29.209Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:02:29.209Z] The best model improves the baseline by 14.34%. [2025-12-13T13:02:29.796Z] Top recommended movies for user id 72: [2025-12-13T13:02:29.796Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:02:29.796Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:02:29.796Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:02:29.796Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:02:29.796Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:02:29.796Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (11554.523 ms) ====== [2025-12-13T13:02:29.796Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-13T13:02:29.796Z] GC before operation: completed in 114.026 ms, heap usage 247.024 MB -> 89.471 MB. [2025-12-13T13:02:31.020Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:02:32.965Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:02:34.902Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:02:36.835Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:02:38.074Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:02:38.664Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:02:39.937Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:02:41.200Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:02:41.200Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:02:41.788Z] The best model improves the baseline by 14.34%. [2025-12-13T13:02:41.788Z] Top recommended movies for user id 72: [2025-12-13T13:02:41.788Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:02:41.788Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:02:41.788Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:02:41.788Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:02:41.788Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:02:41.788Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11932.500 ms) ====== [2025-12-13T13:02:41.788Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-13T13:02:41.788Z] GC before operation: completed in 138.516 ms, heap usage 235.019 MB -> 89.310 MB. [2025-12-13T13:02:43.712Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:02:45.644Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:02:47.602Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:02:49.527Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:02:50.114Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:02:51.341Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:02:52.569Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:02:53.822Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:02:54.413Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:02:54.413Z] The best model improves the baseline by 14.34%. [2025-12-13T13:02:54.413Z] Top recommended movies for user id 72: [2025-12-13T13:02:54.413Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:02:54.413Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:02:54.413Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:02:54.413Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:02:54.413Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:02:54.413Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12571.879 ms) ====== [2025-12-13T13:02:54.413Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-13T13:02:54.413Z] GC before operation: completed in 127.297 ms, heap usage 437.425 MB -> 92.846 MB. [2025-12-13T13:02:56.338Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:02:58.262Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:03:00.200Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:03:01.757Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:03:02.986Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:03:04.231Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:03:05.496Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:03:06.083Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:03:06.673Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:03:06.673Z] The best model improves the baseline by 14.34%. [2025-12-13T13:03:06.673Z] Top recommended movies for user id 72: [2025-12-13T13:03:06.673Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:03:06.673Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:03:06.673Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:03:06.673Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:03:06.673Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:03:06.673Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12168.469 ms) ====== [2025-12-13T13:03:06.673Z] ----------------------------------- [2025-12-13T13:03:06.673Z] renaissance-movie-lens_0_PASSED [2025-12-13T13:03:06.673Z] ----------------------------------- [2025-12-13T13:03:06.673Z] [2025-12-13T13:03:06.673Z] TEST TEARDOWN: [2025-12-13T13:03:06.673Z] Nothing to be done for teardown. [2025-12-13T13:03:06.673Z] renaissance-movie-lens_0 Finish Time: Sat Dec 13 13:03:06 2025 Epoch Time (ms): 1765630986540