[2025-12-13T14:01:47.113Z] Running test renaissance-movie-lens_0 ... [2025-12-13T14:01:47.113Z] =============================================== [2025-12-13T14:01:47.113Z] renaissance-movie-lens_0 Start Time: Sat Dec 13 09:01:46 2025 Epoch Time (ms): 1765634506515 [2025-12-13T14:01:47.113Z] variation: NoOptions [2025-12-13T14:01:47.113Z] JVM_OPTIONS: [2025-12-13T14:01:47.113Z] { \ [2025-12-13T14:01:47.113Z] echo ""; echo "TEST SETUP:"; \ [2025-12-13T14:01:47.113Z] echo "Nothing to be done for setup."; \ [2025-12-13T14:01:47.113Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656330915548/renaissance-movie-lens_0"; \ [2025-12-13T14:01:47.113Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656330915548/renaissance-movie-lens_0"; \ [2025-12-13T14:01:47.113Z] echo ""; echo "TESTING:"; \ [2025-12-13T14:01:47.113Z] "/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_17656330915548/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-13T14:01:47.113Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656330915548/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-13T14:01:47.113Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-13T14:01:47.113Z] echo "Nothing to be done for teardown."; \ [2025-12-13T14:01:47.113Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17656330915548/TestTargetResult"; [2025-12-13T14:01:47.113Z] [2025-12-13T14:01:47.113Z] TEST SETUP: [2025-12-13T14:01:47.113Z] Nothing to be done for setup. [2025-12-13T14:01:47.113Z] [2025-12-13T14:01:47.113Z] TESTING: [2025-12-13T14:01:47.113Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-13T14:01:47.113Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/output_17656330915548/renaissance-movie-lens_0/launcher-090146-8557828772540274818/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-13T14:01:47.113Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-13T14:01:47.113Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-13T14:01:50.756Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-13T14:01:54.453Z] 09:01:54.200 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. [2025-12-13T14:01:56.477Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-13T14:01:56.477Z] Training: 60056, validation: 20285, test: 19854 [2025-12-13T14:01:56.477Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-13T14:01:57.085Z] GC before operation: completed in 149.724 ms, heap usage 298.804 MB -> 75.487 MB. [2025-12-13T14:02:01.972Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:02:06.664Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:02:09.414Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:02:12.489Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:02:13.094Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:02:14.338Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:02:16.337Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:02:17.633Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:02:17.633Z] 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. [2025-12-13T14:02:17.633Z] The best model improves the baseline by 14.34%. [2025-12-13T14:02:18.224Z] Top recommended movies for user id 72: [2025-12-13T14:02:18.224Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:02:18.224Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:02:18.224Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:02:18.224Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:02:18.224Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:02:18.224Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21046.849 ms) ====== [2025-12-13T14:02:18.224Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-13T14:02:18.224Z] GC before operation: completed in 123.999 ms, heap usage 317.895 MB -> 88.084 MB. [2025-12-13T14:02:20.181Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:02:22.951Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:02:24.993Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:02:26.955Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:02:28.223Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:02:29.497Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:02:30.819Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:02:32.093Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:02:32.093Z] 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. [2025-12-13T14:02:32.093Z] The best model improves the baseline by 14.34%. [2025-12-13T14:02:32.093Z] Top recommended movies for user id 72: [2025-12-13T14:02:32.093Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:02:32.093Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:02:32.093Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:02:32.093Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:02:32.093Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:02:32.093Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (14276.594 ms) ====== [2025-12-13T14:02:32.093Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-13T14:02:32.713Z] GC before operation: completed in 154.518 ms, heap usage 445.072 MB -> 91.102 MB. [2025-12-13T14:02:34.711Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:02:36.693Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:02:38.673Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:02:40.669Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:02:41.932Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:02:43.193Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:02:44.440Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:02:45.730Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:02:45.730Z] 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. [2025-12-13T14:02:45.730Z] The best model improves the baseline by 14.34%. [2025-12-13T14:02:45.730Z] Top recommended movies for user id 72: [2025-12-13T14:02:45.730Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:02:45.730Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:02:45.730Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:02:45.730Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:02:45.730Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:02:45.730Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13397.674 ms) ====== [2025-12-13T14:02:45.730Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-13T14:02:46.343Z] GC before operation: completed in 127.479 ms, heap usage 326.705 MB -> 88.436 MB. [2025-12-13T14:02:48.343Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:02:50.321Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:02:53.062Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:02:55.013Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:02:56.272Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:02:57.533Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:02:58.783Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:02:59.382Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:02:59.996Z] 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. [2025-12-13T14:02:59.996Z] The best model improves the baseline by 14.34%. [2025-12-13T14:02:59.996Z] Top recommended movies for user id 72: [2025-12-13T14:02:59.996Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:02:59.996Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:02:59.996Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:02:59.996Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:02:59.996Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:02:59.996Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13923.503 ms) ====== [2025-12-13T14:02:59.996Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-13T14:02:59.996Z] GC before operation: completed in 119.208 ms, heap usage 159.639 MB -> 88.491 MB. [2025-12-13T14:03:02.067Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:03:04.053Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:03:05.736Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:03:06.977Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:03:08.237Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:03:09.496Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:03:10.748Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:03:11.357Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:03:11.960Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T14:03:11.960Z] The best model improves the baseline by 14.34%. [2025-12-13T14:03:11.960Z] Top recommended movies for user id 72: [2025-12-13T14:03:11.960Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:03:11.960Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:03:11.960Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:03:11.960Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:03:11.960Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:03:11.960Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (11813.449 ms) ====== [2025-12-13T14:03:11.960Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-13T14:03:11.960Z] GC before operation: completed in 116.339 ms, heap usage 174.564 MB -> 88.490 MB. [2025-12-13T14:03:14.033Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:03:16.002Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:03:17.986Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:03:19.955Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:03:21.243Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:03:22.539Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:03:23.793Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:03:25.051Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:03:25.051Z] 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. [2025-12-13T14:03:25.051Z] The best model improves the baseline by 14.34%. [2025-12-13T14:03:25.051Z] Top recommended movies for user id 72: [2025-12-13T14:03:25.051Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:03:25.051Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:03:25.051Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:03:25.051Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:03:25.051Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:03:25.051Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13165.784 ms) ====== [2025-12-13T14:03:25.051Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-13T14:03:25.051Z] GC before operation: completed in 109.195 ms, heap usage 156.923 MB -> 88.838 MB. [2025-12-13T14:03:27.828Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:03:29.813Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:03:31.773Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:03:33.723Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:03:34.997Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:03:36.276Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:03:37.548Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:03:38.819Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:03:38.819Z] 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. [2025-12-13T14:03:38.819Z] The best model improves the baseline by 14.34%. [2025-12-13T14:03:38.819Z] Top recommended movies for user id 72: [2025-12-13T14:03:38.819Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:03:38.819Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:03:38.819Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:03:38.819Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:03:38.819Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:03:38.819Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13542.335 ms) ====== [2025-12-13T14:03:38.819Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-13T14:03:38.819Z] GC before operation: completed in 94.871 ms, heap usage 225.458 MB -> 88.868 MB. [2025-12-13T14:03:40.788Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:03:42.770Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:03:44.784Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:03:46.763Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:03:47.370Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:03:48.631Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:03:49.881Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:03:51.183Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:03:51.183Z] 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. [2025-12-13T14:03:51.183Z] The best model improves the baseline by 14.34%. [2025-12-13T14:03:51.183Z] Top recommended movies for user id 72: [2025-12-13T14:03:51.183Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:03:51.183Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:03:51.183Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:03:51.183Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:03:51.183Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:03:51.183Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12245.724 ms) ====== [2025-12-13T14:03:51.183Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-13T14:03:51.183Z] GC before operation: completed in 141.321 ms, heap usage 113.124 MB -> 88.804 MB. [2025-12-13T14:03:53.187Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:03:55.160Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:03:57.130Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:03:58.399Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:03:59.893Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:04:01.143Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:04:02.436Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:04:03.733Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:04:03.733Z] 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. [2025-12-13T14:04:03.733Z] The best model improves the baseline by 14.34%. [2025-12-13T14:04:03.733Z] Top recommended movies for user id 72: [2025-12-13T14:04:03.733Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:04:03.733Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:04:03.733Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:04:03.733Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:04:03.733Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:04:03.733Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12658.690 ms) ====== [2025-12-13T14:04:03.733Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-13T14:04:04.336Z] GC before operation: completed in 116.450 ms, heap usage 107.093 MB -> 92.143 MB. [2025-12-13T14:04:06.338Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:04:08.323Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:04:10.333Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:04:12.319Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:04:12.932Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:04:14.188Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:04:15.462Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:04:16.710Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:04:16.710Z] 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. [2025-12-13T14:04:16.710Z] The best model improves the baseline by 14.34%. [2025-12-13T14:04:16.710Z] Top recommended movies for user id 72: [2025-12-13T14:04:16.710Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:04:16.710Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:04:16.710Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:04:16.710Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:04:16.710Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:04:16.710Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12835.149 ms) ====== [2025-12-13T14:04:16.710Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-13T14:04:17.322Z] GC before operation: completed in 117.933 ms, heap usage 157.438 MB -> 89.072 MB. [2025-12-13T14:04:19.283Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:04:21.295Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:04:23.331Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:04:24.592Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:04:25.868Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:04:27.144Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:04:28.448Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:04:29.753Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:04:29.753Z] 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. [2025-12-13T14:04:29.753Z] The best model improves the baseline by 14.34%. [2025-12-13T14:04:30.383Z] Top recommended movies for user id 72: [2025-12-13T14:04:30.383Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:04:30.383Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:04:30.383Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:04:30.383Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:04:30.383Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:04:30.383Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13075.115 ms) ====== [2025-12-13T14:04:30.383Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-13T14:04:30.383Z] GC before operation: completed in 135.405 ms, heap usage 178.315 MB -> 88.829 MB. [2025-12-13T14:04:32.362Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:04:34.323Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:04:36.293Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:04:38.250Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:04:39.492Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:04:40.100Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:04:41.367Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:04:42.673Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:04:42.673Z] 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. [2025-12-13T14:04:42.673Z] The best model improves the baseline by 14.34%. [2025-12-13T14:04:42.673Z] Top recommended movies for user id 72: [2025-12-13T14:04:42.673Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:04:42.673Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:04:42.673Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:04:42.673Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:04:42.673Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:04:42.673Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12411.539 ms) ====== [2025-12-13T14:04:42.673Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-13T14:04:42.673Z] GC before operation: completed in 118.900 ms, heap usage 213.454 MB -> 88.972 MB. [2025-12-13T14:04:44.663Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:04:46.643Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:04:48.657Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:04:49.933Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:04:51.193Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:04:52.137Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:04:53.388Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:04:54.642Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:04:54.642Z] 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. [2025-12-13T14:04:54.642Z] The best model improves the baseline by 14.34%. [2025-12-13T14:04:54.642Z] Top recommended movies for user id 72: [2025-12-13T14:04:54.642Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:04:54.642Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:04:54.642Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:04:54.642Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:04:54.642Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:04:54.642Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11922.027 ms) ====== [2025-12-13T14:04:54.642Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-13T14:04:54.642Z] GC before operation: completed in 122.801 ms, heap usage 246.437 MB -> 89.213 MB. [2025-12-13T14:04:56.593Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:04:58.593Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:04:59.853Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:05:01.851Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:05:02.503Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:05:03.767Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:05:04.380Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:05:05.658Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:05:05.658Z] 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. [2025-12-13T14:05:05.658Z] The best model improves the baseline by 14.34%. [2025-12-13T14:05:06.273Z] Top recommended movies for user id 72: [2025-12-13T14:05:06.273Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:05:06.273Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:05:06.273Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:05:06.273Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:05:06.273Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:05:06.273Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11128.279 ms) ====== [2025-12-13T14:05:06.273Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-13T14:05:06.273Z] GC before operation: completed in 154.226 ms, heap usage 197.062 MB -> 88.961 MB. [2025-12-13T14:05:08.263Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:05:09.526Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:05:11.496Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:05:12.748Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:05:14.003Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:05:15.253Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:05:16.534Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:05:18.541Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:05:18.541Z] 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. [2025-12-13T14:05:18.541Z] The best model improves the baseline by 14.34%. [2025-12-13T14:05:18.541Z] Top recommended movies for user id 72: [2025-12-13T14:05:18.541Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:05:18.541Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:05:18.541Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:05:18.541Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:05:18.541Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:05:18.541Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12447.702 ms) ====== [2025-12-13T14:05:18.541Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-13T14:05:18.541Z] GC before operation: completed in 169.682 ms, heap usage 285.026 MB -> 89.315 MB. [2025-12-13T14:05:21.304Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:05:23.283Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:05:25.269Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:05:27.248Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:05:28.518Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:05:29.778Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:05:31.063Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:05:32.320Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:05:32.320Z] 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. [2025-12-13T14:05:32.320Z] The best model improves the baseline by 14.34%. [2025-12-13T14:05:32.320Z] Top recommended movies for user id 72: [2025-12-13T14:05:32.320Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:05:32.320Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:05:32.320Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:05:32.320Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:05:32.320Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:05:32.320Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13655.162 ms) ====== [2025-12-13T14:05:32.320Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-13T14:05:32.320Z] GC before operation: completed in 128.085 ms, heap usage 168.453 MB -> 89.008 MB. [2025-12-13T14:05:34.323Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:05:36.334Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:05:39.133Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:05:40.417Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:05:41.693Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:05:42.969Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:05:44.218Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:05:44.950Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:05:44.950Z] 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. [2025-12-13T14:05:45.553Z] The best model improves the baseline by 14.34%. [2025-12-13T14:05:45.553Z] Top recommended movies for user id 72: [2025-12-13T14:05:45.553Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:05:45.553Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:05:45.553Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:05:45.553Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:05:45.553Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:05:45.553Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12866.693 ms) ====== [2025-12-13T14:05:45.553Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-13T14:05:45.553Z] GC before operation: completed in 103.068 ms, heap usage 110.074 MB -> 89.538 MB. [2025-12-13T14:05:47.512Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:05:49.497Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:05:51.484Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:05:53.523Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:05:54.133Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:05:55.412Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:05:56.046Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:05:57.340Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:05:57.340Z] 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. [2025-12-13T14:05:57.340Z] The best model improves the baseline by 14.34%. [2025-12-13T14:05:57.340Z] Top recommended movies for user id 72: [2025-12-13T14:05:57.340Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:05:57.340Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:05:57.340Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:05:57.340Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:05:57.340Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:05:57.340Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12037.390 ms) ====== [2025-12-13T14:05:57.340Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-13T14:05:57.954Z] GC before operation: completed in 139.740 ms, heap usage 163.142 MB -> 88.986 MB. [2025-12-13T14:05:59.233Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:06:01.247Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:06:03.222Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:06:04.473Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:06:05.728Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:06:06.338Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:06:07.596Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:06:08.213Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:06:08.213Z] 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. [2025-12-13T14:06:08.213Z] The best model improves the baseline by 14.34%. [2025-12-13T14:06:08.843Z] Top recommended movies for user id 72: [2025-12-13T14:06:08.843Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:06:08.843Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:06:08.843Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:06:08.843Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:06:08.843Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:06:08.843Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (10851.026 ms) ====== [2025-12-13T14:06:08.843Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-13T14:06:08.843Z] GC before operation: completed in 112.910 ms, heap usage 350.085 MB -> 89.482 MB. [2025-12-13T14:06:10.141Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:06:12.136Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:06:14.130Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:06:15.373Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:06:16.656Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:06:17.915Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:06:19.199Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:06:19.823Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:06:20.417Z] 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. [2025-12-13T14:06:20.417Z] The best model improves the baseline by 14.34%. [2025-12-13T14:06:20.417Z] Top recommended movies for user id 72: [2025-12-13T14:06:20.417Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:06:20.417Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:06:20.417Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:06:20.417Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:06:20.417Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:06:20.417Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11590.987 ms) ====== [2025-12-13T14:06:20.417Z] ----------------------------------- [2025-12-13T14:06:20.417Z] renaissance-movie-lens_0_PASSED [2025-12-13T14:06:20.417Z] ----------------------------------- [2025-12-13T14:06:20.417Z] [2025-12-13T14:06:20.417Z] TEST TEARDOWN: [2025-12-13T14:06:20.417Z] Nothing to be done for teardown. [2025-12-13T14:06:20.417Z] renaissance-movie-lens_0 Finish Time: Sat Dec 13 09:06:20 2025 Epoch Time (ms): 1765634780149