[2025-12-27T13:42:34.328Z] Running test renaissance-movie-lens_0 ... [2025-12-27T13:42:34.328Z] =============================================== [2025-12-27T13:42:34.328Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 13:42:34 2025 Epoch Time (ms): 1766842954239 [2025-12-27T13:42:34.328Z] variation: NoOptions [2025-12-27T13:42:34.328Z] JVM_OPTIONS: [2025-12-27T13:42:34.328Z] { \ [2025-12-27T13:42:34.328Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T13:42:34.328Z] echo "Nothing to be done for setup."; \ [2025-12-27T13:42:34.328Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17668405404929/renaissance-movie-lens_0"; \ [2025-12-27T13:42:34.328Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17668405404929/renaissance-movie-lens_0"; \ [2025-12-27T13:42:34.328Z] echo ""; echo "TESTING:"; \ [2025-12-27T13:42:34.328Z] "/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_17668405404929/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T13:42:34.328Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17668405404929/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T13:42:34.328Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T13:42:34.328Z] echo "Nothing to be done for teardown."; \ [2025-12-27T13:42:34.328Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17668405404929/TestTargetResult"; [2025-12-27T13:42:34.328Z] [2025-12-27T13:42:34.328Z] TEST SETUP: [2025-12-27T13:42:34.328Z] Nothing to be done for setup. [2025-12-27T13:42:34.328Z] [2025-12-27T13:42:34.328Z] TESTING: [2025-12-27T13:42:35.754Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T13:42:35.754Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/output_17668405404929/renaissance-movie-lens_0/launcher-134234-11085972517133470540/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T13:42:35.754Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T13:42:35.754Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T13:42:40.787Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-27T13:42:48.366Z] 13:42:47.844 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-12-27T13:42:50.560Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T13:42:51.257Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T13:42:51.257Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T13:42:51.924Z] GC before operation: completed in 252.859 ms, heap usage 389.650 MB -> 75.721 MB. [2025-12-27T13:43:01.490Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:43:09.217Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:43:14.251Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:43:19.270Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:43:22.370Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:43:25.420Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:43:28.435Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:43:30.681Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:43:31.363Z] 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. [2025-12-27T13:43:31.363Z] The best model improves the baseline by 14.34%. [2025-12-27T13:43:32.064Z] Top recommended movies for user id 72: [2025-12-27T13:43:32.064Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:43:32.064Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:43:32.064Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:43:32.064Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:43:32.064Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:43:32.064Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (40153.383 ms) ====== [2025-12-27T13:43:32.064Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T13:43:32.064Z] GC before operation: completed in 199.287 ms, heap usage 311.722 MB -> 88.320 MB. [2025-12-27T13:43:36.044Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:43:40.542Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:43:45.591Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:43:49.659Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:43:51.863Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:43:54.060Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:43:57.086Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:43:59.236Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:43:59.910Z] 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. [2025-12-27T13:43:59.910Z] The best model improves the baseline by 14.34%. [2025-12-27T13:43:59.910Z] Top recommended movies for user id 72: [2025-12-27T13:43:59.910Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:43:59.910Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:43:59.910Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:43:59.910Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:43:59.910Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:43:59.910Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (27815.367 ms) ====== [2025-12-27T13:43:59.910Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T13:43:59.910Z] GC before operation: completed in 175.854 ms, heap usage 161.300 MB -> 87.592 MB. [2025-12-27T13:44:03.933Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:44:09.103Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:44:13.063Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:44:16.998Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:44:18.467Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:44:20.643Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:44:23.211Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:44:25.361Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:44:25.361Z] 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. [2025-12-27T13:44:25.361Z] The best model improves the baseline by 14.34%. [2025-12-27T13:44:25.361Z] Top recommended movies for user id 72: [2025-12-27T13:44:25.361Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:44:25.361Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:44:25.361Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:44:25.361Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:44:25.361Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:44:25.361Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (25550.534 ms) ====== [2025-12-27T13:44:25.361Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T13:44:26.031Z] GC before operation: completed in 208.328 ms, heap usage 306.695 MB -> 88.550 MB. [2025-12-27T13:44:29.121Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:44:33.022Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:44:37.028Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:44:40.043Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:44:42.241Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:44:44.415Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:44:46.570Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:44:48.722Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:44:49.384Z] 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. [2025-12-27T13:44:49.384Z] The best model improves the baseline by 14.34%. [2025-12-27T13:44:49.384Z] Top recommended movies for user id 72: [2025-12-27T13:44:49.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:44:49.384Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:44:49.384Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:44:49.384Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:44:49.384Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:44:49.384Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23481.697 ms) ====== [2025-12-27T13:44:49.384Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T13:44:49.384Z] GC before operation: completed in 230.021 ms, heap usage 215.204 MB -> 88.702 MB. [2025-12-27T13:44:53.415Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:44:57.406Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:45:01.782Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:45:05.794Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:45:07.965Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:45:10.104Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:45:12.245Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:45:15.249Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:45:15.249Z] 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. [2025-12-27T13:45:15.249Z] The best model improves the baseline by 14.34%. [2025-12-27T13:45:15.249Z] Top recommended movies for user id 72: [2025-12-27T13:45:15.249Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:45:15.249Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:45:15.249Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:45:15.249Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:45:15.249Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:45:15.249Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (25792.869 ms) ====== [2025-12-27T13:45:15.249Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T13:45:15.249Z] GC before operation: completed in 228.657 ms, heap usage 210.930 MB -> 88.631 MB. [2025-12-27T13:45:19.221Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:45:23.275Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:45:27.373Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:45:31.382Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:45:34.430Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:45:35.794Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:45:38.785Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:45:40.990Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:45:40.990Z] 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. [2025-12-27T13:45:40.990Z] The best model improves the baseline by 14.34%. [2025-12-27T13:45:40.990Z] Top recommended movies for user id 72: [2025-12-27T13:45:40.990Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:45:40.990Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:45:40.990Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:45:40.990Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:45:40.990Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:45:40.990Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (25596.455 ms) ====== [2025-12-27T13:45:40.990Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T13:45:41.652Z] GC before operation: completed in 226.257 ms, heap usage 309.135 MB -> 89.233 MB. [2025-12-27T13:45:45.585Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:45:48.676Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:45:52.657Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:45:56.595Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:45:58.810Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:46:01.024Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:46:03.148Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:46:05.285Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:46:05.285Z] 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. [2025-12-27T13:46:05.285Z] The best model improves the baseline by 14.34%. [2025-12-27T13:46:05.285Z] Top recommended movies for user id 72: [2025-12-27T13:46:05.285Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:46:05.285Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:46:05.285Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:46:05.285Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:46:05.285Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:46:05.285Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (24195.521 ms) ====== [2025-12-27T13:46:05.285Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T13:46:05.933Z] GC before operation: completed in 241.843 ms, heap usage 210.490 MB -> 88.985 MB. [2025-12-27T13:46:08.914Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:46:12.837Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:46:15.831Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:46:19.799Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:46:21.963Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:46:23.384Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:46:26.770Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:46:28.175Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:46:28.175Z] 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. [2025-12-27T13:46:28.175Z] The best model improves the baseline by 14.34%. [2025-12-27T13:46:28.870Z] Top recommended movies for user id 72: [2025-12-27T13:46:28.870Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:46:28.870Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:46:28.870Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:46:28.870Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:46:28.870Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:46:28.870Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22755.857 ms) ====== [2025-12-27T13:46:28.870Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T13:46:28.870Z] GC before operation: completed in 234.170 ms, heap usage 224.162 MB -> 89.242 MB. [2025-12-27T13:46:32.776Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:46:35.711Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:46:38.666Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:46:40.778Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:46:42.945Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:46:44.287Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:46:46.363Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:46:48.409Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:46:48.409Z] 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. [2025-12-27T13:46:48.409Z] The best model improves the baseline by 14.34%. [2025-12-27T13:46:48.409Z] Top recommended movies for user id 72: [2025-12-27T13:46:48.409Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:46:48.409Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:46:48.409Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:46:48.409Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:46:48.409Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:46:48.409Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19822.749 ms) ====== [2025-12-27T13:46:48.409Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T13:46:49.055Z] GC before operation: completed in 237.504 ms, heap usage 171.847 MB -> 89.029 MB. [2025-12-27T13:46:51.174Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:46:54.457Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:46:57.401Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:47:00.325Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:47:01.643Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:47:02.973Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:47:05.047Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:47:06.495Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:47:07.134Z] 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. [2025-12-27T13:47:07.134Z] The best model improves the baseline by 14.34%. [2025-12-27T13:47:07.134Z] Top recommended movies for user id 72: [2025-12-27T13:47:07.134Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:47:07.134Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:47:07.134Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:47:07.134Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:47:07.134Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:47:07.134Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18195.682 ms) ====== [2025-12-27T13:47:07.134Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T13:47:07.134Z] GC before operation: completed in 203.855 ms, heap usage 189.616 MB -> 89.178 MB. [2025-12-27T13:47:10.032Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:47:12.937Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:47:16.745Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:47:18.843Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:47:20.913Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:47:22.234Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:47:24.396Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:47:26.590Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:47:26.590Z] 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. [2025-12-27T13:47:26.590Z] The best model improves the baseline by 14.34%. [2025-12-27T13:47:26.591Z] Top recommended movies for user id 72: [2025-12-27T13:47:26.591Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:47:26.591Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:47:26.591Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:47:26.591Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:47:26.591Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:47:26.591Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19525.410 ms) ====== [2025-12-27T13:47:26.591Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T13:47:27.230Z] GC before operation: completed in 244.136 ms, heap usage 251.758 MB -> 89.075 MB. [2025-12-27T13:47:30.198Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:47:34.096Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:47:37.510Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:47:40.491Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:47:41.832Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:47:43.957Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:47:46.177Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:47:47.534Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:47:48.180Z] 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. [2025-12-27T13:47:48.180Z] The best model improves the baseline by 14.34%. [2025-12-27T13:47:48.180Z] Top recommended movies for user id 72: [2025-12-27T13:47:48.180Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:47:48.180Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:47:48.180Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:47:48.180Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:47:48.180Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:47:48.180Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (21149.304 ms) ====== [2025-12-27T13:47:48.180Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T13:47:48.180Z] GC before operation: completed in 180.400 ms, heap usage 136.521 MB -> 89.214 MB. [2025-12-27T13:47:52.028Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:47:55.889Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:47:59.757Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:48:02.826Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:48:04.977Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:48:06.336Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:48:09.284Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:48:10.605Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:48:11.369Z] 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. [2025-12-27T13:48:11.369Z] The best model improves the baseline by 14.34%. [2025-12-27T13:48:11.369Z] Top recommended movies for user id 72: [2025-12-27T13:48:11.369Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:48:11.369Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:48:11.369Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:48:11.369Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:48:11.369Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:48:11.369Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22959.161 ms) ====== [2025-12-27T13:48:11.369Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T13:48:11.369Z] GC before operation: completed in 188.902 ms, heap usage 119.052 MB -> 89.171 MB. [2025-12-27T13:48:14.630Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:48:18.541Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:48:21.456Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:48:24.456Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:48:26.631Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:48:27.991Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:48:30.103Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:48:31.468Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:48:32.115Z] 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. [2025-12-27T13:48:32.115Z] The best model improves the baseline by 14.34%. [2025-12-27T13:48:32.115Z] Top recommended movies for user id 72: [2025-12-27T13:48:32.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:48:32.115Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:48:32.115Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:48:32.115Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:48:32.115Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:48:32.115Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20669.396 ms) ====== [2025-12-27T13:48:32.115Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T13:48:32.115Z] GC before operation: completed in 183.740 ms, heap usage 141.861 MB -> 89.085 MB. [2025-12-27T13:48:35.142Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:48:38.048Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:48:41.051Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:48:44.015Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:48:46.128Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:48:47.481Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:48:49.566Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:48:50.917Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:48:50.917Z] 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. [2025-12-27T13:48:50.917Z] The best model improves the baseline by 14.34%. [2025-12-27T13:48:50.917Z] Top recommended movies for user id 72: [2025-12-27T13:48:50.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:48:50.917Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:48:50.917Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:48:50.917Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:48:50.917Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:48:50.917Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18670.276 ms) ====== [2025-12-27T13:48:50.917Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T13:48:51.555Z] GC before operation: completed in 200.401 ms, heap usage 182.927 MB -> 89.295 MB. [2025-12-27T13:48:54.050Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:48:56.961Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:48:59.900Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:49:02.024Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:49:04.146Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:49:05.494Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:49:07.653Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:49:09.050Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:49:09.050Z] 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. [2025-12-27T13:49:09.050Z] The best model improves the baseline by 14.34%. [2025-12-27T13:49:09.685Z] Top recommended movies for user id 72: [2025-12-27T13:49:09.685Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:49:09.685Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:49:09.685Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:49:09.685Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:49:09.685Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:49:09.685Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18180.462 ms) ====== [2025-12-27T13:49:09.685Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T13:49:09.685Z] GC before operation: completed in 184.453 ms, heap usage 108.385 MB -> 89.084 MB. [2025-12-27T13:49:12.671Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:49:15.752Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:49:18.681Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:49:21.671Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:49:23.079Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:49:25.229Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:49:26.562Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:49:28.677Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:49:28.677Z] 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. [2025-12-27T13:49:28.677Z] The best model improves the baseline by 14.34%. [2025-12-27T13:49:28.677Z] Top recommended movies for user id 72: [2025-12-27T13:49:28.677Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:49:28.677Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:49:28.677Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:49:28.677Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:49:28.677Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:49:28.677Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19295.496 ms) ====== [2025-12-27T13:49:28.677Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T13:49:29.706Z] GC before operation: completed in 161.582 ms, heap usage 158.872 MB -> 89.307 MB. [2025-12-27T13:49:31.821Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:49:34.888Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:49:38.839Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:49:41.738Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:49:43.108Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:49:45.291Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:49:48.297Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:49:49.640Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:49:50.288Z] 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. [2025-12-27T13:49:50.288Z] The best model improves the baseline by 14.34%. [2025-12-27T13:49:50.288Z] Top recommended movies for user id 72: [2025-12-27T13:49:50.288Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:49:50.288Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:49:50.288Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:49:50.288Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:49:50.288Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:49:50.288Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (21193.553 ms) ====== [2025-12-27T13:49:50.288Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T13:49:50.288Z] GC before operation: completed in 176.291 ms, heap usage 206.818 MB -> 89.145 MB. [2025-12-27T13:49:53.275Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:49:55.345Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:49:58.276Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:50:00.368Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:50:02.451Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:50:03.088Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:50:05.389Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:50:06.695Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:50:06.695Z] 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. [2025-12-27T13:50:06.695Z] The best model improves the baseline by 14.34%. [2025-12-27T13:50:06.695Z] Top recommended movies for user id 72: [2025-12-27T13:50:06.695Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:50:06.695Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:50:06.695Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:50:06.695Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:50:06.695Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:50:06.695Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16429.666 ms) ====== [2025-12-27T13:50:06.695Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T13:50:07.341Z] GC before operation: completed in 172.023 ms, heap usage 208.559 MB -> 89.266 MB. [2025-12-27T13:50:09.392Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:50:11.451Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:50:14.344Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:50:16.401Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:50:18.466Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:50:19.772Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:50:21.077Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:50:22.388Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:50:23.015Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-27T13:50:23.015Z] The best model improves the baseline by 14.34%. [2025-12-27T13:50:23.015Z] Top recommended movies for user id 72: [2025-12-27T13:50:23.015Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:50:23.015Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:50:23.015Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:50:23.015Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:50:23.015Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:50:23.015Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15849.192 ms) ====== [2025-12-27T13:50:23.015Z] ----------------------------------- [2025-12-27T13:50:23.015Z] renaissance-movie-lens_0_PASSED [2025-12-27T13:50:23.015Z] ----------------------------------- [2025-12-27T13:50:23.015Z] [2025-12-27T13:50:23.015Z] TEST TEARDOWN: [2025-12-27T13:50:23.015Z] Nothing to be done for teardown. [2025-12-27T13:50:23.015Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 13:50:22 2025 Epoch Time (ms): 1766843422859