[2025-12-27T14:32:50.690Z] Running test renaissance-movie-lens_0 ... [2025-12-27T14:32:50.690Z] =============================================== [2025-12-27T14:32:50.690Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 14:32:50 2025 Epoch Time (ms): 1766845970536 [2025-12-27T14:32:50.690Z] variation: NoOptions [2025-12-27T14:32:50.690Z] JVM_OPTIONS: [2025-12-27T14:32:50.690Z] { \ [2025-12-27T14:32:50.690Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T14:32:50.690Z] echo "Nothing to be done for setup."; \ [2025-12-27T14:32:50.690Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1766843704659/renaissance-movie-lens_0"; \ [2025-12-27T14:32:50.690Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1766843704659/renaissance-movie-lens_0"; \ [2025-12-27T14:32:50.690Z] echo ""; echo "TESTING:"; \ [2025-12-27T14:32:50.690Z] "/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_1766843704659/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T14:32:50.690Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1766843704659/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T14:32:50.690Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T14:32:50.690Z] echo "Nothing to be done for teardown."; \ [2025-12-27T14:32:50.690Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1766843704659/TestTargetResult"; [2025-12-27T14:32:50.690Z] [2025-12-27T14:32:50.690Z] TEST SETUP: [2025-12-27T14:32:50.690Z] Nothing to be done for setup. [2025-12-27T14:32:50.690Z] [2025-12-27T14:32:50.690Z] TESTING: [2025-12-27T14:32:52.073Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T14:32:52.073Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/output_1766843704659/renaissance-movie-lens_0/launcher-143250-10475491225208485886/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T14:32:52.073Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T14:32:52.073Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T14:32:55.952Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-27T14:33:01.989Z] 14:33:01.764 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. [2025-12-27T14:33:04.903Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T14:33:05.569Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T14:33:05.569Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T14:33:05.569Z] GC before operation: completed in 206.966 ms, heap usage 358.363 MB -> 75.641 MB. [2025-12-27T14:33:13.360Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:33:17.186Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:33:22.200Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:33:26.113Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:33:28.187Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:33:30.267Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:33:32.422Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:33:34.490Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:33:35.131Z] 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. [2025-12-27T14:33:35.132Z] The best model improves the baseline by 14.34%. [2025-12-27T14:33:35.132Z] Top recommended movies for user id 72: [2025-12-27T14:33:35.132Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:33:35.132Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:33:35.132Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:33:35.132Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:33:35.132Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:33:35.132Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29587.840 ms) ====== [2025-12-27T14:33:35.132Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T14:33:35.773Z] GC before operation: completed in 191.653 ms, heap usage 286.118 MB -> 87.240 MB. [2025-12-27T14:33:38.695Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:33:42.488Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:33:46.327Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:33:49.696Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:33:51.831Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:33:53.988Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:33:56.091Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:33:57.437Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:33:58.105Z] 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. [2025-12-27T14:33:58.105Z] The best model improves the baseline by 14.34%. [2025-12-27T14:33:58.105Z] Top recommended movies for user id 72: [2025-12-27T14:33:58.105Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:33:58.105Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:33:58.105Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:33:58.105Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:33:58.105Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:33:58.105Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22776.751 ms) ====== [2025-12-27T14:33:58.105Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T14:33:58.755Z] GC before operation: completed in 215.684 ms, heap usage 240.410 MB -> 87.744 MB. [2025-12-27T14:34:01.769Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:34:04.683Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:34:07.586Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:34:10.534Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:34:12.632Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:34:13.946Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:34:16.104Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:34:18.225Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:34:18.225Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-27T14:34:18.225Z] The best model improves the baseline by 14.34%. [2025-12-27T14:34:18.225Z] Top recommended movies for user id 72: [2025-12-27T14:34:18.225Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:34:18.225Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:34:18.225Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:34:18.225Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:34:18.225Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:34:18.225Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20012.367 ms) ====== [2025-12-27T14:34:18.225Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T14:34:18.883Z] GC before operation: completed in 232.516 ms, heap usage 215.648 MB -> 88.422 MB. [2025-12-27T14:34:21.820Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:34:25.178Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:34:28.068Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:34:31.026Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:34:32.414Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:34:34.537Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:34:35.859Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:34:37.949Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:34:37.949Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-27T14:34:37.949Z] The best model improves the baseline by 14.34%. [2025-12-27T14:34:38.586Z] Top recommended movies for user id 72: [2025-12-27T14:34:38.586Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:34:38.586Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:34:38.586Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:34:38.586Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:34:38.586Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:34:38.586Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19633.190 ms) ====== [2025-12-27T14:34:38.586Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T14:34:38.586Z] GC before operation: completed in 181.730 ms, heap usage 114.311 MB -> 88.605 MB. [2025-12-27T14:34:41.512Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:34:45.380Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:34:48.362Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:34:51.428Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:34:52.782Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:34:54.887Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:34:56.225Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:34:58.309Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:34:58.309Z] 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. [2025-12-27T14:34:58.309Z] The best model improves the baseline by 14.34%. [2025-12-27T14:34:58.950Z] Top recommended movies for user id 72: [2025-12-27T14:34:58.950Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:34:58.950Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:34:58.950Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:34:58.950Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:34:58.950Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:34:58.950Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20127.344 ms) ====== [2025-12-27T14:34:58.950Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T14:34:58.950Z] GC before operation: completed in 180.177 ms, heap usage 225.004 MB -> 88.748 MB. [2025-12-27T14:35:02.282Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:35:05.290Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:35:08.274Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:35:11.364Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:35:12.741Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:35:14.817Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:35:16.230Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:35:18.349Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:35:18.349Z] 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. [2025-12-27T14:35:18.349Z] The best model improves the baseline by 14.34%. [2025-12-27T14:35:19.017Z] Top recommended movies for user id 72: [2025-12-27T14:35:19.017Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:35:19.017Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:35:19.017Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:35:19.017Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:35:19.017Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:35:19.017Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19909.508 ms) ====== [2025-12-27T14:35:19.017Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T14:35:19.017Z] GC before operation: completed in 193.531 ms, heap usage 211.702 MB -> 89.062 MB. [2025-12-27T14:35:21.961Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:35:24.928Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:35:28.826Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:35:31.809Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:35:33.131Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:35:35.282Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:35:36.599Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:35:38.718Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:35:38.718Z] 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. [2025-12-27T14:35:38.718Z] The best model improves the baseline by 14.34%. [2025-12-27T14:35:39.355Z] Top recommended movies for user id 72: [2025-12-27T14:35:39.355Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:35:39.355Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:35:39.355Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:35:39.355Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:35:39.355Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:35:39.355Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20215.619 ms) ====== [2025-12-27T14:35:39.355Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T14:35:39.355Z] GC before operation: completed in 206.196 ms, heap usage 249.051 MB -> 89.176 MB. [2025-12-27T14:35:42.256Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:35:44.657Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:35:47.614Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:35:50.619Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:35:52.724Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:35:54.060Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:35:56.147Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:35:57.491Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:35:58.146Z] 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. [2025-12-27T14:35:58.146Z] The best model improves the baseline by 14.34%. [2025-12-27T14:35:58.146Z] Top recommended movies for user id 72: [2025-12-27T14:35:58.146Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:35:58.146Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:35:58.146Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:35:58.146Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:35:58.146Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:35:58.146Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18632.540 ms) ====== [2025-12-27T14:35:58.146Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T14:35:58.146Z] GC before operation: completed in 161.585 ms, heap usage 354.430 MB -> 89.492 MB. [2025-12-27T14:36:01.172Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:36:04.064Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:36:07.000Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:36:09.959Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:36:11.354Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:36:12.684Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:36:14.858Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:36:16.958Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:36:16.958Z] 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. [2025-12-27T14:36:16.958Z] The best model improves the baseline by 14.34%. [2025-12-27T14:36:17.609Z] Top recommended movies for user id 72: [2025-12-27T14:36:17.609Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:36:17.609Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:36:17.609Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:36:17.609Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:36:17.609Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:36:17.609Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19130.997 ms) ====== [2025-12-27T14:36:17.609Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T14:36:17.609Z] GC before operation: completed in 183.906 ms, heap usage 167.533 MB -> 89.035 MB. [2025-12-27T14:36:20.090Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:36:23.032Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:36:25.974Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:36:28.916Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:36:30.281Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:36:32.383Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:36:33.759Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:36:35.948Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:36:35.948Z] 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. [2025-12-27T14:36:36.620Z] The best model improves the baseline by 14.34%. [2025-12-27T14:36:36.620Z] Top recommended movies for user id 72: [2025-12-27T14:36:36.620Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:36:36.620Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:36:36.620Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:36:36.620Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:36:36.620Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:36:36.620Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18956.692 ms) ====== [2025-12-27T14:36:36.620Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T14:36:36.620Z] GC before operation: completed in 242.838 ms, heap usage 242.983 MB -> 89.318 MB. [2025-12-27T14:36:39.630Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:36:42.677Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:36:45.653Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:36:48.653Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:36:50.021Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:36:51.367Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:36:53.562Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:36:55.697Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:36:55.697Z] 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. [2025-12-27T14:36:55.697Z] The best model improves the baseline by 14.34%. [2025-12-27T14:36:55.697Z] Top recommended movies for user id 72: [2025-12-27T14:36:55.697Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:36:55.697Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:36:55.697Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:36:55.697Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:36:55.697Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:36:55.697Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19294.054 ms) ====== [2025-12-27T14:36:55.697Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T14:36:56.372Z] GC before operation: completed in 198.069 ms, heap usage 217.274 MB -> 89.029 MB. [2025-12-27T14:36:59.300Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:37:01.859Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:37:05.755Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:37:07.859Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:37:10.002Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:37:12.225Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:37:13.585Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:37:14.922Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:37:15.574Z] 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. [2025-12-27T14:37:15.574Z] The best model improves the baseline by 14.34%. [2025-12-27T14:37:15.574Z] Top recommended movies for user id 72: [2025-12-27T14:37:15.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:37:15.574Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:37:15.574Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:37:15.574Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:37:15.574Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:37:15.574Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19437.692 ms) ====== [2025-12-27T14:37:15.574Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T14:37:15.574Z] GC before operation: completed in 195.893 ms, heap usage 162.119 MB -> 89.186 MB. [2025-12-27T14:37:18.514Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:37:21.553Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:37:24.531Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:37:27.425Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:37:28.750Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:37:30.105Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:37:32.182Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:37:33.520Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:37:33.520Z] 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. [2025-12-27T14:37:33.520Z] The best model improves the baseline by 14.34%. [2025-12-27T14:37:33.520Z] Top recommended movies for user id 72: [2025-12-27T14:37:33.520Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:37:33.520Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:37:33.520Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:37:33.520Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:37:33.520Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:37:33.520Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17960.721 ms) ====== [2025-12-27T14:37:33.520Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T14:37:34.171Z] GC before operation: completed in 183.403 ms, heap usage 351.859 MB -> 89.641 MB. [2025-12-27T14:37:36.394Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:37:39.302Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:37:42.172Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:37:44.261Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:37:45.588Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:37:46.934Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:37:49.004Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:37:50.343Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:37:50.975Z] 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. [2025-12-27T14:37:50.975Z] The best model improves the baseline by 14.34%. [2025-12-27T14:37:50.975Z] Top recommended movies for user id 72: [2025-12-27T14:37:50.975Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:37:50.975Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:37:50.975Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:37:50.975Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:37:50.975Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:37:50.975Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16946.601 ms) ====== [2025-12-27T14:37:50.975Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T14:37:50.975Z] GC before operation: completed in 176.240 ms, heap usage 305.483 MB -> 89.434 MB. [2025-12-27T14:37:53.904Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:37:56.001Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:37:58.964Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:38:01.196Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:38:03.302Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:38:04.638Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:38:06.698Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:38:08.008Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:38:08.008Z] 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. [2025-12-27T14:38:08.008Z] The best model improves the baseline by 14.34%. [2025-12-27T14:38:08.008Z] Top recommended movies for user id 72: [2025-12-27T14:38:08.008Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:38:08.008Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:38:08.008Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:38:08.008Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:38:08.008Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:38:08.008Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17061.521 ms) ====== [2025-12-27T14:38:08.008Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T14:38:08.645Z] GC before operation: completed in 209.319 ms, heap usage 167.778 MB -> 89.334 MB. [2025-12-27T14:38:12.010Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:38:14.087Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:38:16.992Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:38:19.086Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:38:21.152Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:38:22.484Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:38:23.824Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:38:25.160Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:38:25.787Z] 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. [2025-12-27T14:38:25.787Z] The best model improves the baseline by 14.34%. [2025-12-27T14:38:25.787Z] Top recommended movies for user id 72: [2025-12-27T14:38:25.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:38:25.787Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:38:25.787Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:38:25.787Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:38:25.787Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:38:25.787Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17474.946 ms) ====== [2025-12-27T14:38:25.787Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T14:38:25.787Z] GC before operation: completed in 161.232 ms, heap usage 224.947 MB -> 89.318 MB. [2025-12-27T14:38:28.738Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:38:30.826Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:38:33.742Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:38:36.658Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:38:37.986Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:38:39.315Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:38:40.645Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:38:42.714Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:38:42.714Z] 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. [2025-12-27T14:38:42.714Z] The best model improves the baseline by 14.34%. [2025-12-27T14:38:42.714Z] Top recommended movies for user id 72: [2025-12-27T14:38:42.714Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:38:42.714Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:38:42.714Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:38:42.714Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:38:42.714Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:38:42.714Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16830.494 ms) ====== [2025-12-27T14:38:42.714Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T14:38:42.714Z] GC before operation: completed in 167.931 ms, heap usage 114.897 MB -> 89.163 MB. [2025-12-27T14:38:45.616Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:38:47.692Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:38:50.995Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:38:52.371Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:38:54.447Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:38:55.809Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:38:57.159Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:38:58.507Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:38:58.507Z] 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. [2025-12-27T14:38:58.507Z] The best model improves the baseline by 14.34%. [2025-12-27T14:38:59.185Z] Top recommended movies for user id 72: [2025-12-27T14:38:59.185Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:38:59.185Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:38:59.185Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:38:59.185Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:38:59.185Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:38:59.185Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15912.236 ms) ====== [2025-12-27T14:38:59.185Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T14:38:59.185Z] GC before operation: completed in 184.660 ms, heap usage 236.555 MB -> 89.285 MB. [2025-12-27T14:39:02.122Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:39:04.218Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:39:07.091Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:39:09.152Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:39:10.466Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:39:12.522Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:39:13.835Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:39:15.162Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:39:15.809Z] 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. [2025-12-27T14:39:15.809Z] The best model improves the baseline by 14.34%. [2025-12-27T14:39:15.809Z] Top recommended movies for user id 72: [2025-12-27T14:39:15.809Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:39:15.809Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:39:15.809Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:39:15.809Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:39:15.809Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:39:15.809Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16572.868 ms) ====== [2025-12-27T14:39:15.809Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T14:39:15.809Z] GC before operation: completed in 182.880 ms, heap usage 308.488 MB -> 89.462 MB. [2025-12-27T14:39:17.884Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:39:20.801Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:39:22.856Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:39:26.156Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:39:26.795Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:39:28.136Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:39:30.230Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:39:31.564Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:39:31.564Z] 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. [2025-12-27T14:39:31.564Z] The best model improves the baseline by 14.34%. [2025-12-27T14:39:31.564Z] Top recommended movies for user id 72: [2025-12-27T14:39:31.564Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:39:31.564Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:39:31.564Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:39:31.564Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:39:31.564Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:39:31.564Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15871.860 ms) ====== [2025-12-27T14:39:32.202Z] ----------------------------------- [2025-12-27T14:39:32.202Z] renaissance-movie-lens_0_PASSED [2025-12-27T14:39:32.202Z] ----------------------------------- [2025-12-27T14:39:32.202Z] [2025-12-27T14:39:32.202Z] TEST TEARDOWN: [2025-12-27T14:39:32.202Z] Nothing to be done for teardown. [2025-12-27T14:39:32.202Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 14:39:31 2025 Epoch Time (ms): 1766846371747