[2025-09-03T23:36:43.875Z] Running test renaissance-movie-lens_0 ... [2025-09-03T23:36:43.875Z] =============================================== [2025-09-03T23:36:43.875Z] renaissance-movie-lens_0 Start Time: Wed Sep 3 23:36:43 2025 Epoch Time (ms): 1756942603489 [2025-09-03T23:36:43.875Z] variation: NoOptions [2025-09-03T23:36:43.875Z] JVM_OPTIONS: [2025-09-03T23:36:43.875Z] { \ [2025-09-03T23:36:43.875Z] echo ""; echo "TEST SETUP:"; \ [2025-09-03T23:36:43.876Z] echo "Nothing to be done for setup."; \ [2025-09-03T23:36:43.876Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17569393614509/renaissance-movie-lens_0"; \ [2025-09-03T23:36:43.876Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17569393614509/renaissance-movie-lens_0"; \ [2025-09-03T23:36:43.876Z] echo ""; echo "TESTING:"; \ [2025-09-03T23:36:43.876Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-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_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17569393614509/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-03T23:36:43.876Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17569393614509/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-03T23:36:43.876Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-03T23:36:43.876Z] echo "Nothing to be done for teardown."; \ [2025-09-03T23:36:43.876Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17569393614509/TestTargetResult"; [2025-09-03T23:36:43.876Z] [2025-09-03T23:36:43.876Z] TEST SETUP: [2025-09-03T23:36:43.876Z] Nothing to be done for setup. [2025-09-03T23:36:43.876Z] [2025-09-03T23:36:43.876Z] TESTING: [2025-09-03T23:36:55.406Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-03T23:37:13.879Z] 23:37:12.858 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-09-03T23:37:18.076Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-03T23:37:18.076Z] Training: 60056, validation: 20285, test: 19854 [2025-09-03T23:37:18.076Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-03T23:37:19.036Z] GC before operation: completed in 240.659 ms, heap usage 389.055 MB -> 75.943 MB. [2025-09-03T23:37:32.781Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:37:40.981Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:37:48.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:37:55.378Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:37:58.417Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:38:02.582Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:38:05.612Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:38:08.640Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:38:08.640Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:38:08.640Z] The best model improves the baseline by 14.52%. [2025-09-03T23:38:09.602Z] Top recommended movies for user id 72: [2025-09-03T23:38:09.602Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:38:09.603Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:38:09.603Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:38:09.603Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:38:09.603Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:38:09.603Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (50943.112 ms) ====== [2025-09-03T23:38:09.603Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-03T23:38:09.603Z] GC before operation: completed in 271.442 ms, heap usage 213.615 MB -> 86.382 MB. [2025-09-03T23:38:16.327Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:38:21.740Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:38:27.210Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:38:32.621Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:38:36.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:38:39.837Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:38:42.877Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:38:45.978Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:38:46.949Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:38:46.949Z] The best model improves the baseline by 14.52%. [2025-09-03T23:38:46.949Z] Top recommended movies for user id 72: [2025-09-03T23:38:46.949Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:38:46.949Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:38:46.949Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:38:46.949Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:38:46.949Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:38:46.949Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (37273.622 ms) ====== [2025-09-03T23:38:46.949Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-03T23:38:47.910Z] GC before operation: completed in 315.878 ms, heap usage 271.920 MB -> 88.678 MB. [2025-09-03T23:38:52.783Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:38:59.539Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:39:04.950Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:39:10.352Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:39:12.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:39:15.371Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:39:18.402Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:39:21.440Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:39:22.396Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:39:22.396Z] The best model improves the baseline by 14.52%. [2025-09-03T23:39:22.396Z] Top recommended movies for user id 72: [2025-09-03T23:39:22.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:39:22.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:39:22.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:39:22.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:39:22.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:39:22.396Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (35204.807 ms) ====== [2025-09-03T23:39:22.396Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-03T23:39:23.362Z] GC before operation: completed in 257.656 ms, heap usage 119.883 MB -> 89.064 MB. [2025-09-03T23:39:28.766Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:39:32.946Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:39:37.123Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:39:42.108Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:39:46.286Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:39:49.331Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:39:52.385Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:39:55.433Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:39:56.386Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:39:56.386Z] The best model improves the baseline by 14.52%. [2025-09-03T23:39:56.386Z] Top recommended movies for user id 72: [2025-09-03T23:39:56.386Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:39:56.386Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:39:56.386Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:39:56.386Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:39:56.386Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:39:56.386Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (33658.545 ms) ====== [2025-09-03T23:39:56.386Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-03T23:39:56.386Z] GC before operation: completed in 212.796 ms, heap usage 202.807 MB -> 89.582 MB. [2025-09-03T23:40:01.794Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:40:07.193Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:40:13.990Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:40:18.168Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:40:20.140Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:40:23.226Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:40:25.201Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:40:28.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:40:28.240Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:40:28.240Z] The best model improves the baseline by 14.52%. [2025-09-03T23:40:28.240Z] Top recommended movies for user id 72: [2025-09-03T23:40:28.240Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:40:28.240Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:40:28.240Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:40:28.240Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:40:28.240Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:40:28.240Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (31790.982 ms) ====== [2025-09-03T23:40:28.240Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-03T23:40:29.198Z] GC before operation: completed in 230.514 ms, heap usage 297.312 MB -> 89.599 MB. [2025-09-03T23:40:33.383Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:40:37.553Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:40:40.586Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:40:45.210Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:40:47.178Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:40:49.153Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:40:52.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:40:54.151Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:40:55.110Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:40:55.110Z] The best model improves the baseline by 14.52%. [2025-09-03T23:40:55.110Z] Top recommended movies for user id 72: [2025-09-03T23:40:55.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:40:55.110Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:40:55.110Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:40:55.110Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:40:55.110Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:40:55.110Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (26142.323 ms) ====== [2025-09-03T23:40:55.110Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-03T23:40:55.110Z] GC before operation: completed in 212.394 ms, heap usage 146.658 MB -> 90.628 MB. [2025-09-03T23:40:59.280Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:41:03.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:41:07.648Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:41:11.961Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:41:14.988Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:41:16.954Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:41:19.980Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:41:21.945Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:41:21.945Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:41:21.945Z] The best model improves the baseline by 14.52%. [2025-09-03T23:41:22.903Z] Top recommended movies for user id 72: [2025-09-03T23:41:22.903Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:41:22.903Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:41:22.903Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:41:22.903Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:41:22.903Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:41:22.903Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (27461.201 ms) ====== [2025-09-03T23:41:22.903Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-03T23:41:22.903Z] GC before operation: completed in 206.592 ms, heap usage 119.001 MB -> 89.610 MB. [2025-09-03T23:41:27.126Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:41:30.867Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:41:35.058Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:41:39.243Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:41:41.215Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:41:44.247Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:41:46.217Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:41:49.254Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:41:49.254Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:41:49.254Z] The best model improves the baseline by 14.52%. [2025-09-03T23:41:49.254Z] Top recommended movies for user id 72: [2025-09-03T23:41:49.254Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:41:49.254Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:41:49.254Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:41:49.254Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:41:49.254Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:41:49.254Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (26811.488 ms) ====== [2025-09-03T23:41:49.254Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-03T23:41:50.213Z] GC before operation: completed in 210.935 ms, heap usage 288.765 MB -> 90.167 MB. [2025-09-03T23:41:54.419Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:41:58.591Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:42:02.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:42:05.790Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:42:08.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:42:10.781Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:42:12.743Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:42:15.776Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:42:16.735Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:42:16.735Z] The best model improves the baseline by 14.52%. [2025-09-03T23:42:16.735Z] Top recommended movies for user id 72: [2025-09-03T23:42:16.735Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:42:16.735Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:42:16.735Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:42:16.735Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:42:16.735Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:42:16.735Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (27293.709 ms) ====== [2025-09-03T23:42:16.735Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-03T23:42:17.698Z] GC before operation: completed in 258.332 ms, heap usage 240.126 MB -> 89.837 MB. [2025-09-03T23:42:23.127Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:42:28.210Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:42:32.375Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:42:35.402Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:42:38.431Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:42:40.395Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:42:42.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:42:45.406Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:42:46.366Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:42:46.366Z] The best model improves the baseline by 14.52%. [2025-09-03T23:42:46.366Z] Top recommended movies for user id 72: [2025-09-03T23:42:46.366Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:42:46.366Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:42:46.366Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:42:46.366Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:42:46.366Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:42:46.366Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (28996.465 ms) ====== [2025-09-03T23:42:46.366Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-03T23:42:46.366Z] GC before operation: completed in 217.059 ms, heap usage 169.849 MB -> 90.015 MB. [2025-09-03T23:42:51.801Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:42:57.405Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:43:01.659Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:43:05.840Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:43:08.880Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:43:10.866Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:43:13.896Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:43:15.868Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:43:15.868Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:43:15.868Z] The best model improves the baseline by 14.52%. [2025-09-03T23:43:15.868Z] Top recommended movies for user id 72: [2025-09-03T23:43:15.868Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:43:15.868Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:43:15.868Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:43:15.868Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:43:15.868Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:43:15.868Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (29518.255 ms) ====== [2025-09-03T23:43:15.868Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-03T23:43:16.826Z] GC before operation: completed in 254.271 ms, heap usage 372.153 MB -> 90.001 MB. [2025-09-03T23:43:19.862Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:43:24.464Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:43:28.635Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:43:31.662Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:43:34.685Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:43:36.659Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:43:39.710Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:43:42.749Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:43:42.749Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:43:42.749Z] The best model improves the baseline by 14.52%. [2025-09-03T23:43:42.749Z] Top recommended movies for user id 72: [2025-09-03T23:43:42.749Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:43:42.749Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:43:42.749Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:43:42.749Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:43:42.749Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:43:42.749Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (26799.618 ms) ====== [2025-09-03T23:43:42.749Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-03T23:43:43.705Z] GC before operation: completed in 244.683 ms, heap usage 178.983 MB -> 90.031 MB. [2025-09-03T23:43:49.148Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:43:54.592Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:44:01.453Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:44:06.887Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:44:11.086Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:44:15.301Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:44:19.056Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:44:23.283Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:44:23.283Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:44:23.283Z] The best model improves the baseline by 14.52%. [2025-09-03T23:44:24.248Z] Top recommended movies for user id 72: [2025-09-03T23:44:24.248Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:44:24.248Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:44:24.248Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:44:24.248Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:44:24.248Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:44:24.248Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (40776.128 ms) ====== [2025-09-03T23:44:24.248Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-03T23:44:24.248Z] GC before operation: completed in 339.646 ms, heap usage 278.118 MB -> 90.223 MB. [2025-09-03T23:44:32.501Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:44:37.942Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:44:44.741Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:44:50.199Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:44:54.409Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:44:58.607Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:45:01.676Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:45:05.900Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:45:05.900Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:45:06.866Z] The best model improves the baseline by 14.52%. [2025-09-03T23:45:06.866Z] Top recommended movies for user id 72: [2025-09-03T23:45:06.866Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:45:06.866Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:45:06.866Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:45:06.866Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:45:06.866Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:45:06.866Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42191.739 ms) ====== [2025-09-03T23:45:06.866Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-03T23:45:06.866Z] GC before operation: completed in 311.508 ms, heap usage 172.288 MB -> 89.890 MB. [2025-09-03T23:45:13.647Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:45:19.837Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:45:26.620Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:45:32.058Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:45:36.257Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:45:40.463Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:45:43.516Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:45:47.719Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:45:47.719Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:45:48.695Z] The best model improves the baseline by 14.52%. [2025-09-03T23:45:48.695Z] Top recommended movies for user id 72: [2025-09-03T23:45:48.695Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:45:48.695Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:45:48.695Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:45:48.695Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:45:48.695Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:45:48.695Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (41409.996 ms) ====== [2025-09-03T23:45:48.695Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-03T23:45:48.695Z] GC before operation: completed in 332.433 ms, heap usage 430.262 MB -> 90.384 MB. [2025-09-03T23:45:55.526Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:46:02.279Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:46:07.720Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:46:13.401Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:46:16.475Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:46:19.525Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:46:22.585Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:46:26.840Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:46:26.840Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:46:26.840Z] The best model improves the baseline by 14.52%. [2025-09-03T23:46:27.810Z] Top recommended movies for user id 72: [2025-09-03T23:46:27.810Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:46:27.810Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:46:27.810Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:46:27.810Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:46:27.810Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:46:27.810Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38583.457 ms) ====== [2025-09-03T23:46:27.810Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-03T23:46:27.810Z] GC before operation: completed in 315.616 ms, heap usage 364.710 MB -> 90.354 MB. [2025-09-03T23:46:34.552Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:46:40.001Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:46:45.522Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:46:52.302Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:46:56.494Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:46:59.583Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:47:03.792Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:47:08.014Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:47:09.692Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:47:09.692Z] The best model improves the baseline by 14.52%. [2025-09-03T23:47:09.692Z] Top recommended movies for user id 72: [2025-09-03T23:47:09.692Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:47:09.692Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:47:09.692Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:47:09.692Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:47:09.692Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:47:09.693Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (41419.898 ms) ====== [2025-09-03T23:47:09.693Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-03T23:47:09.693Z] GC before operation: completed in 409.396 ms, heap usage 122.579 MB -> 90.024 MB. [2025-09-03T23:47:16.466Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:47:21.965Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:47:27.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:47:32.849Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:47:37.076Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:47:40.141Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:47:43.206Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:47:47.415Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:47:47.415Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:47:47.415Z] The best model improves the baseline by 14.52%. [2025-09-03T23:47:47.415Z] Top recommended movies for user id 72: [2025-09-03T23:47:47.415Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:47:47.415Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:47:47.415Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:47:47.415Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:47:47.415Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:47:47.415Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (38232.397 ms) ====== [2025-09-03T23:47:47.415Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-03T23:47:48.392Z] GC before operation: completed in 348.689 ms, heap usage 262.168 MB -> 90.022 MB. [2025-09-03T23:47:53.821Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:48:00.760Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:48:06.721Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:48:11.100Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:48:15.299Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:48:19.499Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:48:22.584Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:48:25.665Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:48:26.632Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:48:26.632Z] The best model improves the baseline by 14.52%. [2025-09-03T23:48:26.632Z] Top recommended movies for user id 72: [2025-09-03T23:48:26.632Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:48:26.632Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:48:26.632Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:48:26.632Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:48:26.632Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:48:26.632Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (38959.833 ms) ====== [2025-09-03T23:48:26.632Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-03T23:48:27.594Z] GC before operation: completed in 314.126 ms, heap usage 121.838 MB -> 90.043 MB. [2025-09-03T23:48:33.077Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T23:48:39.838Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T23:48:45.275Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T23:48:52.064Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T23:48:55.136Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T23:48:59.352Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T23:49:04.265Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T23:49:06.237Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T23:49:07.212Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T23:49:07.213Z] The best model improves the baseline by 14.52%. [2025-09-03T23:49:07.213Z] Top recommended movies for user id 72: [2025-09-03T23:49:07.213Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T23:49:07.213Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T23:49:07.213Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T23:49:07.213Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T23:49:07.213Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T23:49:07.213Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (39845.300 ms) ====== [2025-09-03T23:49:09.188Z] ----------------------------------- [2025-09-03T23:49:09.188Z] renaissance-movie-lens_0_PASSED [2025-09-03T23:49:09.188Z] ----------------------------------- [2025-09-03T23:49:09.188Z] [2025-09-03T23:49:09.188Z] TEST TEARDOWN: [2025-09-03T23:49:09.188Z] Nothing to be done for teardown. [2025-09-03T23:49:09.188Z] renaissance-movie-lens_0 Finish Time: Wed Sep 3 23:49:08 2025 Epoch Time (ms): 1756943348861