[2025-09-25T03:10:04.639Z] Running test renaissance-movie-lens_0 ... [2025-09-25T03:10:04.639Z] =============================================== [2025-09-25T03:10:04.639Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 03:10:03 2025 Epoch Time (ms): 1758769803825 [2025-09-25T03:10:04.639Z] variation: NoOptions [2025-09-25T03:10:04.639Z] JVM_OPTIONS: [2025-09-25T03:10:04.639Z] { \ [2025-09-25T03:10:04.639Z] echo ""; echo "TEST SETUP:"; \ [2025-09-25T03:10:04.639Z] echo "Nothing to be done for setup."; \ [2025-09-25T03:10:04.639Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17587673591287/renaissance-movie-lens_0"; \ [2025-09-25T03:10:04.639Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17587673591287/renaissance-movie-lens_0"; \ [2025-09-25T03:10:04.639Z] echo ""; echo "TESTING:"; \ [2025-09-25T03:10:04.639Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_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_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17587673591287/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-25T03:10:04.639Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17587673591287/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-25T03:10:04.639Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-25T03:10:04.639Z] echo "Nothing to be done for teardown."; \ [2025-09-25T03:10:04.639Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17587673591287/TestTargetResult"; [2025-09-25T03:10:04.639Z] [2025-09-25T03:10:04.639Z] TEST SETUP: [2025-09-25T03:10:04.639Z] Nothing to be done for setup. [2025-09-25T03:10:04.639Z] [2025-09-25T03:10:04.639Z] TESTING: [2025-09-25T03:10:14.249Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-25T03:10:30.588Z] 03:10:29.506 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-09-25T03:10:37.302Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-25T03:10:38.836Z] Training: 60056, validation: 20285, test: 19854 [2025-09-25T03:10:38.836Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-25T03:10:38.836Z] GC before operation: completed in 241.786 ms, heap usage 273.574 MB -> 75.955 MB. [2025-09-25T03:10:57.413Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:11:08.822Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:11:16.922Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:11:24.991Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:11:29.311Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:11:33.620Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:11:37.919Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:11:41.229Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:11:41.967Z] 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. [2025-09-25T03:11:41.967Z] The best model improves the baseline by 14.52%. [2025-09-25T03:11:42.715Z] Top recommended movies for user id 72: [2025-09-25T03:11:42.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:11:42.715Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:11:42.715Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:11:42.715Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:11:42.715Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:11:42.715Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (63232.148 ms) ====== [2025-09-25T03:11:42.715Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-25T03:11:42.715Z] GC before operation: completed in 233.325 ms, heap usage 471.506 MB -> 90.672 MB. [2025-09-25T03:11:49.386Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:11:56.075Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:12:02.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:12:08.128Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:12:11.623Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:12:14.939Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:12:19.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:12:22.535Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:12:22.535Z] 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. [2025-09-25T03:12:22.535Z] The best model improves the baseline by 14.52%. [2025-09-25T03:12:23.283Z] Top recommended movies for user id 72: [2025-09-25T03:12:23.283Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:12:23.283Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:12:23.283Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:12:23.283Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:12:23.283Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:12:23.283Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (40729.775 ms) ====== [2025-09-25T03:12:23.283Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-25T03:12:23.283Z] GC before operation: completed in 257.979 ms, heap usage 180.980 MB -> 92.468 MB. [2025-09-25T03:12:29.941Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:12:35.376Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:12:42.019Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:12:46.328Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:12:49.737Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:12:53.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:12:56.328Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:12:59.236Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:12:59.978Z] 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. [2025-09-25T03:12:59.978Z] The best model improves the baseline by 14.52%. [2025-09-25T03:12:59.978Z] Top recommended movies for user id 72: [2025-09-25T03:12:59.978Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:12:59.978Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:12:59.979Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:12:59.979Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:12:59.979Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:12:59.979Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (36631.934 ms) ====== [2025-09-25T03:12:59.979Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-25T03:13:00.719Z] GC before operation: completed in 221.082 ms, heap usage 243.195 MB -> 95.148 MB. [2025-09-25T03:13:06.121Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:13:11.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:13:18.198Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:13:22.492Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:13:25.795Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:13:29.166Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:13:31.536Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:13:34.837Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:13:34.837Z] 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. [2025-09-25T03:13:34.837Z] The best model improves the baseline by 14.52%. [2025-09-25T03:13:35.573Z] Top recommended movies for user id 72: [2025-09-25T03:13:35.573Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:13:35.573Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:13:35.573Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:13:35.573Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:13:35.573Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:13:35.573Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (35025.382 ms) ====== [2025-09-25T03:13:35.573Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-25T03:13:35.573Z] GC before operation: completed in 231.927 ms, heap usage 134.913 MB -> 94.341 MB. [2025-09-25T03:13:40.974Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:13:46.371Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:13:51.166Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:13:56.566Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:13:58.945Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:14:02.225Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:14:05.508Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:14:07.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:14:08.671Z] 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. [2025-09-25T03:14:08.671Z] The best model improves the baseline by 14.52%. [2025-09-25T03:14:09.410Z] Top recommended movies for user id 72: [2025-09-25T03:14:09.410Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:14:09.410Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:14:09.410Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:14:09.410Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:14:09.410Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:14:09.410Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (33395.188 ms) ====== [2025-09-25T03:14:09.410Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-25T03:14:09.410Z] GC before operation: completed in 222.847 ms, heap usage 507.225 MB -> 92.489 MB. [2025-09-25T03:14:14.821Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:14:19.106Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:14:24.501Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:14:28.914Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:14:32.452Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:14:34.828Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:14:38.142Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:14:40.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:14:41.254Z] 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. [2025-09-25T03:14:41.254Z] The best model improves the baseline by 14.52%. [2025-09-25T03:14:41.992Z] Top recommended movies for user id 72: [2025-09-25T03:14:41.992Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:14:41.992Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:14:41.992Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:14:41.992Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:14:41.992Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:14:41.992Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (32350.626 ms) ====== [2025-09-25T03:14:41.992Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-25T03:14:41.992Z] GC before operation: completed in 223.418 ms, heap usage 545.562 MB -> 93.724 MB. [2025-09-25T03:14:47.398Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:14:52.807Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:14:57.103Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:15:02.497Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:15:04.874Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:15:07.324Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:15:10.610Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:15:12.986Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:15:13.723Z] 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. [2025-09-25T03:15:13.723Z] The best model improves the baseline by 14.52%. [2025-09-25T03:15:13.723Z] Top recommended movies for user id 72: [2025-09-25T03:15:13.723Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:15:13.723Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:15:13.723Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:15:13.723Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:15:13.723Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:15:13.723Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (31951.554 ms) ====== [2025-09-25T03:15:13.723Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-25T03:15:13.723Z] GC before operation: completed in 224.293 ms, heap usage 606.452 MB -> 93.748 MB. [2025-09-25T03:15:19.578Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:15:24.977Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:15:30.372Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:15:34.678Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:15:38.142Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:15:42.417Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:15:46.771Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:15:49.157Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:15:49.896Z] 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. [2025-09-25T03:15:49.896Z] The best model improves the baseline by 14.52%. [2025-09-25T03:15:49.896Z] Top recommended movies for user id 72: [2025-09-25T03:15:49.896Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:15:49.896Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:15:49.897Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:15:49.897Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:15:49.897Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:15:49.897Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (35996.483 ms) ====== [2025-09-25T03:15:49.897Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-25T03:15:50.641Z] GC before operation: completed in 250.706 ms, heap usage 504.413 MB -> 92.881 MB. [2025-09-25T03:15:57.287Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:16:02.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:16:07.069Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:16:12.463Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:16:14.844Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:16:18.135Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:16:20.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:16:23.813Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:16:23.813Z] 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. [2025-09-25T03:16:23.813Z] The best model improves the baseline by 14.52%. [2025-09-25T03:16:24.554Z] Top recommended movies for user id 72: [2025-09-25T03:16:24.554Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:16:24.554Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:16:24.554Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:16:24.554Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:16:24.554Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:16:24.554Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (34251.610 ms) ====== [2025-09-25T03:16:24.554Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-25T03:16:24.554Z] GC before operation: completed in 235.003 ms, heap usage 175.664 MB -> 93.645 MB. [2025-09-25T03:16:29.968Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:16:35.360Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:16:39.679Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:16:45.085Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:16:47.828Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:16:50.190Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:16:53.525Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:16:56.819Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:16:56.819Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-25T03:16:56.819Z] The best model improves the baseline by 14.52%. [2025-09-25T03:16:57.570Z] Top recommended movies for user id 72: [2025-09-25T03:16:57.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:16:57.570Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:16:57.570Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:16:57.570Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:16:57.570Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:16:57.570Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (32409.410 ms) ====== [2025-09-25T03:16:57.570Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-25T03:16:57.570Z] GC before operation: completed in 317.211 ms, heap usage 214.956 MB -> 90.212 MB. [2025-09-25T03:17:02.965Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:17:08.392Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:17:13.831Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:17:19.232Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:17:22.554Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:17:25.828Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:17:29.120Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:17:32.890Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:17:33.635Z] 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. [2025-09-25T03:17:33.635Z] The best model improves the baseline by 14.52%. [2025-09-25T03:17:33.635Z] Top recommended movies for user id 72: [2025-09-25T03:17:33.635Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:17:33.635Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:17:33.635Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:17:33.635Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:17:33.635Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:17:33.635Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (35773.813 ms) ====== [2025-09-25T03:17:33.635Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-25T03:17:33.635Z] GC before operation: completed in 261.247 ms, heap usage 124.761 MB -> 91.593 MB. [2025-09-25T03:17:39.031Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:17:44.466Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:17:49.995Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:17:54.308Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:17:57.591Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:18:00.884Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:18:03.248Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:18:06.537Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:18:06.537Z] 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. [2025-09-25T03:18:06.537Z] The best model improves the baseline by 14.52%. [2025-09-25T03:18:07.275Z] Top recommended movies for user id 72: [2025-09-25T03:18:07.275Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:18:07.275Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:18:07.275Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:18:07.275Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:18:07.275Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:18:07.275Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (33593.567 ms) ====== [2025-09-25T03:18:07.275Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-25T03:18:07.275Z] GC before operation: completed in 214.546 ms, heap usage 260.810 MB -> 90.318 MB. [2025-09-25T03:18:12.701Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:18:18.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:18:22.871Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:18:28.274Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:18:31.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:18:33.924Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:18:37.198Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:18:40.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:18:41.212Z] 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. [2025-09-25T03:18:41.212Z] The best model improves the baseline by 14.52%. [2025-09-25T03:18:41.212Z] Top recommended movies for user id 72: [2025-09-25T03:18:41.212Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:18:41.212Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:18:41.212Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:18:41.212Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:18:41.212Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:18:41.212Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (33986.405 ms) ====== [2025-09-25T03:18:41.212Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-25T03:18:41.944Z] GC before operation: completed in 244.986 ms, heap usage 492.759 MB -> 90.720 MB. [2025-09-25T03:18:47.346Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:18:51.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:18:57.070Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:19:01.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:19:05.145Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:19:08.421Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:19:11.711Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:19:15.024Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:19:15.024Z] 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. [2025-09-25T03:19:15.024Z] The best model improves the baseline by 14.52%. [2025-09-25T03:19:15.763Z] Top recommended movies for user id 72: [2025-09-25T03:19:15.763Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:19:15.763Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:19:15.763Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:19:15.763Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:19:15.763Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:19:15.763Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (33914.828 ms) ====== [2025-09-25T03:19:15.763Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-25T03:19:15.763Z] GC before operation: completed in 262.618 ms, heap usage 203.800 MB -> 90.125 MB. [2025-09-25T03:19:22.402Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:19:30.509Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:19:35.939Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:19:41.334Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:19:44.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:19:47.968Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:19:50.813Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:19:53.199Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:19:53.935Z] 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. [2025-09-25T03:19:53.935Z] The best model improves the baseline by 14.52%. [2025-09-25T03:19:53.935Z] Top recommended movies for user id 72: [2025-09-25T03:19:53.935Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:19:53.935Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:19:53.935Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:19:53.935Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:19:53.935Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:19:53.935Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (38413.853 ms) ====== [2025-09-25T03:19:53.935Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-25T03:19:54.667Z] GC before operation: completed in 304.226 ms, heap usage 192.759 MB -> 90.353 MB. [2025-09-25T03:20:00.072Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:20:04.361Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:20:10.985Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:20:15.263Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:20:18.536Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:20:20.898Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:20:24.273Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:20:26.650Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:20:27.391Z] 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. [2025-09-25T03:20:27.391Z] The best model improves the baseline by 14.52%. [2025-09-25T03:20:27.391Z] Top recommended movies for user id 72: [2025-09-25T03:20:27.391Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:20:27.391Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:20:27.392Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:20:27.392Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:20:27.392Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:20:27.392Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (33163.313 ms) ====== [2025-09-25T03:20:27.392Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-25T03:20:28.124Z] GC before operation: completed in 240.475 ms, heap usage 200.795 MB -> 90.181 MB. [2025-09-25T03:20:34.775Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:20:41.888Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:20:48.519Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:20:53.948Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:20:57.239Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:21:00.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:21:03.893Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:21:06.270Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:21:07.000Z] 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. [2025-09-25T03:21:07.000Z] The best model improves the baseline by 14.52%. [2025-09-25T03:21:07.000Z] Top recommended movies for user id 72: [2025-09-25T03:21:07.000Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:21:07.000Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:21:07.000Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:21:07.000Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:21:07.000Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:21:07.000Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (39188.314 ms) ====== [2025-09-25T03:21:07.000Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-25T03:21:07.740Z] GC before operation: completed in 316.921 ms, heap usage 548.561 MB -> 94.054 MB. [2025-09-25T03:21:13.146Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:21:17.455Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:21:22.868Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:21:27.650Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:21:30.969Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:21:33.357Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:21:36.640Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:21:39.018Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:21:39.754Z] 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. [2025-09-25T03:21:39.754Z] The best model improves the baseline by 14.52%. [2025-09-25T03:21:40.484Z] Top recommended movies for user id 72: [2025-09-25T03:21:40.484Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:21:40.484Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:21:40.484Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:21:40.484Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:21:40.484Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:21:40.484Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (32735.966 ms) ====== [2025-09-25T03:21:40.484Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-25T03:21:40.484Z] GC before operation: completed in 204.206 ms, heap usage 188.469 MB -> 95.766 MB. [2025-09-25T03:21:44.775Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:21:48.083Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:21:52.375Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:21:55.670Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:21:58.058Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:22:01.356Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:22:03.720Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:22:07.002Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:22:07.861Z] 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. [2025-09-25T03:22:07.861Z] The best model improves the baseline by 14.52%. [2025-09-25T03:22:07.861Z] Top recommended movies for user id 72: [2025-09-25T03:22:07.861Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:22:07.861Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:22:07.861Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:22:07.861Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:22:07.861Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:22:07.861Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27442.813 ms) ====== [2025-09-25T03:22:07.861Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-25T03:22:07.861Z] GC before operation: completed in 229.637 ms, heap usage 510.877 MB -> 93.860 MB. [2025-09-25T03:22:12.643Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T03:22:18.041Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T03:22:23.415Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T03:22:27.712Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T03:22:30.110Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T03:22:33.386Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T03:22:36.670Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T03:22:39.040Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T03:22:39.780Z] 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. [2025-09-25T03:22:39.780Z] The best model improves the baseline by 14.52%. [2025-09-25T03:22:39.780Z] Top recommended movies for user id 72: [2025-09-25T03:22:39.780Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T03:22:39.780Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T03:22:39.780Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T03:22:39.780Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T03:22:39.780Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T03:22:39.780Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (32084.722 ms) ====== [2025-09-25T03:22:41.291Z] ----------------------------------- [2025-09-25T03:22:41.291Z] renaissance-movie-lens_0_PASSED [2025-09-25T03:22:41.291Z] ----------------------------------- [2025-09-25T03:22:41.291Z] [2025-09-25T03:22:41.291Z] TEST TEARDOWN: [2025-09-25T03:22:41.291Z] Nothing to be done for teardown. [2025-09-25T03:22:41.291Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 03:22:40 2025 Epoch Time (ms): 1758770560699