[2025-12-05T12:48:40.913Z] Running test renaissance-movie-lens_0 ... [2025-12-05T12:48:40.913Z] =============================================== [2025-12-05T12:48:40.913Z] renaissance-movie-lens_0 Start Time: Fri Dec 5 04:48:36 2025 Epoch Time (ms): 1764938916995 [2025-12-05T12:48:40.913Z] variation: NoOptions [2025-12-05T12:48:40.913Z] JVM_OPTIONS: [2025-12-05T12:48:40.913Z] { \ [2025-12-05T12:48:40.913Z] echo ""; echo "TEST SETUP:"; \ [2025-12-05T12:48:40.913Z] echo "Nothing to be done for setup."; \ [2025-12-05T12:48:40.913Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17649375796456/renaissance-movie-lens_0"; \ [2025-12-05T12:48:40.913Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17649375796456/renaissance-movie-lens_0"; \ [2025-12-05T12:48:40.913Z] echo ""; echo "TESTING:"; \ [2025-12-05T12:48:40.913Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17649375796456/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-05T12:48:40.913Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17649375796456/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-05T12:48:40.913Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-05T12:48:40.913Z] echo "Nothing to be done for teardown."; \ [2025-12-05T12:48:40.913Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17649375796456/TestTargetResult"; [2025-12-05T12:48:40.913Z] [2025-12-05T12:48:40.913Z] TEST SETUP: [2025-12-05T12:48:40.913Z] Nothing to be done for setup. [2025-12-05T12:48:40.913Z] [2025-12-05T12:48:40.913Z] TESTING: [2025-12-05T12:48:45.935Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-05T12:48:51.056Z] 04:48:47.676 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. [2025-12-05T12:48:53.036Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-05T12:48:53.933Z] Training: 60056, validation: 20285, test: 19854 [2025-12-05T12:48:53.933Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-05T12:48:53.933Z] GC before operation: completed in 105.195 ms, heap usage 301.502 MB -> 74.591 MB. [2025-12-05T12:48:59.363Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:49:03.740Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:49:07.191Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:49:10.464Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:49:11.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:49:13.712Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:49:15.578Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:49:17.494Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:49:17.880Z] 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. [2025-12-05T12:49:17.880Z] The best model improves the baseline by 14.52%. [2025-12-05T12:49:17.880Z] Top recommended movies for user id 72: [2025-12-05T12:49:17.880Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:49:17.880Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:49:17.880Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:49:17.880Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:49:17.880Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:49:17.880Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24102.971 ms) ====== [2025-12-05T12:49:17.880Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-05T12:49:17.880Z] GC before operation: completed in 117.299 ms, heap usage 325.945 MB -> 87.057 MB. [2025-12-05T12:49:21.176Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:49:24.594Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:49:27.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:49:31.140Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:49:32.439Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:49:35.020Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:49:36.377Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:49:38.902Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:49:38.902Z] 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. [2025-12-05T12:49:38.902Z] The best model improves the baseline by 14.52%. [2025-12-05T12:49:39.290Z] Top recommended movies for user id 72: [2025-12-05T12:49:39.290Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:49:39.290Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:49:39.290Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:49:39.290Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:49:39.290Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:49:39.290Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21051.873 ms) ====== [2025-12-05T12:49:39.290Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-05T12:49:39.290Z] GC before operation: completed in 107.245 ms, heap usage 322.121 MB -> 87.856 MB. [2025-12-05T12:49:42.550Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:49:45.803Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:49:48.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:49:51.669Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:49:53.552Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:49:55.432Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:49:57.291Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:49:58.608Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:49:58.990Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-05T12:49:58.990Z] The best model improves the baseline by 14.52%. [2025-12-05T12:49:58.990Z] Top recommended movies for user id 72: [2025-12-05T12:49:58.990Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:49:58.990Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:49:58.990Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:49:58.990Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:49:58.990Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:49:58.990Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19816.910 ms) ====== [2025-12-05T12:49:58.990Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-05T12:49:58.990Z] GC before operation: completed in 107.467 ms, heap usage 438.207 MB -> 88.590 MB. [2025-12-05T12:50:02.317Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:50:06.616Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:50:09.138Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:50:12.527Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:50:15.039Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:50:17.627Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:50:19.530Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:50:22.130Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:50:22.130Z] 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. [2025-12-05T12:50:22.130Z] The best model improves the baseline by 14.52%. [2025-12-05T12:50:22.130Z] Top recommended movies for user id 72: [2025-12-05T12:50:22.130Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:50:22.130Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:50:22.130Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:50:22.130Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:50:22.130Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:50:22.130Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23055.451 ms) ====== [2025-12-05T12:50:22.130Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-05T12:50:22.130Z] GC before operation: completed in 111.922 ms, heap usage 518.063 MB -> 88.995 MB. [2025-12-05T12:50:25.415Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:50:29.684Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:50:33.008Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:50:37.164Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:50:39.712Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:50:41.531Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:50:44.031Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:50:45.876Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:50:46.263Z] 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. [2025-12-05T12:50:46.263Z] The best model improves the baseline by 14.52%. [2025-12-05T12:50:46.263Z] Top recommended movies for user id 72: [2025-12-05T12:50:46.263Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:50:46.263Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:50:46.263Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:50:46.263Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:50:46.263Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:50:46.263Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24022.146 ms) ====== [2025-12-05T12:50:46.263Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-05T12:50:46.263Z] GC before operation: completed in 97.172 ms, heap usage 424.803 MB -> 88.777 MB. [2025-12-05T12:50:50.470Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:50:54.621Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:50:56.440Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:50:59.733Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:51:01.136Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:51:03.049Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:51:04.949Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:51:06.905Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:51:06.905Z] 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. [2025-12-05T12:51:06.905Z] The best model improves the baseline by 14.52%. [2025-12-05T12:51:06.905Z] Top recommended movies for user id 72: [2025-12-05T12:51:06.905Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:51:06.906Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:51:06.906Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:51:06.906Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:51:06.906Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:51:06.906Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20483.290 ms) ====== [2025-12-05T12:51:06.906Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-05T12:51:06.906Z] GC before operation: completed in 113.260 ms, heap usage 353.114 MB -> 89.023 MB. [2025-12-05T12:51:11.055Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:51:13.049Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:51:16.266Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:51:18.817Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:51:20.092Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:51:22.592Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:51:23.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:51:25.938Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:51:25.938Z] 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. [2025-12-05T12:51:25.938Z] The best model improves the baseline by 14.52%. [2025-12-05T12:51:25.938Z] Top recommended movies for user id 72: [2025-12-05T12:51:25.938Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:51:25.938Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:51:25.938Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:51:25.938Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:51:25.938Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:51:25.938Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18847.629 ms) ====== [2025-12-05T12:51:25.938Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-05T12:51:25.939Z] GC before operation: completed in 97.188 ms, heap usage 534.916 MB -> 89.232 MB. [2025-12-05T12:51:28.415Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:51:31.676Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:51:34.134Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:51:38.390Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:51:40.326Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:51:42.156Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:51:43.987Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:51:46.509Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:51:46.961Z] 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. [2025-12-05T12:51:46.961Z] The best model improves the baseline by 14.52%. [2025-12-05T12:51:47.355Z] Top recommended movies for user id 72: [2025-12-05T12:51:47.355Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:51:47.355Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:51:47.355Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:51:47.355Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:51:47.355Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:51:47.355Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21246.162 ms) ====== [2025-12-05T12:51:47.355Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-05T12:51:47.355Z] GC before operation: completed in 122.591 ms, heap usage 362.448 MB -> 89.177 MB. [2025-12-05T12:51:50.605Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:51:54.781Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:51:58.895Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:52:02.107Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:52:04.663Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:52:05.991Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:52:07.920Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:52:10.477Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:52:10.845Z] 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. [2025-12-05T12:52:10.845Z] The best model improves the baseline by 14.52%. [2025-12-05T12:52:10.845Z] Top recommended movies for user id 72: [2025-12-05T12:52:10.845Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:52:10.845Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:52:10.845Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:52:10.845Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:52:10.845Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:52:10.845Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (23508.988 ms) ====== [2025-12-05T12:52:10.845Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-05T12:52:10.845Z] GC before operation: completed in 98.902 ms, heap usage 498.728 MB -> 89.241 MB. [2025-12-05T12:52:14.953Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:52:18.291Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:52:22.394Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:52:24.890Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:52:27.549Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:52:29.343Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:52:31.199Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:52:33.751Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:52:34.150Z] 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. [2025-12-05T12:52:34.150Z] The best model improves the baseline by 14.52%. [2025-12-05T12:52:34.150Z] Top recommended movies for user id 72: [2025-12-05T12:52:34.150Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:52:34.150Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:52:34.150Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:52:34.150Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:52:34.150Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:52:34.150Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (23359.293 ms) ====== [2025-12-05T12:52:34.150Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-05T12:52:34.537Z] GC before operation: completed in 122.904 ms, heap usage 500.150 MB -> 89.404 MB. [2025-12-05T12:52:37.719Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:52:41.830Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:52:45.073Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:52:48.438Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:52:50.969Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:52:53.576Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:52:55.455Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:52:57.364Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:52:57.364Z] 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. [2025-12-05T12:52:57.364Z] The best model improves the baseline by 14.52%. [2025-12-05T12:52:57.364Z] Top recommended movies for user id 72: [2025-12-05T12:52:57.364Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:52:57.364Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:52:57.364Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:52:57.364Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:52:57.364Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:52:57.365Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (23033.445 ms) ====== [2025-12-05T12:52:57.365Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-05T12:52:57.727Z] GC before operation: completed in 107.323 ms, heap usage 492.549 MB -> 89.150 MB. [2025-12-05T12:53:00.163Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:53:04.483Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:53:07.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:53:11.253Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:53:13.097Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:53:14.949Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:53:16.845Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:53:19.444Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:53:19.444Z] 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. [2025-12-05T12:53:19.444Z] The best model improves the baseline by 14.52%. [2025-12-05T12:53:19.826Z] Top recommended movies for user id 72: [2025-12-05T12:53:19.826Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:53:19.826Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:53:19.826Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:53:19.826Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:53:19.826Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:53:19.826Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22078.408 ms) ====== [2025-12-05T12:53:19.826Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-05T12:53:19.826Z] GC before operation: completed in 112.304 ms, heap usage 174.352 MB -> 89.034 MB. [2025-12-05T12:53:23.064Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:53:26.315Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:53:29.497Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:53:31.935Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:53:33.764Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:53:35.114Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:53:36.946Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:53:38.265Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:53:38.630Z] 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. [2025-12-05T12:53:38.630Z] The best model improves the baseline by 14.52%. [2025-12-05T12:53:38.630Z] Top recommended movies for user id 72: [2025-12-05T12:53:38.630Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:53:38.630Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:53:38.630Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:53:38.630Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:53:38.630Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:53:38.630Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18883.009 ms) ====== [2025-12-05T12:53:38.630Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-05T12:53:38.630Z] GC before operation: completed in 95.244 ms, heap usage 426.238 MB -> 89.402 MB. [2025-12-05T12:53:41.964Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:53:44.462Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:53:47.691Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:53:50.249Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:53:51.492Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:53:53.312Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:53:54.587Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:53:56.396Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:53:56.396Z] 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. [2025-12-05T12:53:56.396Z] The best model improves the baseline by 14.52%. [2025-12-05T12:53:56.396Z] Top recommended movies for user id 72: [2025-12-05T12:53:56.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:53:56.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:53:56.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:53:56.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:53:56.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:53:56.396Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17691.842 ms) ====== [2025-12-05T12:53:56.396Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-05T12:53:56.396Z] GC before operation: completed in 94.548 ms, heap usage 352.096 MB -> 89.119 MB. [2025-12-05T12:53:59.713Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:54:03.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:54:07.259Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:54:10.558Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:54:12.560Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:54:14.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:54:16.343Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:54:18.211Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:54:19.082Z] 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. [2025-12-05T12:54:19.082Z] The best model improves the baseline by 14.52%. [2025-12-05T12:54:19.082Z] Top recommended movies for user id 72: [2025-12-05T12:54:19.082Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:54:19.082Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:54:19.082Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:54:19.082Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:54:19.082Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:54:19.082Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (22668.901 ms) ====== [2025-12-05T12:54:19.082Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-05T12:54:19.455Z] GC before operation: completed in 107.488 ms, heap usage 478.068 MB -> 89.539 MB. [2025-12-05T12:54:23.606Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:54:26.949Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:54:31.095Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:54:34.256Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:54:36.183Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:54:38.079Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:54:40.512Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:54:41.773Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:54:42.202Z] 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. [2025-12-05T12:54:42.202Z] The best model improves the baseline by 14.52%. [2025-12-05T12:54:42.588Z] Top recommended movies for user id 72: [2025-12-05T12:54:42.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:54:42.588Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:54:42.588Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:54:42.588Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:54:42.588Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:54:42.588Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (23448.750 ms) ====== [2025-12-05T12:54:42.588Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-05T12:54:43.026Z] GC before operation: completed in 367.018 ms, heap usage 362.204 MB -> 89.164 MB. [2025-12-05T12:54:46.288Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:54:49.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:54:52.997Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:54:56.323Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:54:57.620Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:54:59.509Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:55:02.146Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:55:04.059Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:55:04.059Z] 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. [2025-12-05T12:55:04.059Z] The best model improves the baseline by 14.52%. [2025-12-05T12:55:04.059Z] Top recommended movies for user id 72: [2025-12-05T12:55:04.059Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:55:04.059Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:55:04.059Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:55:04.059Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:55:04.059Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:55:04.059Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20982.113 ms) ====== [2025-12-05T12:55:04.059Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-05T12:55:04.059Z] GC before operation: completed in 100.692 ms, heap usage 318.496 MB -> 89.269 MB. [2025-12-05T12:55:08.393Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:55:12.523Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:55:15.061Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:55:19.238Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:55:20.479Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:55:22.320Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:55:23.568Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:55:25.540Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:55:25.898Z] 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. [2025-12-05T12:55:25.898Z] The best model improves the baseline by 14.52%. [2025-12-05T12:55:25.898Z] Top recommended movies for user id 72: [2025-12-05T12:55:25.898Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:55:25.898Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:55:25.898Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:55:25.898Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:55:25.898Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:55:25.898Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (21736.893 ms) ====== [2025-12-05T12:55:25.898Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-05T12:55:25.898Z] GC before operation: completed in 100.510 ms, heap usage 414.777 MB -> 89.184 MB. [2025-12-05T12:55:29.257Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:55:31.744Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:55:34.968Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:55:36.855Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:55:39.308Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:55:40.553Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:55:41.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:55:44.315Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:55:44.315Z] 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. [2025-12-05T12:55:44.315Z] The best model improves the baseline by 14.52%. [2025-12-05T12:55:44.315Z] Top recommended movies for user id 72: [2025-12-05T12:55:44.315Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:55:44.315Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:55:44.315Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:55:44.315Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:55:44.315Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:55:44.315Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18353.168 ms) ====== [2025-12-05T12:55:44.315Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-05T12:55:44.315Z] GC before operation: completed in 100.929 ms, heap usage 520.380 MB -> 89.458 MB. [2025-12-05T12:55:47.524Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-05T12:55:50.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-05T12:55:53.263Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-05T12:55:55.782Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-05T12:55:57.616Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-05T12:55:58.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-05T12:56:01.102Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-05T12:56:03.067Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-05T12:56:03.067Z] 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. [2025-12-05T12:56:03.465Z] The best model improves the baseline by 14.52%. [2025-12-05T12:56:03.465Z] Top recommended movies for user id 72: [2025-12-05T12:56:03.465Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-05T12:56:03.465Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-05T12:56:03.465Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-05T12:56:03.465Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-05T12:56:03.465Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-05T12:56:03.465Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18848.344 ms) ====== [2025-12-05T12:56:04.237Z] ----------------------------------- [2025-12-05T12:56:04.237Z] renaissance-movie-lens_0_PASSED [2025-12-05T12:56:04.237Z] ----------------------------------- [2025-12-05T12:56:04.237Z] [2025-12-05T12:56:04.237Z] TEST TEARDOWN: [2025-12-05T12:56:04.237Z] Nothing to be done for teardown. [2025-12-05T12:56:04.237Z] renaissance-movie-lens_0 Finish Time: Fri Dec 5 04:56:00 2025 Epoch Time (ms): 1764939360532