renaissance-movie-lens_0
[2025-09-25T05:32:47.252Z] Running test renaissance-movie-lens_0 ...
[2025-09-25T05:32:47.252Z] ===============================================
[2025-09-25T05:32:47.252Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 01:32:46 2025 Epoch Time (ms): 1758778366851
[2025-09-25T05:32:47.252Z] variation: NoOptions
[2025-09-25T05:32:47.791Z] JVM_OPTIONS:
[2025-09-25T05:32:47.791Z] { \
[2025-09-25T05:32:47.791Z] echo ""; echo "TEST SETUP:"; \
[2025-09-25T05:32:47.791Z] echo "Nothing to be done for setup."; \
[2025-09-25T05:32:47.791Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17587762696023/renaissance-movie-lens_0"; \
[2025-09-25T05:32:47.791Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17587762696023/renaissance-movie-lens_0"; \
[2025-09-25T05:32:47.791Z] echo ""; echo "TESTING:"; \
[2025-09-25T05:32:47.791Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/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_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17587762696023/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-25T05:32:47.791Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17587762696023/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-25T05:32:47.791Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-25T05:32:47.791Z] echo "Nothing to be done for teardown."; \
[2025-09-25T05:32:47.791Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17587762696023/TestTargetResult";
[2025-09-25T05:32:47.791Z]
[2025-09-25T05:32:47.791Z] TEST SETUP:
[2025-09-25T05:32:47.791Z] Nothing to be done for setup.
[2025-09-25T05:32:48.417Z]
[2025-09-25T05:32:48.417Z] TESTING:
[2025-09-25T05:33:34.271Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-09-25T05:34:12.221Z] 01:34:08.686 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-25T05:34:23.054Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-25T05:34:25.867Z] Training: 60056, validation: 20285, test: 19854
[2025-09-25T05:34:25.867Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-25T05:34:25.867Z] GC before operation: completed in 440.204 ms, heap usage 480.260 MB -> 75.722 MB.
[2025-09-25T05:35:20.608Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:36:15.761Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:36:49.382Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:37:24.039Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:37:38.614Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:37:59.458Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:38:16.813Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:38:34.117Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:38:35.447Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:38:35.447Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:38:36.857Z] Top recommended movies for user id 72:
[2025-09-25T05:38:36.857Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:38:36.857Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:38:36.857Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:38:36.857Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:38:36.857Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:38:36.857Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (250550.392 ms) ======
[2025-09-25T05:38:36.857Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-25T05:38:38.237Z] GC before operation: completed in 1634.536 ms, heap usage 753.111 MB -> 100.089 MB.
[2025-09-25T05:39:18.818Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:39:33.723Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:39:57.335Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:40:21.121Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:40:33.489Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:40:48.599Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:41:03.582Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:41:15.398Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:41:15.398Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:41:15.941Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:41:16.448Z] Top recommended movies for user id 72:
[2025-09-25T05:41:16.448Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:41:16.448Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:41:16.448Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:41:16.448Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:41:16.448Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:41:16.448Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (158043.867 ms) ======
[2025-09-25T05:41:16.448Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-25T05:41:17.172Z] GC before operation: completed in 428.647 ms, heap usage 438.105 MB -> 88.334 MB.
[2025-09-25T05:41:50.032Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:42:13.783Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:42:38.092Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:43:06.794Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:43:15.527Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:43:27.368Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:43:44.008Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:43:58.122Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:43:58.643Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:43:59.214Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:43:59.843Z] Top recommended movies for user id 72:
[2025-09-25T05:43:59.843Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:43:59.843Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:43:59.843Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:43:59.843Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:43:59.843Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:43:59.843Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (162791.649 ms) ======
[2025-09-25T05:43:59.843Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-25T05:44:01.516Z] GC before operation: completed in 1833.309 ms, heap usage 269.243 MB -> 90.603 MB.
[2025-09-25T05:44:29.452Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:45:02.489Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:45:21.283Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:45:48.984Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:46:01.314Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:46:13.911Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:46:28.138Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:46:48.641Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:46:49.891Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:46:49.891Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:46:50.452Z] Top recommended movies for user id 72:
[2025-09-25T05:46:50.452Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:46:50.452Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:46:50.452Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:46:50.452Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:46:50.452Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:46:50.452Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (168971.278 ms) ======
[2025-09-25T05:46:50.452Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-25T05:46:50.978Z] GC before operation: completed in 505.297 ms, heap usage 502.662 MB -> 89.453 MB.
[2025-09-25T05:47:14.448Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:47:33.633Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:47:53.434Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:48:16.892Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:48:26.989Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:48:38.439Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:48:48.451Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:49:03.218Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:49:04.443Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:49:04.966Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:49:05.616Z] Top recommended movies for user id 72:
[2025-09-25T05:49:05.616Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:49:05.616Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:49:05.616Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:49:05.616Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:49:05.616Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:49:05.616Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (134421.924 ms) ======
[2025-09-25T05:49:05.616Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-25T05:49:06.332Z] GC before operation: completed in 891.487 ms, heap usage 252.833 MB -> 91.155 MB.
[2025-09-25T05:49:25.335Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:49:53.325Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:50:06.867Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:50:23.064Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:50:35.479Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:50:47.416Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:50:57.834Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:51:09.547Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:51:10.609Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:51:10.609Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:51:11.895Z] Top recommended movies for user id 72:
[2025-09-25T05:51:11.895Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:51:11.895Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:51:11.895Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:51:11.895Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:51:11.895Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:51:11.895Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (125477.463 ms) ======
[2025-09-25T05:51:11.895Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-25T05:51:12.902Z] GC before operation: completed in 1048.368 ms, heap usage 469.438 MB -> 89.676 MB.
[2025-09-25T05:51:31.834Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:51:59.589Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:52:18.950Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:52:48.136Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:52:56.390Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:53:08.543Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:53:22.245Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:53:36.497Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:53:37.834Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:53:39.449Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:53:40.840Z] Top recommended movies for user id 72:
[2025-09-25T05:53:40.840Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:53:40.840Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:53:40.840Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:53:40.840Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:53:40.840Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:53:40.840Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (147726.928 ms) ======
[2025-09-25T05:53:40.840Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-25T05:53:40.840Z] GC before operation: completed in 462.199 ms, heap usage 129.341 MB -> 91.293 MB.
[2025-09-25T05:54:08.314Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:54:32.137Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:55:06.131Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:55:25.854Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:55:38.567Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:55:59.886Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:56:14.204Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:56:32.170Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:56:33.514Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:56:33.514Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:56:34.086Z] Top recommended movies for user id 72:
[2025-09-25T05:56:34.086Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:56:34.086Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:56:34.086Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:56:34.086Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:56:34.086Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:56:34.086Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (173263.153 ms) ======
[2025-09-25T05:56:34.086Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-25T05:56:34.864Z] GC before operation: completed in 407.064 ms, heap usage 952.303 MB -> 94.381 MB.
[2025-09-25T05:57:09.249Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:57:23.723Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:57:43.644Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T05:58:08.892Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T05:58:19.303Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T05:58:34.555Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T05:58:49.016Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T05:59:00.652Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T05:59:00.652Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T05:59:00.652Z] The best model improves the baseline by 14.52%.
[2025-09-25T05:59:01.882Z] Top recommended movies for user id 72:
[2025-09-25T05:59:01.882Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T05:59:01.882Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T05:59:01.882Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T05:59:01.882Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T05:59:01.882Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T05:59:01.882Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (147277.121 ms) ======
[2025-09-25T05:59:01.882Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-25T05:59:02.439Z] GC before operation: completed in 450.506 ms, heap usage 170.500 MB -> 90.613 MB.
[2025-09-25T05:59:15.809Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T05:59:26.865Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T05:59:45.769Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:00:14.295Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:00:19.939Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:00:29.990Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:00:41.839Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:00:51.651Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:00:53.220Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:00:53.220Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:00:54.102Z] Top recommended movies for user id 72:
[2025-09-25T06:00:54.102Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:00:54.102Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:00:54.102Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:00:54.102Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:00:54.102Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:00:54.102Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (111188.752 ms) ======
[2025-09-25T06:00:54.102Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-25T06:00:55.415Z] GC before operation: completed in 1917.015 ms, heap usage 658.154 MB -> 93.469 MB.
[2025-09-25T06:01:14.692Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:01:25.772Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:01:48.488Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:02:02.252Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:02:11.521Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:02:22.904Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:02:32.822Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:02:42.348Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:02:42.790Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:02:43.212Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:02:44.330Z] Top recommended movies for user id 72:
[2025-09-25T06:02:44.330Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:02:44.330Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:02:44.330Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:02:44.330Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:02:44.330Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:02:44.330Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (108080.151 ms) ======
[2025-09-25T06:02:44.330Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-25T06:02:45.110Z] GC before operation: completed in 1597.204 ms, heap usage 258.836 MB -> 89.496 MB.
[2025-09-25T06:03:12.975Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:03:22.018Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:03:37.935Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:03:54.789Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:04:06.185Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:04:17.970Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:04:27.946Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:04:42.555Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:04:44.735Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:04:44.735Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:04:46.820Z] Top recommended movies for user id 72:
[2025-09-25T06:04:46.820Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:04:46.820Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:04:46.820Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:04:46.820Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:04:46.820Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:04:46.820Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (121534.116 ms) ======
[2025-09-25T06:04:46.820Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-25T06:04:46.820Z] GC before operation: completed in 377.239 ms, heap usage 302.798 MB -> 92.161 MB.
[2025-09-25T06:05:14.322Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:05:28.188Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:05:47.952Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:06:07.774Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:06:23.963Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:06:40.982Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:06:53.790Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:07:05.780Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:07:06.302Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:07:06.780Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:07:07.378Z] Top recommended movies for user id 72:
[2025-09-25T06:07:07.379Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:07:07.379Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:07:07.379Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:07:07.379Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:07:07.379Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:07:07.379Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (140031.968 ms) ======
[2025-09-25T06:07:07.379Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-25T06:07:07.945Z] GC before operation: completed in 1028.379 ms, heap usage 798.890 MB -> 97.564 MB.
[2025-09-25T06:07:30.626Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:07:55.222Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:08:15.433Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:08:40.750Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:08:53.174Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:09:07.717Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:09:17.560Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:09:26.845Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:09:26.845Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:09:27.694Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:09:28.261Z] Top recommended movies for user id 72:
[2025-09-25T06:09:28.261Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:09:28.261Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:09:28.261Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:09:28.261Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:09:28.261Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:09:28.261Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (140289.407 ms) ======
[2025-09-25T06:09:28.261Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-25T06:09:28.728Z] GC before operation: completed in 431.377 ms, heap usage 720.863 MB -> 95.089 MB.
[2025-09-25T06:09:56.510Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:10:12.738Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:10:31.927Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:10:55.753Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:11:08.221Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:11:19.538Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:11:29.611Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:11:50.356Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:11:51.562Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:11:51.562Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:11:52.220Z] Top recommended movies for user id 72:
[2025-09-25T06:11:52.220Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:11:52.220Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:11:52.220Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:11:52.220Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:11:52.220Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:11:52.220Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (143521.291 ms) ======
[2025-09-25T06:11:52.220Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-25T06:11:52.671Z] GC before operation: completed in 495.866 ms, heap usage 383.247 MB -> 91.624 MB.
[2025-09-25T06:12:16.281Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:12:44.663Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:13:04.330Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:13:27.389Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:13:34.504Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:13:46.831Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:14:01.220Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:14:13.389Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:14:14.471Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:14:15.125Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:14:16.551Z] Top recommended movies for user id 72:
[2025-09-25T06:14:16.551Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:14:16.551Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:14:16.551Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:14:16.551Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:14:16.551Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:14:16.551Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (143783.423 ms) ======
[2025-09-25T06:14:16.551Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-25T06:14:17.115Z] GC before operation: completed in 568.739 ms, heap usage 714.210 MB -> 95.807 MB.
[2025-09-25T06:14:41.200Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:15:04.816Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:15:20.934Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:15:38.064Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:15:48.422Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:15:58.102Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:16:05.725Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:16:17.296Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:16:17.296Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:16:17.296Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:16:18.679Z] Top recommended movies for user id 72:
[2025-09-25T06:16:18.679Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:16:18.679Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:16:18.679Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:16:18.679Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:16:18.679Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:16:18.679Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (121306.624 ms) ======
[2025-09-25T06:16:18.679Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-25T06:16:18.679Z] GC before operation: completed in 402.530 ms, heap usage 196.482 MB -> 89.562 MB.
[2025-09-25T06:16:52.105Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:17:12.879Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:17:36.616Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:17:57.486Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:18:09.556Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:18:17.861Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:18:34.536Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:18:49.100Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:18:51.125Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:18:51.125Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:18:51.658Z] Top recommended movies for user id 72:
[2025-09-25T06:18:51.658Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:18:51.658Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:18:51.658Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:18:51.658Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:18:51.658Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:18:51.658Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (152746.332 ms) ======
[2025-09-25T06:18:51.658Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-25T06:18:53.144Z] GC before operation: completed in 1333.144 ms, heap usage 303.883 MB -> 89.560 MB.
[2025-09-25T06:19:16.714Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:19:38.729Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:20:02.902Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:20:25.971Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:20:36.756Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:20:56.872Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:21:09.726Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:21:19.861Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:21:20.907Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:21:20.907Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:21:21.437Z] Top recommended movies for user id 72:
[2025-09-25T06:21:21.437Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:21:21.437Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:21:21.437Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:21:21.437Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:21:21.437Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:21:21.437Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (148188.746 ms) ======
[2025-09-25T06:21:21.437Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-25T06:21:21.437Z] GC before operation: completed in 360.301 ms, heap usage 356.794 MB -> 91.578 MB.
[2025-09-25T06:21:49.496Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:22:09.422Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:22:38.294Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:22:54.697Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:23:07.505Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:23:17.188Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:23:28.997Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:23:49.481Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:23:49.481Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-25T06:23:49.481Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:23:51.448Z] Top recommended movies for user id 72:
[2025-09-25T06:23:51.448Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-25T06:23:51.448Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-25T06:23:51.448Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-25T06:23:51.448Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-25T06:23:51.448Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-25T06:23:51.448Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (149901.898 ms) ======
[2025-09-25T06:24:01.219Z] -----------------------------------
[2025-09-25T06:24:01.219Z] renaissance-movie-lens_0_PASSED
[2025-09-25T06:24:01.219Z] -----------------------------------
[2025-09-25T06:24:01.219Z]
[2025-09-25T06:24:01.219Z] TEST TEARDOWN:
[2025-09-25T06:24:01.219Z] Nothing to be done for teardown.
[2025-09-25T06:24:02.341Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 02:24:01 2025 Epoch Time (ms): 1758781441496