[2025-09-05T17:40:46.871Z] Running test renaissance-movie-lens_0 ... [2025-09-05T17:40:46.871Z] =============================================== [2025-09-05T17:40:46.871Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 10:40:46 2025 Epoch Time (ms): 1757094046273 [2025-09-05T17:40:46.871Z] variation: NoOptions [2025-09-05T17:40:46.871Z] JVM_OPTIONS: [2025-09-05T17:40:46.871Z] { \ [2025-09-05T17:40:46.871Z] echo ""; echo "TEST SETUP:"; \ [2025-09-05T17:40:46.871Z] echo "Nothing to be done for setup."; \ [2025-09-05T17:40:46.871Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17570903486685/renaissance-movie-lens_0"; \ [2025-09-05T17:40:46.871Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17570903486685/renaissance-movie-lens_0"; \ [2025-09-05T17:40:46.871Z] echo ""; echo "TESTING:"; \ [2025-09-05T17:40:46.871Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/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_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17570903486685/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-05T17:40:46.871Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17570903486685/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-05T17:40:46.871Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-05T17:40:46.871Z] echo "Nothing to be done for teardown."; \ [2025-09-05T17:40:46.871Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17570903486685/TestTargetResult"; [2025-09-05T17:40:46.871Z] [2025-09-05T17:40:46.871Z] TEST SETUP: [2025-09-05T17:40:46.871Z] Nothing to be done for setup. [2025-09-05T17:40:46.871Z] [2025-09-05T17:40:46.871Z] TESTING: [2025-09-05T17:40:49.870Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-09-05T17:40:49.871Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/output_17570903486685/renaissance-movie-lens_0/launcher-104046-8957388088520418719/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-09-05T17:40:49.871Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-09-05T17:40:49.871Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-09-05T17:41:07.321Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-09-05T17:41:25.599Z] 10:41:23.660 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. [2025-09-05T17:41:31.652Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-05T17:41:33.487Z] Training: 60056, validation: 20285, test: 19854 [2025-09-05T17:41:33.487Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-05T17:41:33.912Z] GC before operation: completed in 468.596 ms, heap usage 294.000 MB -> 76.121 MB. [2025-09-05T17:41:59.813Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:42:18.601Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:42:33.470Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:42:44.093Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:42:51.624Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:43:00.614Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:43:08.005Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:43:14.786Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:43:15.406Z] 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. [2025-09-05T17:43:15.406Z] The best model improves the baseline by 14.52%. [2025-09-05T17:43:15.853Z] Top recommended movies for user id 72: [2025-09-05T17:43:15.853Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:43:15.853Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:43:15.853Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:43:15.853Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:43:15.853Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:43:15.853Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (101758.561 ms) ====== [2025-09-05T17:43:15.853Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-05T17:43:17.005Z] GC before operation: completed in 474.855 ms, heap usage 585.676 MB -> 91.993 MB. [2025-09-05T17:43:29.710Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:43:41.878Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:43:54.547Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:44:07.140Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:44:12.892Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:44:20.027Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:44:27.058Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:44:34.265Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:44:34.265Z] 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. [2025-09-05T17:44:34.699Z] The best model improves the baseline by 14.52%. [2025-09-05T17:44:34.699Z] Top recommended movies for user id 72: [2025-09-05T17:44:34.699Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:44:34.699Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:44:35.136Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:44:35.136Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:44:35.136Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:44:35.136Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (78590.144 ms) ====== [2025-09-05T17:44:35.136Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-05T17:44:35.136Z] GC before operation: completed in 324.945 ms, heap usage 268.087 MB -> 88.018 MB. [2025-09-05T17:44:50.108Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:45:02.747Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:45:13.563Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:45:26.436Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:45:35.132Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:45:41.347Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:45:48.688Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:45:54.446Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:45:55.062Z] 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. [2025-09-05T17:45:55.577Z] The best model improves the baseline by 14.52%. [2025-09-05T17:45:56.020Z] Top recommended movies for user id 72: [2025-09-05T17:45:56.020Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:45:56.020Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:45:56.020Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:45:56.020Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:45:56.020Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:45:56.020Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (80739.694 ms) ====== [2025-09-05T17:45:56.020Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-05T17:45:56.752Z] GC before operation: completed in 348.393 ms, heap usage 216.591 MB -> 88.614 MB. [2025-09-05T17:46:11.416Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:46:24.094Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:46:39.693Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:46:52.095Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:46:57.171Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:47:04.410Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:47:11.851Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:47:18.056Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:47:19.092Z] 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. [2025-09-05T17:47:19.092Z] The best model improves the baseline by 14.52%. [2025-09-05T17:47:20.044Z] Top recommended movies for user id 72: [2025-09-05T17:47:20.044Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:47:20.044Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:47:20.044Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:47:20.044Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:47:20.044Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:47:20.044Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (83630.171 ms) ====== [2025-09-05T17:47:20.044Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-05T17:47:20.532Z] GC before operation: completed in 438.001 ms, heap usage 785.610 MB -> 93.184 MB. [2025-09-05T17:47:35.569Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:47:50.162Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:48:05.139Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:48:16.152Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:48:23.436Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:48:29.873Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:48:35.901Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:48:43.027Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:48:44.219Z] 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. [2025-09-05T17:48:44.219Z] The best model improves the baseline by 14.52%. [2025-09-05T17:48:44.760Z] Top recommended movies for user id 72: [2025-09-05T17:48:44.760Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:48:44.760Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:48:44.760Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:48:44.760Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:48:44.760Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:48:44.760Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (84027.299 ms) ====== [2025-09-05T17:48:44.760Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-05T17:48:45.362Z] GC before operation: completed in 566.444 ms, heap usage 729.274 MB -> 92.829 MB. [2025-09-05T17:49:00.447Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:49:12.963Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:49:25.381Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:49:37.640Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:49:44.098Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:49:51.154Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:49:59.712Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:50:07.376Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:50:08.371Z] 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. [2025-09-05T17:50:08.371Z] The best model improves the baseline by 14.52%. [2025-09-05T17:50:09.479Z] Top recommended movies for user id 72: [2025-09-05T17:50:09.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:50:09.479Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:50:09.479Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:50:09.479Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:50:09.479Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:50:09.479Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (83575.339 ms) ====== [2025-09-05T17:50:09.479Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-05T17:50:09.479Z] GC before operation: completed in 397.873 ms, heap usage 932.901 MB -> 94.114 MB. [2025-09-05T17:50:22.317Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:50:37.481Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:50:46.270Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:50:57.021Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:51:04.501Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:51:10.612Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:51:16.542Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:51:22.107Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:51:23.120Z] 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. [2025-09-05T17:51:23.120Z] The best model improves the baseline by 14.52%. [2025-09-05T17:51:24.139Z] Top recommended movies for user id 72: [2025-09-05T17:51:24.139Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:51:24.139Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:51:24.139Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:51:24.139Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:51:24.139Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:51:24.139Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (74890.026 ms) ====== [2025-09-05T17:51:24.139Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-05T17:51:24.139Z] GC before operation: completed in 233.183 ms, heap usage 237.532 MB -> 89.277 MB. [2025-09-05T17:51:34.074Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:51:44.633Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:51:52.028Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:52:00.566Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:52:05.108Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:52:09.712Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:52:15.400Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:52:19.920Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:52:20.376Z] 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. [2025-09-05T17:52:20.376Z] The best model improves the baseline by 14.52%. [2025-09-05T17:52:20.917Z] Top recommended movies for user id 72: [2025-09-05T17:52:20.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:52:20.917Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:52:20.917Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:52:20.917Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:52:20.917Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:52:20.917Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (56851.075 ms) ====== [2025-09-05T17:52:20.917Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-05T17:52:21.367Z] GC before operation: completed in 433.775 ms, heap usage 494.271 MB -> 89.823 MB. [2025-09-05T17:52:29.947Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:52:40.093Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:52:55.808Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:53:08.414Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:53:14.575Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:53:19.656Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:53:26.778Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:53:32.511Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:53:33.575Z] 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. [2025-09-05T17:53:33.575Z] The best model improves the baseline by 14.52%. [2025-09-05T17:53:34.033Z] Top recommended movies for user id 72: [2025-09-05T17:53:34.033Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:53:34.033Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:53:34.033Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:53:34.033Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:53:34.033Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:53:34.033Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (72599.809 ms) ====== [2025-09-05T17:53:34.033Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-05T17:53:34.492Z] GC before operation: completed in 546.729 ms, heap usage 1.405 GB -> 95.380 MB. [2025-09-05T17:53:49.120Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:53:59.550Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:54:10.091Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:54:22.703Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:54:27.984Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:54:34.034Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:54:41.688Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:54:48.812Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:54:48.812Z] 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. [2025-09-05T17:54:48.812Z] The best model improves the baseline by 14.52%. [2025-09-05T17:54:49.417Z] Top recommended movies for user id 72: [2025-09-05T17:54:49.417Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:54:49.417Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:54:49.417Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:54:49.417Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:54:49.417Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:54:49.417Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (74965.581 ms) ====== [2025-09-05T17:54:49.417Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-05T17:54:49.890Z] GC before operation: completed in 487.854 ms, heap usage 1.079 GB -> 95.034 MB. [2025-09-05T17:55:02.674Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:55:13.345Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:55:23.625Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:55:34.411Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:55:40.441Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:55:46.294Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:55:53.484Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:55:59.103Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:55:59.103Z] 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. [2025-09-05T17:55:59.578Z] The best model improves the baseline by 14.52%. [2025-09-05T17:56:00.112Z] Top recommended movies for user id 72: [2025-09-05T17:56:00.113Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:56:00.113Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:56:00.113Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:56:00.113Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:56:00.113Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:56:00.113Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (69701.037 ms) ====== [2025-09-05T17:56:00.113Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-05T17:56:00.113Z] GC before operation: completed in 381.303 ms, heap usage 512.786 MB -> 92.941 MB. [2025-09-05T17:56:13.015Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:56:25.373Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:56:35.894Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:56:46.236Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:56:53.477Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:56:59.886Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:57:07.031Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:57:14.396Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:57:15.650Z] 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. [2025-09-05T17:57:15.650Z] The best model improves the baseline by 14.52%. [2025-09-05T17:57:16.278Z] Top recommended movies for user id 72: [2025-09-05T17:57:16.278Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:57:16.278Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:57:16.278Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:57:16.278Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:57:16.278Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:57:16.278Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (76145.989 ms) ====== [2025-09-05T17:57:16.278Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-05T17:57:16.928Z] GC before operation: completed in 536.555 ms, heap usage 684.435 MB -> 93.393 MB. [2025-09-05T17:57:29.750Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:57:40.331Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:57:53.060Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:58:02.582Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:58:07.476Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:58:18.304Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:58:24.098Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:58:29.852Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:58:31.326Z] 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. [2025-09-05T17:58:31.326Z] The best model improves the baseline by 14.52%. [2025-09-05T17:58:31.791Z] Top recommended movies for user id 72: [2025-09-05T17:58:31.791Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:58:31.791Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:58:31.791Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:58:31.791Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:58:31.791Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:58:31.791Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (74961.642 ms) ====== [2025-09-05T17:58:31.791Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-05T17:58:32.348Z] GC before operation: completed in 305.455 ms, heap usage 1.270 GB -> 95.411 MB. [2025-09-05T17:58:45.116Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:58:55.632Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:59:06.207Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:59:18.489Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:59:23.172Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:59:30.706Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:59:38.054Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:59:43.056Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:59:44.108Z] 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. [2025-09-05T17:59:44.108Z] The best model improves the baseline by 14.52%. [2025-09-05T17:59:44.654Z] Top recommended movies for user id 72: [2025-09-05T17:59:44.654Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T17:59:44.654Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T17:59:44.654Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T17:59:44.654Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T17:59:44.654Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T17:59:44.654Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (72465.349 ms) ====== [2025-09-05T17:59:44.654Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-05T17:59:45.124Z] GC before operation: completed in 343.464 ms, heap usage 123.896 MB -> 93.385 MB. [2025-09-05T17:59:57.506Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T18:00:10.338Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T18:00:21.247Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T18:00:31.714Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T18:00:36.425Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T18:00:43.892Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T18:00:49.842Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T18:00:56.843Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T18:00:56.843Z] 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. [2025-09-05T18:00:57.274Z] The best model improves the baseline by 14.52%. [2025-09-05T18:00:57.763Z] Top recommended movies for user id 72: [2025-09-05T18:00:57.763Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T18:00:57.763Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T18:00:57.763Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T18:00:57.763Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T18:00:57.763Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T18:00:57.763Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (72907.370 ms) ====== [2025-09-05T18:00:57.763Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-05T18:00:58.237Z] GC before operation: completed in 304.921 ms, heap usage 224.762 MB -> 89.581 MB. [2025-09-05T18:01:11.313Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T18:01:23.950Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T18:01:35.134Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T18:01:47.922Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T18:01:55.541Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T18:02:01.851Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T18:02:10.873Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T18:02:21.609Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T18:02:21.609Z] 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. [2025-09-05T18:02:21.609Z] The best model improves the baseline by 14.52%. [2025-09-05T18:02:21.609Z] Top recommended movies for user id 72: [2025-09-05T18:02:21.609Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T18:02:21.609Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T18:02:21.609Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T18:02:21.609Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T18:02:21.609Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T18:02:21.609Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (83526.769 ms) ====== [2025-09-05T18:02:21.609Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-05T18:02:22.122Z] GC before operation: completed in 303.565 ms, heap usage 210.125 MB -> 89.422 MB. [2025-09-05T18:02:35.244Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T18:02:48.035Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T18:03:00.660Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T18:03:09.675Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T18:03:16.959Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T18:03:22.828Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T18:03:28.743Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T18:03:32.669Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T18:03:33.628Z] 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. [2025-09-05T18:03:33.628Z] The best model improves the baseline by 14.52%. [2025-09-05T18:03:34.094Z] Top recommended movies for user id 72: [2025-09-05T18:03:34.094Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T18:03:34.094Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T18:03:34.094Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T18:03:34.094Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T18:03:34.094Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T18:03:34.094Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (72119.653 ms) ====== [2025-09-05T18:03:34.094Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-05T18:03:34.593Z] GC before operation: completed in 454.911 ms, heap usage 409.391 MB -> 89.926 MB. [2025-09-05T18:03:45.039Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T18:03:51.903Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T18:04:00.514Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T18:04:08.067Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T18:04:16.733Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T18:04:26.225Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T18:04:33.416Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T18:04:38.628Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T18:04:39.553Z] 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. [2025-09-05T18:04:39.553Z] The best model improves the baseline by 14.52%. [2025-09-05T18:04:40.210Z] Top recommended movies for user id 72: [2025-09-05T18:04:40.210Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T18:04:40.210Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T18:04:40.210Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T18:04:40.210Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T18:04:40.210Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T18:04:40.210Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (65530.899 ms) ====== [2025-09-05T18:04:40.210Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-05T18:04:40.933Z] GC before operation: completed in 517.081 ms, heap usage 1.097 GB -> 95.005 MB. [2025-09-05T18:04:53.576Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T18:05:03.917Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T18:05:16.662Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T18:05:29.229Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T18:05:35.024Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T18:05:41.024Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T18:05:49.605Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T18:05:56.769Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T18:05:57.175Z] 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. [2025-09-05T18:05:57.175Z] The best model improves the baseline by 14.52%. [2025-09-05T18:05:57.585Z] Top recommended movies for user id 72: [2025-09-05T18:05:57.586Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T18:05:57.586Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T18:05:57.586Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T18:05:57.586Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T18:05:57.586Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T18:05:57.586Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (76970.508 ms) ====== [2025-09-05T18:05:57.586Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-05T18:05:58.071Z] GC before operation: completed in 348.837 ms, heap usage 320.279 MB -> 89.713 MB. [2025-09-05T18:06:10.607Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T18:06:22.872Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T18:06:34.420Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T18:06:44.462Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T18:06:51.915Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T18:06:59.219Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T18:07:06.404Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T18:07:13.524Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T18:07:14.425Z] 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. [2025-09-05T18:07:14.425Z] The best model improves the baseline by 14.52%. [2025-09-05T18:07:14.832Z] Top recommended movies for user id 72: [2025-09-05T18:07:14.832Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T18:07:14.832Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T18:07:14.832Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T18:07:14.832Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T18:07:14.832Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T18:07:14.832Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (76680.029 ms) ====== [2025-09-05T18:07:19.262Z] ----------------------------------- [2025-09-05T18:07:19.262Z] renaissance-movie-lens_0_PASSED [2025-09-05T18:07:19.262Z] ----------------------------------- [2025-09-05T18:07:19.262Z] [2025-09-05T18:07:19.262Z] TEST TEARDOWN: [2025-09-05T18:07:19.262Z] Nothing to be done for teardown. [2025-09-05T18:07:19.657Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 11:07:18 2025 Epoch Time (ms): 1757095638934