Test Results Summary Service

renaissance-movie-lens_0

[2025-10-16T21:06:13.347Z] Running test renaissance-movie-lens_0 ... [2025-10-16T21:06:13.347Z] =============================================== [2025-10-16T21:06:13.347Z] renaissance-movie-lens_0 Start Time: Thu Oct 16 17:06:13 2025 Epoch Time (ms): 1760648773014 [2025-10-16T21:06:13.347Z] variation: NoOptions [2025-10-16T21:06:13.347Z] JVM_OPTIONS: [2025-10-16T21:06:13.347Z] { \ [2025-10-16T21:06:13.347Z] echo ""; echo "TEST SETUP:"; \ [2025-10-16T21:06:13.347Z] echo "Nothing to be done for setup."; \ [2025-10-16T21:06:13.347Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17606481536612/renaissance-movie-lens_0"; \ [2025-10-16T21:06:13.347Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17606481536612/renaissance-movie-lens_0"; \ [2025-10-16T21:06:13.347Z] echo ""; echo "TESTING:"; \ [2025-10-16T21:06:13.347Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_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_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17606481536612/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-10-16T21:06:13.347Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17606481536612/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-10-16T21:06:13.347Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-10-16T21:06:13.347Z] echo "Nothing to be done for teardown."; \ [2025-10-16T21:06:13.347Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17606481536612/TestTargetResult"; [2025-10-16T21:06:13.347Z] [2025-10-16T21:06:13.347Z] TEST SETUP: [2025-10-16T21:06:13.347Z] Nothing to be done for setup. [2025-10-16T21:06:13.347Z] [2025-10-16T21:06:13.347Z] TESTING: [2025-10-16T21:06:13.347Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-10-16T21:06:13.347Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/output_17606481536612/renaissance-movie-lens_0/launcher-170613-8500489171208016223/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-10-16T21:06:13.347Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-10-16T21:06:13.347Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-10-16T21:06:15.732Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-10-16T21:06:19.881Z] 17:06:17.643 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. [2025-10-16T21:06:19.881Z] Got 100004 ratings from 671 users on 9066 movies. [2025-10-16T21:06:19.881Z] Training: 60056, validation: 20285, test: 19854 [2025-10-16T21:06:19.881Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-10-16T21:06:19.881Z] GC before operation: completed in 50.715 ms, heap usage 243.725 MB -> 75.786 MB. [2025-10-16T21:06:21.647Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:06:22.894Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:06:24.662Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:06:25.900Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:06:26.256Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:06:27.022Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:06:27.800Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:06:28.563Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:06:28.919Z] 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. [2025-10-16T21:06:28.919Z] The best model improves the baseline by 14.52%. [2025-10-16T21:06:28.919Z] Top recommended movies for user id 72: [2025-10-16T21:06:28.919Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:06:28.919Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:06:28.919Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:06:28.919Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:06:28.919Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:06:28.919Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (9879.805 ms) ====== [2025-10-16T21:06:28.919Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-10-16T21:06:28.919Z] GC before operation: completed in 66.417 ms, heap usage 240.235 MB -> 89.543 MB. [2025-10-16T21:06:30.167Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:06:31.426Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:06:32.667Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:06:33.451Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:06:34.224Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:06:35.164Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:06:35.523Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:06:36.286Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:06:36.286Z] 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. [2025-10-16T21:06:36.286Z] The best model improves the baseline by 14.52%. [2025-10-16T21:06:36.286Z] Top recommended movies for user id 72: [2025-10-16T21:06:36.286Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:06:36.286Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:06:36.286Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:06:36.286Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:06:36.286Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:06:36.286Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (7256.297 ms) ====== [2025-10-16T21:06:36.286Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-10-16T21:06:36.286Z] GC before operation: completed in 49.018 ms, heap usage 393.121 MB -> 88.556 MB. [2025-10-16T21:06:37.538Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:06:38.316Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:06:39.556Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:06:40.806Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:06:41.167Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:06:41.937Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:06:42.696Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:06:43.468Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:06:43.468Z] 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. [2025-10-16T21:06:43.468Z] The best model improves the baseline by 14.52%. [2025-10-16T21:06:43.468Z] Top recommended movies for user id 72: [2025-10-16T21:06:43.468Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:06:43.468Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:06:43.468Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:06:43.468Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:06:43.468Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:06:43.468Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (7165.932 ms) ====== [2025-10-16T21:06:43.468Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-10-16T21:06:43.468Z] GC before operation: completed in 52.045 ms, heap usage 273.029 MB -> 89.148 MB. [2025-10-16T21:06:44.697Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:06:45.925Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:06:47.148Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:06:47.910Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:06:48.673Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:06:49.454Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:06:49.818Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:06:50.582Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:06:50.582Z] 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. [2025-10-16T21:06:50.582Z] The best model improves the baseline by 14.52%. [2025-10-16T21:06:50.941Z] Top recommended movies for user id 72: [2025-10-16T21:06:50.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:06:50.941Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:06:50.941Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:06:50.941Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:06:50.941Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:06:50.941Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (7176.529 ms) ====== [2025-10-16T21:06:50.941Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-10-16T21:06:50.941Z] GC before operation: completed in 49.054 ms, heap usage 326.641 MB -> 89.376 MB. [2025-10-16T21:06:51.716Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:06:52.938Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:06:54.169Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:06:54.930Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:06:55.704Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:06:56.490Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:06:56.852Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:06:57.613Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:06:57.614Z] 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. [2025-10-16T21:06:57.614Z] The best model improves the baseline by 14.52%. [2025-10-16T21:06:57.614Z] Top recommended movies for user id 72: [2025-10-16T21:06:57.614Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:06:57.614Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:06:57.614Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:06:57.614Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:06:57.614Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:06:57.614Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (6945.260 ms) ====== [2025-10-16T21:06:57.614Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-10-16T21:06:57.972Z] GC before operation: completed in 50.276 ms, heap usage 298.275 MB -> 89.293 MB. [2025-10-16T21:06:58.736Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:06:59.986Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:01.343Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:02.128Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:02.929Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:03.296Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:04.067Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:04.448Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:04.801Z] 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. [2025-10-16T21:07:04.801Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:04.801Z] Top recommended movies for user id 72: [2025-10-16T21:07:04.801Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:04.801Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:04.801Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:04.801Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:04.801Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:04.801Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (6902.875 ms) ====== [2025-10-16T21:07:04.801Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-10-16T21:07:04.801Z] GC before operation: completed in 50.677 ms, heap usage 243.155 MB -> 89.459 MB. [2025-10-16T21:07:06.035Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:07.263Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:08.092Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:09.377Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:10.210Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:10.574Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:11.348Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:11.704Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:12.059Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-10-16T21:07:12.059Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:12.059Z] Top recommended movies for user id 72: [2025-10-16T21:07:12.059Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:12.059Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:12.059Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:12.059Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:12.059Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:12.059Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7319.606 ms) ====== [2025-10-16T21:07:12.059Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-10-16T21:07:12.059Z] GC before operation: completed in 51.331 ms, heap usage 340.684 MB -> 89.659 MB. [2025-10-16T21:07:13.415Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:14.233Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:15.468Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:16.286Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:17.118Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:17.899Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:18.275Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:19.055Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:19.055Z] 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. [2025-10-16T21:07:19.055Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:19.056Z] Top recommended movies for user id 72: [2025-10-16T21:07:19.056Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:19.056Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:19.056Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:19.056Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:19.056Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:19.056Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (6972.365 ms) ====== [2025-10-16T21:07:19.056Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-10-16T21:07:19.056Z] GC before operation: completed in 53.446 ms, heap usage 146.457 MB -> 89.533 MB. [2025-10-16T21:07:20.398Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:21.233Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:22.486Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:23.267Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:24.031Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:24.802Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:25.570Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:26.342Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:26.342Z] 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. [2025-10-16T21:07:26.342Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:26.342Z] Top recommended movies for user id 72: [2025-10-16T21:07:26.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:26.342Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:26.342Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:26.342Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:26.342Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:26.342Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (7144.478 ms) ====== [2025-10-16T21:07:26.342Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-10-16T21:07:26.342Z] GC before operation: completed in 48.549 ms, heap usage 273.445 MB -> 89.652 MB. [2025-10-16T21:07:27.570Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:28.357Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:29.585Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:30.831Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:31.189Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:31.958Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:32.716Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:33.069Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:33.422Z] 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. [2025-10-16T21:07:33.422Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:33.422Z] Top recommended movies for user id 72: [2025-10-16T21:07:33.422Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:33.422Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:33.422Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:33.422Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:33.422Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:33.422Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (7048.186 ms) ====== [2025-10-16T21:07:33.422Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-10-16T21:07:33.422Z] GC before operation: completed in 50.473 ms, heap usage 333.342 MB -> 90.038 MB. [2025-10-16T21:07:34.673Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:35.906Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:36.677Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:37.947Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:38.307Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:38.741Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:39.515Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:39.884Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:39.884Z] 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. [2025-10-16T21:07:39.884Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:40.242Z] Top recommended movies for user id 72: [2025-10-16T21:07:40.242Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:40.242Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:40.242Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:40.242Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:40.242Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:40.242Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6634.568 ms) ====== [2025-10-16T21:07:40.242Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-10-16T21:07:40.242Z] GC before operation: completed in 51.208 ms, heap usage 452.841 MB -> 89.823 MB. [2025-10-16T21:07:41.014Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:42.313Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:43.110Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:44.342Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:44.696Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:45.140Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:45.911Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:46.699Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:46.699Z] 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. [2025-10-16T21:07:46.699Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:46.699Z] Top recommended movies for user id 72: [2025-10-16T21:07:46.699Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:46.699Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:46.699Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:46.699Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:46.699Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:46.699Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (6509.398 ms) ====== [2025-10-16T21:07:46.699Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-10-16T21:07:46.699Z] GC before operation: completed in 50.023 ms, heap usage 162.962 MB -> 89.595 MB. [2025-10-16T21:07:47.938Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:48.712Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:49.945Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:50.703Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:51.080Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:51.844Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:52.648Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:53.010Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:53.010Z] 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. [2025-10-16T21:07:53.010Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:53.010Z] Top recommended movies for user id 72: [2025-10-16T21:07:53.010Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:53.010Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:53.010Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:53.010Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:53.010Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:53.010Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (6435.003 ms) ====== [2025-10-16T21:07:53.010Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-10-16T21:07:53.369Z] GC before operation: completed in 48.915 ms, heap usage 151.163 MB -> 89.817 MB. [2025-10-16T21:07:54.134Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:07:55.379Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:07:56.153Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:07:57.408Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:07:57.769Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:07:58.545Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:07:58.900Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:07:59.663Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:07:59.663Z] 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. [2025-10-16T21:07:59.663Z] The best model improves the baseline by 14.52%. [2025-10-16T21:07:59.663Z] Top recommended movies for user id 72: [2025-10-16T21:07:59.663Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:07:59.663Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:07:59.663Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:07:59.663Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:07:59.663Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:07:59.663Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (6449.360 ms) ====== [2025-10-16T21:07:59.663Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-10-16T21:07:59.663Z] GC before operation: completed in 48.059 ms, heap usage 116.471 MB -> 89.549 MB. [2025-10-16T21:08:00.923Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:08:01.737Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:08:03.047Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:08:03.847Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:08:04.228Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:08:05.017Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:08:05.823Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:08:06.208Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:08:06.566Z] 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. [2025-10-16T21:08:06.566Z] The best model improves the baseline by 14.52%. [2025-10-16T21:08:06.566Z] Top recommended movies for user id 72: [2025-10-16T21:08:06.566Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:08:06.566Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:08:06.566Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:08:06.566Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:08:06.566Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:08:06.566Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (6803.227 ms) ====== [2025-10-16T21:08:06.566Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-10-16T21:08:06.566Z] GC before operation: completed in 48.460 ms, heap usage 173.523 MB -> 89.907 MB. [2025-10-16T21:08:07.793Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:08:08.566Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:08:09.331Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:08:10.568Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:08:10.924Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:08:11.697Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:08:12.066Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:08:12.841Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:08:12.841Z] 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. [2025-10-16T21:08:12.841Z] The best model improves the baseline by 14.52%. [2025-10-16T21:08:13.202Z] Top recommended movies for user id 72: [2025-10-16T21:08:13.202Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:08:13.202Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:08:13.202Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:08:13.202Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:08:13.202Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:08:13.202Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6481.878 ms) ====== [2025-10-16T21:08:13.202Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-10-16T21:08:13.202Z] GC before operation: completed in 50.819 ms, heap usage 420.192 MB -> 90.121 MB. [2025-10-16T21:08:13.961Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:08:15.198Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:08:16.006Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:08:17.243Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:08:18.001Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:08:18.364Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:08:19.127Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:08:19.899Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:08:19.899Z] 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. [2025-10-16T21:08:19.899Z] The best model improves the baseline by 14.52%. [2025-10-16T21:08:19.899Z] Top recommended movies for user id 72: [2025-10-16T21:08:19.899Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:08:19.899Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:08:19.899Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:08:19.899Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:08:19.899Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:08:19.899Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (6861.082 ms) ====== [2025-10-16T21:08:19.899Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-10-16T21:08:19.899Z] GC before operation: completed in 47.631 ms, heap usage 333.163 MB -> 90.061 MB. [2025-10-16T21:08:21.147Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:08:22.373Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:08:23.206Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:08:24.549Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:08:24.919Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:08:25.690Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:08:26.462Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:08:26.828Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:08:26.828Z] 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. [2025-10-16T21:08:26.828Z] The best model improves the baseline by 14.52%. [2025-10-16T21:08:27.192Z] Top recommended movies for user id 72: [2025-10-16T21:08:27.192Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:08:27.192Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:08:27.192Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:08:27.192Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:08:27.192Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:08:27.192Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (7064.086 ms) ====== [2025-10-16T21:08:27.192Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-10-16T21:08:27.192Z] GC before operation: completed in 53.113 ms, heap usage 337.768 MB -> 89.835 MB. [2025-10-16T21:08:28.432Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:08:29.208Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:08:30.467Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:08:31.696Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:08:32.062Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:08:32.829Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:08:33.611Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:08:33.990Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:08:34.351Z] 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. [2025-10-16T21:08:34.351Z] The best model improves the baseline by 14.52%. [2025-10-16T21:08:34.351Z] Top recommended movies for user id 72: [2025-10-16T21:08:34.351Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:08:34.351Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:08:34.351Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:08:34.351Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:08:34.351Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:08:34.351Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (7182.909 ms) ====== [2025-10-16T21:08:34.351Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-10-16T21:08:34.351Z] GC before operation: completed in 52.664 ms, heap usage 212.990 MB -> 89.662 MB. [2025-10-16T21:08:35.575Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-16T21:08:36.835Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-16T21:08:37.612Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-16T21:08:38.841Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-16T21:08:39.626Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-16T21:08:39.984Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-16T21:08:40.749Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-16T21:08:41.525Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-16T21:08:41.525Z] 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. [2025-10-16T21:08:41.525Z] The best model improves the baseline by 14.52%. [2025-10-16T21:08:41.525Z] Top recommended movies for user id 72: [2025-10-16T21:08:41.525Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-16T21:08:41.525Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-16T21:08:41.525Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-16T21:08:41.525Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-16T21:08:41.525Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-16T21:08:41.525Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (7282.568 ms) ====== [2025-10-16T21:08:41.880Z] ----------------------------------- [2025-10-16T21:08:41.880Z] renaissance-movie-lens_0_PASSED [2025-10-16T21:08:41.880Z] ----------------------------------- [2025-10-16T21:08:41.880Z] [2025-10-16T21:08:41.880Z] TEST TEARDOWN: [2025-10-16T21:08:41.880Z] Nothing to be done for teardown. [2025-10-16T21:08:41.880Z] renaissance-movie-lens_0 Finish Time: Thu Oct 16 17:08:41 2025 Epoch Time (ms): 1760648921633