Test Results Summary Service

renaissance-movie-lens_0

[2025-10-22T16:59:53.445Z] Running test renaissance-movie-lens_0 ... [2025-10-22T16:59:53.445Z] =============================================== [2025-10-22T16:59:53.445Z] renaissance-movie-lens_0 Start Time: Wed Oct 22 09:59:53 2025 Epoch Time (ms): 1761152393141 [2025-10-22T16:59:53.445Z] variation: NoOptions [2025-10-22T16:59:53.445Z] JVM_OPTIONS: [2025-10-22T16:59:53.445Z] { \ [2025-10-22T16:59:53.445Z] echo ""; echo "TEST SETUP:"; \ [2025-10-22T16:59:53.445Z] echo "Nothing to be done for setup."; \ [2025-10-22T16:59:53.445Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17611514254816/renaissance-movie-lens_0"; \ [2025-10-22T16:59:53.445Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17611514254816/renaissance-movie-lens_0"; \ [2025-10-22T16:59:53.445Z] echo ""; echo "TESTING:"; \ [2025-10-22T16:59:53.445Z] "/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_17611514254816/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-10-22T16:59:53.445Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17611514254816/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-10-22T16:59:53.445Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-10-22T16:59:53.445Z] echo "Nothing to be done for teardown."; \ [2025-10-22T16:59:53.445Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17611514254816/TestTargetResult"; [2025-10-22T16:59:53.445Z] [2025-10-22T16:59:53.445Z] TEST SETUP: [2025-10-22T16:59:53.445Z] Nothing to be done for setup. [2025-10-22T16:59:53.445Z] [2025-10-22T16:59:53.445Z] TESTING: [2025-10-22T16:59:54.240Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-10-22T16:59:54.240Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/output_17611514254816/renaissance-movie-lens_0/launcher-095953-13036391515834917173/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-10-22T16:59:54.240Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-10-22T16:59:54.240Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-10-22T16:59:58.343Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-10-22T17:00:03.129Z] 10:00:02.750 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. [2025-10-22T17:00:05.150Z] Got 100004 ratings from 671 users on 9066 movies. [2025-10-22T17:00:05.594Z] Training: 60056, validation: 20285, test: 19854 [2025-10-22T17:00:05.594Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-10-22T17:00:05.594Z] GC before operation: completed in 81.194 ms, heap usage 584.989 MB -> 75.878 MB. [2025-10-22T17:00:10.931Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:00:15.134Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:00:17.755Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:00:21.169Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:00:22.494Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:00:24.380Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:00:26.292Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:00:27.581Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:00:27.969Z] 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. [2025-10-22T17:00:27.969Z] The best model improves the baseline by 14.52%. [2025-10-22T17:00:28.344Z] Top recommended movies for user id 72: [2025-10-22T17:00:28.344Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:00:28.344Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:00:28.344Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:00:28.344Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:00:28.344Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:00:28.344Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22509.510 ms) ====== [2025-10-22T17:00:28.344Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-10-22T17:00:28.344Z] GC before operation: completed in 105.068 ms, heap usage 425.234 MB -> 91.436 MB. [2025-10-22T17:00:31.642Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:00:35.837Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:00:39.537Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:00:42.775Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:00:44.649Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:00:45.961Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:00:48.478Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:00:49.774Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:00:49.774Z] 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. [2025-10-22T17:00:50.173Z] The best model improves the baseline by 14.52%. [2025-10-22T17:00:50.173Z] Top recommended movies for user id 72: [2025-10-22T17:00:50.173Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:00:50.173Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:00:50.173Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:00:50.173Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:00:50.173Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:00:50.173Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21831.611 ms) ====== [2025-10-22T17:00:50.173Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-10-22T17:00:50.173Z] GC before operation: completed in 102.861 ms, heap usage 354.218 MB -> 88.278 MB. [2025-10-22T17:00:53.448Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:00:56.677Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:00:59.957Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:01:02.564Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:01:04.495Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:01:06.450Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:01:08.312Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:01:09.731Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:01:10.114Z] 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. [2025-10-22T17:01:10.114Z] The best model improves the baseline by 14.52%. [2025-10-22T17:01:10.496Z] Top recommended movies for user id 72: [2025-10-22T17:01:10.496Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:01:10.496Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:01:10.496Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:01:10.496Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:01:10.496Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:01:10.496Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20222.540 ms) ====== [2025-10-22T17:01:10.496Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-10-22T17:01:10.496Z] GC before operation: completed in 78.914 ms, heap usage 120.627 MB -> 88.810 MB. [2025-10-22T17:01:13.848Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:01:16.541Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:01:19.859Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:01:22.351Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:01:23.659Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:01:24.965Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:01:26.276Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:01:28.144Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:01:28.144Z] 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. [2025-10-22T17:01:28.523Z] The best model improves the baseline by 14.52%. [2025-10-22T17:01:28.523Z] Top recommended movies for user id 72: [2025-10-22T17:01:28.523Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:01:28.523Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:01:28.523Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:01:28.523Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:01:28.523Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:01:28.523Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17903.463 ms) ====== [2025-10-22T17:01:28.523Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-10-22T17:01:28.523Z] GC before operation: completed in 75.531 ms, heap usage 455.190 MB -> 89.472 MB. [2025-10-22T17:01:31.799Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:01:34.330Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:01:36.927Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:01:38.876Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:01:39.708Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:01:40.519Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:01:41.780Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:01:42.580Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:01:42.961Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-10-22T17:01:42.961Z] The best model improves the baseline by 14.52%. [2025-10-22T17:01:42.961Z] Top recommended movies for user id 72: [2025-10-22T17:01:42.961Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:01:42.961Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:01:42.961Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:01:42.961Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:01:42.961Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:01:42.961Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14503.962 ms) ====== [2025-10-22T17:01:42.961Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-10-22T17:01:42.961Z] GC before operation: completed in 84.418 ms, heap usage 254.736 MB -> 89.104 MB. [2025-10-22T17:01:45.609Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:01:47.465Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:01:50.074Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:01:52.056Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:01:53.972Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:01:55.908Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:01:57.832Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:01:59.650Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:02:00.030Z] 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. [2025-10-22T17:02:00.030Z] The best model improves the baseline by 14.52%. [2025-10-22T17:02:00.449Z] Top recommended movies for user id 72: [2025-10-22T17:02:00.449Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:02:00.449Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:02:00.449Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:02:00.449Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:02:00.449Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:02:00.449Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17242.091 ms) ====== [2025-10-22T17:02:00.449Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-10-22T17:02:00.449Z] GC before operation: completed in 111.770 ms, heap usage 345.208 MB -> 89.611 MB. [2025-10-22T17:02:03.803Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:02:08.049Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:02:10.590Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:02:13.853Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:02:16.657Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:02:19.361Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:02:22.065Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:02:25.404Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:02:25.404Z] 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. [2025-10-22T17:02:25.404Z] The best model improves the baseline by 14.52%. [2025-10-22T17:02:25.404Z] Top recommended movies for user id 72: [2025-10-22T17:02:25.404Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:02:25.404Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:02:25.404Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:02:25.404Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:02:25.404Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:02:25.404Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (25089.821 ms) ====== [2025-10-22T17:02:25.404Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-10-22T17:02:25.824Z] GC before operation: completed in 194.824 ms, heap usage 126.293 MB -> 89.177 MB. [2025-10-22T17:02:30.140Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:02:32.685Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:02:35.202Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:02:37.658Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:02:39.087Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:02:41.246Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:02:43.326Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:02:45.914Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:02:45.914Z] 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. [2025-10-22T17:02:45.914Z] The best model improves the baseline by 14.52%. [2025-10-22T17:02:45.914Z] Top recommended movies for user id 72: [2025-10-22T17:02:45.914Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:02:45.914Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:02:45.914Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:02:45.914Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:02:45.914Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:02:45.914Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20186.285 ms) ====== [2025-10-22T17:02:45.914Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-10-22T17:02:45.914Z] GC before operation: completed in 126.740 ms, heap usage 277.931 MB -> 89.726 MB. [2025-10-22T17:02:50.154Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:02:54.412Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:02:59.048Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:03:03.253Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:03:05.195Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:03:07.754Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:03:10.395Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:03:12.939Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:03:12.939Z] 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. [2025-10-22T17:03:12.939Z] The best model improves the baseline by 14.52%. [2025-10-22T17:03:12.939Z] Top recommended movies for user id 72: [2025-10-22T17:03:12.939Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:03:12.939Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:03:12.939Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:03:12.939Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:03:12.939Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:03:12.939Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (26996.091 ms) ====== [2025-10-22T17:03:12.939Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-10-22T17:03:13.313Z] GC before operation: completed in 93.155 ms, heap usage 524.894 MB -> 93.102 MB. [2025-10-22T17:03:17.351Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:03:20.626Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:03:24.748Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:03:27.955Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:03:29.227Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:03:31.691Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:03:34.218Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:03:36.779Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:03:37.173Z] 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. [2025-10-22T17:03:37.173Z] The best model improves the baseline by 14.52%. [2025-10-22T17:03:37.173Z] Top recommended movies for user id 72: [2025-10-22T17:03:37.173Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:03:37.173Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:03:37.173Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:03:37.173Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:03:37.173Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:03:37.173Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (24157.888 ms) ====== [2025-10-22T17:03:37.173Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-10-22T17:03:37.564Z] GC before operation: completed in 103.573 ms, heap usage 464.926 MB -> 90.077 MB. [2025-10-22T17:03:41.774Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:03:45.888Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:03:50.095Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:03:54.338Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:03:56.992Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:03:59.497Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:04:02.131Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:04:04.035Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:04:04.422Z] 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. [2025-10-22T17:04:04.422Z] The best model improves the baseline by 14.52%. [2025-10-22T17:04:04.422Z] Top recommended movies for user id 72: [2025-10-22T17:04:04.422Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:04:04.422Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:04:04.422Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:04:04.422Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:04:04.422Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:04:04.422Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27129.358 ms) ====== [2025-10-22T17:04:04.422Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-10-22T17:04:04.817Z] GC before operation: completed in 105.339 ms, heap usage 481.154 MB -> 89.820 MB. [2025-10-22T17:04:08.963Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:04:13.235Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:04:18.521Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:04:22.726Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:04:24.569Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:04:27.042Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:04:28.935Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:04:31.444Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:04:31.444Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-10-22T17:04:31.444Z] The best model improves the baseline by 14.52%. [2025-10-22T17:04:31.444Z] Top recommended movies for user id 72: [2025-10-22T17:04:31.444Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:04:31.444Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:04:31.444Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:04:31.444Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:04:31.444Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:04:31.444Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (26934.695 ms) ====== [2025-10-22T17:04:31.444Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-10-22T17:04:31.856Z] GC before operation: completed in 103.635 ms, heap usage 582.666 MB -> 93.299 MB. [2025-10-22T17:04:36.142Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:04:41.557Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:04:45.724Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:04:51.097Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:04:54.585Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:04:59.113Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:05:11.083Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:05:11.083Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:05:11.083Z] 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. [2025-10-22T17:05:11.083Z] The best model improves the baseline by 14.52%. [2025-10-22T17:05:11.083Z] Top recommended movies for user id 72: [2025-10-22T17:05:11.083Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:05:11.083Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:05:11.083Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:05:11.083Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:05:11.083Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:05:11.083Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36078.065 ms) ====== [2025-10-22T17:05:11.083Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-10-22T17:05:11.083Z] GC before operation: completed in 210.091 ms, heap usage 307.451 MB -> 89.828 MB. [2025-10-22T17:05:17.596Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:05:22.228Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:05:27.596Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:05:32.001Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:05:35.540Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:05:38.126Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:05:40.675Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:05:41.948Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:05:41.948Z] 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. [2025-10-22T17:05:41.948Z] The best model improves the baseline by 14.52%. [2025-10-22T17:05:42.320Z] Top recommended movies for user id 72: [2025-10-22T17:05:42.320Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:05:42.320Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:05:42.320Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:05:42.320Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:05:42.320Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:05:42.320Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (34212.183 ms) ====== [2025-10-22T17:05:42.320Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-10-22T17:05:42.320Z] GC before operation: completed in 80.364 ms, heap usage 252.203 MB -> 89.688 MB. [2025-10-22T17:05:44.228Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:05:47.470Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:05:50.090Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:05:53.306Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:05:54.596Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:05:56.426Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:05:58.245Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:06:00.715Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:06:00.715Z] 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. [2025-10-22T17:06:00.715Z] The best model improves the baseline by 14.52%. [2025-10-22T17:06:00.715Z] Top recommended movies for user id 72: [2025-10-22T17:06:00.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:06:00.715Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:06:00.715Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:06:00.715Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:06:00.715Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:06:00.715Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18586.457 ms) ====== [2025-10-22T17:06:00.715Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-10-22T17:06:01.104Z] GC before operation: completed in 89.446 ms, heap usage 402.551 MB -> 90.057 MB. [2025-10-22T17:06:04.367Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:06:06.954Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:06:09.549Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:06:11.752Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:06:13.061Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:06:14.333Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:06:15.630Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:06:16.893Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:06:17.267Z] 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. [2025-10-22T17:06:17.267Z] The best model improves the baseline by 14.52%. [2025-10-22T17:06:17.267Z] Top recommended movies for user id 72: [2025-10-22T17:06:17.267Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:06:17.267Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:06:17.267Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:06:17.267Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:06:17.267Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:06:17.267Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16440.048 ms) ====== [2025-10-22T17:06:17.267Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-10-22T17:06:17.634Z] GC before operation: completed in 93.517 ms, heap usage 204.920 MB -> 89.650 MB. [2025-10-22T17:06:20.150Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:06:22.613Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:06:25.104Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:06:26.953Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:06:28.245Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:06:29.430Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:06:30.755Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:06:32.015Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:06:32.015Z] 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. [2025-10-22T17:06:32.015Z] The best model improves the baseline by 14.52%. [2025-10-22T17:06:32.015Z] Top recommended movies for user id 72: [2025-10-22T17:06:32.015Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:06:32.015Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:06:32.015Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:06:32.015Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:06:32.015Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:06:32.015Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14647.569 ms) ====== [2025-10-22T17:06:32.015Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-10-22T17:06:32.402Z] GC before operation: completed in 95.678 ms, heap usage 411.883 MB -> 90.129 MB. [2025-10-22T17:06:35.707Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:06:39.862Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:06:43.171Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:06:44.997Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:06:46.272Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:06:47.611Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:06:48.902Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:06:50.197Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:06:50.577Z] 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. [2025-10-22T17:06:50.976Z] The best model improves the baseline by 14.52%. [2025-10-22T17:06:50.976Z] Top recommended movies for user id 72: [2025-10-22T17:06:50.976Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:06:50.976Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:06:50.976Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:06:50.976Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:06:50.976Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:06:50.976Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18708.761 ms) ====== [2025-10-22T17:06:50.976Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-10-22T17:06:50.976Z] GC before operation: completed in 140.214 ms, heap usage 1.192 GB -> 95.514 MB. [2025-10-22T17:06:56.163Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:07:00.245Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:07:03.732Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:07:07.852Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:07:09.744Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:07:11.627Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:07:14.529Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:07:16.358Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:07:16.358Z] 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. [2025-10-22T17:07:16.358Z] The best model improves the baseline by 14.52%. [2025-10-22T17:07:16.723Z] Top recommended movies for user id 72: [2025-10-22T17:07:16.723Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:07:16.723Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:07:16.723Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:07:16.723Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:07:16.723Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:07:16.723Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (25667.689 ms) ====== [2025-10-22T17:07:16.723Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-10-22T17:07:16.723Z] GC before operation: completed in 116.238 ms, heap usage 166.288 MB -> 90.601 MB. [2025-10-22T17:07:20.872Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T17:07:26.210Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T17:07:32.103Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T17:07:39.067Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T17:07:41.807Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T17:07:45.318Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T17:07:49.682Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T17:07:53.033Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T17:07:53.956Z] 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. [2025-10-22T17:07:53.956Z] The best model improves the baseline by 14.52%. [2025-10-22T17:07:54.339Z] Top recommended movies for user id 72: [2025-10-22T17:07:54.339Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-10-22T17:07:54.339Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-10-22T17:07:54.339Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-10-22T17:07:54.339Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-10-22T17:07:54.339Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-10-22T17:07:54.339Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (37340.582 ms) ====== [2025-10-22T17:07:56.216Z] ----------------------------------- [2025-10-22T17:07:56.216Z] renaissance-movie-lens_0_PASSED [2025-10-22T17:07:56.216Z] ----------------------------------- [2025-10-22T17:07:56.216Z] [2025-10-22T17:07:56.216Z] TEST TEARDOWN: [2025-10-22T17:07:56.216Z] Nothing to be done for teardown. [2025-10-22T17:07:56.216Z] renaissance-movie-lens_0 Finish Time: Wed Oct 22 10:07:55 2025 Epoch Time (ms): 1761152875815