[2025-09-03T22:25:08.233Z] Running test renaissance-movie-lens_0 ... [2025-09-03T22:25:08.233Z] =============================================== [2025-09-03T22:25:08.233Z] renaissance-movie-lens_0 Start Time: Wed Sep 3 22:25:07 2025 Epoch Time (ms): 1756938307737 [2025-09-03T22:25:08.233Z] variation: NoOptions [2025-09-03T22:25:08.233Z] JVM_OPTIONS: [2025-09-03T22:25:08.233Z] { \ [2025-09-03T22:25:08.233Z] echo ""; echo "TEST SETUP:"; \ [2025-09-03T22:25:08.233Z] echo "Nothing to be done for setup."; \ [2025-09-03T22:25:08.233Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17569356508969/renaissance-movie-lens_0"; \ [2025-09-03T22:25:08.233Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17569356508969/renaissance-movie-lens_0"; \ [2025-09-03T22:25:08.233Z] echo ""; echo "TESTING:"; \ [2025-09-03T22:25:08.233Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/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 "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17569356508969/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-03T22:25:08.233Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17569356508969/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-03T22:25:08.233Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-03T22:25:08.233Z] echo "Nothing to be done for teardown."; \ [2025-09-03T22:25:08.233Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17569356508969/TestTargetResult"; [2025-09-03T22:25:08.233Z] [2025-09-03T22:25:08.233Z] TEST SETUP: [2025-09-03T22:25:08.233Z] Nothing to be done for setup. [2025-09-03T22:25:08.233Z] [2025-09-03T22:25:08.233Z] TESTING: [2025-09-03T22:25:17.952Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-03T22:25:31.577Z] 22:25:31.402 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-09-03T22:25:35.949Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-03T22:25:37.206Z] Training: 60056, validation: 20285, test: 19854 [2025-09-03T22:25:37.206Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-03T22:25:37.206Z] GC before operation: completed in 214.405 ms, heap usage 460.673 MB -> 76.182 MB. [2025-09-03T22:25:53.230Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:26:00.143Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:26:08.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:26:16.494Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:26:19.848Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:26:24.362Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:26:28.813Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:26:32.165Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:26:32.921Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:26:33.692Z] The best model improves the baseline by 14.52%. [2025-09-03T22:26:33.692Z] Top recommended movies for user id 72: [2025-09-03T22:26:33.692Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:26:33.692Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:26:33.692Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:26:33.692Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:26:33.692Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:26:33.692Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (56534.682 ms) ====== [2025-09-03T22:26:33.692Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-03T22:26:34.446Z] GC before operation: completed in 326.820 ms, heap usage 135.358 MB -> 91.551 MB. [2025-09-03T22:26:41.218Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:26:47.370Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:26:52.897Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:26:58.426Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:27:01.783Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:27:05.138Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:27:08.514Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:27:11.873Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:27:12.623Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:27:12.623Z] The best model improves the baseline by 14.52%. [2025-09-03T22:27:12.623Z] Top recommended movies for user id 72: [2025-09-03T22:27:12.623Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:27:12.623Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:27:12.623Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:27:12.623Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:27:12.623Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:27:12.623Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (38554.859 ms) ====== [2025-09-03T22:27:12.623Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-03T22:27:13.379Z] GC before operation: completed in 228.747 ms, heap usage 218.564 MB -> 92.226 MB. [2025-09-03T22:27:20.147Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:27:24.623Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:27:31.396Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:27:36.917Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:27:40.295Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:27:43.670Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:27:47.029Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:27:49.993Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:27:49.993Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:27:50.748Z] The best model improves the baseline by 14.52%. [2025-09-03T22:27:50.748Z] Top recommended movies for user id 72: [2025-09-03T22:27:50.748Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:27:50.748Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:27:50.748Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:27:50.748Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:27:50.748Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:27:50.748Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (37503.540 ms) ====== [2025-09-03T22:27:50.748Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-03T22:27:50.748Z] GC before operation: completed in 240.748 ms, heap usage 169.079 MB -> 91.645 MB. [2025-09-03T22:27:55.137Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:28:00.739Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:28:05.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:28:09.468Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:28:12.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:28:16.224Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:28:19.588Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:28:22.930Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:28:22.930Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:28:23.715Z] The best model improves the baseline by 14.52%. [2025-09-03T22:28:23.715Z] Top recommended movies for user id 72: [2025-09-03T22:28:23.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:28:23.715Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:28:23.715Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:28:23.715Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:28:23.715Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:28:23.715Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (32759.430 ms) ====== [2025-09-03T22:28:23.715Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-03T22:28:23.715Z] GC before operation: completed in 229.149 ms, heap usage 165.369 MB -> 89.690 MB. [2025-09-03T22:28:29.231Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:28:34.733Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:28:40.241Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:28:44.690Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:28:48.044Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:28:51.679Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:28:54.100Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:28:56.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:28:57.293Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:28:57.293Z] The best model improves the baseline by 14.52%. [2025-09-03T22:28:58.047Z] Top recommended movies for user id 72: [2025-09-03T22:28:58.047Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:28:58.047Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:28:58.047Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:28:58.047Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:28:58.047Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:28:58.047Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (33833.010 ms) ====== [2025-09-03T22:28:58.047Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-03T22:28:58.047Z] GC before operation: completed in 234.084 ms, heap usage 356.363 MB -> 90.071 MB. [2025-09-03T22:29:04.824Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:29:10.344Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:29:15.869Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:29:20.238Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:29:23.598Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:29:26.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:29:29.378Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:29:31.820Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:29:32.582Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:29:32.582Z] The best model improves the baseline by 14.52%. [2025-09-03T22:29:32.582Z] Top recommended movies for user id 72: [2025-09-03T22:29:32.582Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:29:32.582Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:29:32.582Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:29:32.582Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:29:32.582Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:29:32.582Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (34711.520 ms) ====== [2025-09-03T22:29:32.582Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-03T22:29:32.582Z] GC before operation: completed in 219.127 ms, heap usage 286.439 MB -> 93.761 MB. [2025-09-03T22:29:38.095Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:29:42.472Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:29:48.005Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:29:52.901Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:29:56.272Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:29:58.708Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:30:02.086Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:30:04.545Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:30:05.299Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:30:05.299Z] The best model improves the baseline by 14.52%. [2025-09-03T22:30:05.299Z] Top recommended movies for user id 72: [2025-09-03T22:30:05.299Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:30:05.299Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:30:05.299Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:30:05.299Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:30:05.299Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:30:05.299Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (32525.242 ms) ====== [2025-09-03T22:30:05.299Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-03T22:30:06.050Z] GC before operation: completed in 262.981 ms, heap usage 243.300 MB -> 93.306 MB. [2025-09-03T22:30:10.424Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:30:15.924Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:30:20.310Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:30:24.743Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:30:28.099Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:30:30.528Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:30:32.946Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:30:36.301Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:30:36.301Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:30:36.301Z] The best model improves the baseline by 14.52%. [2025-09-03T22:30:37.058Z] Top recommended movies for user id 72: [2025-09-03T22:30:37.058Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:30:37.058Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:30:37.058Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:30:37.058Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:30:37.058Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:30:37.058Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (31018.049 ms) ====== [2025-09-03T22:30:37.058Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-03T22:30:37.058Z] GC before operation: completed in 216.500 ms, heap usage 364.540 MB -> 92.859 MB. [2025-09-03T22:30:42.576Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:30:48.163Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:30:51.784Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:30:57.419Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:30:59.831Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:31:03.203Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:31:06.558Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:31:08.992Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:31:09.753Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:31:09.753Z] The best model improves the baseline by 14.52%. [2025-09-03T22:31:09.753Z] Top recommended movies for user id 72: [2025-09-03T22:31:09.753Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:31:09.753Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:31:09.753Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:31:09.753Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:31:09.753Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:31:09.753Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (33106.818 ms) ====== [2025-09-03T22:31:09.753Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-03T22:31:10.521Z] GC before operation: completed in 302.733 ms, heap usage 276.372 MB -> 90.101 MB. [2025-09-03T22:31:16.051Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:31:20.445Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:31:25.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:31:30.350Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:31:32.819Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:31:36.166Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:31:38.601Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:31:41.025Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:31:41.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:31:41.782Z] The best model improves the baseline by 14.52%. [2025-09-03T22:31:42.535Z] Top recommended movies for user id 72: [2025-09-03T22:31:42.535Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:31:42.535Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:31:42.535Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:31:42.535Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:31:42.535Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:31:42.535Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (31982.515 ms) ====== [2025-09-03T22:31:42.536Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-03T22:31:42.536Z] GC before operation: completed in 220.310 ms, heap usage 230.871 MB -> 90.247 MB. [2025-09-03T22:31:48.552Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:31:51.894Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:31:57.427Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:32:01.812Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:32:05.166Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:32:07.604Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:32:10.980Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:32:13.381Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:32:14.138Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:32:14.138Z] The best model improves the baseline by 14.52%. [2025-09-03T22:32:14.138Z] Top recommended movies for user id 72: [2025-09-03T22:32:14.138Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:32:14.138Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:32:14.138Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:32:14.138Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:32:14.138Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:32:14.138Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (31749.712 ms) ====== [2025-09-03T22:32:14.138Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-03T22:32:14.888Z] GC before operation: completed in 286.836 ms, heap usage 266.031 MB -> 90.084 MB. [2025-09-03T22:32:20.379Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:32:24.786Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:32:29.166Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:32:33.556Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:32:35.985Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:32:39.327Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:32:42.684Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:32:45.101Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:32:45.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:32:45.872Z] The best model improves the baseline by 14.52%. [2025-09-03T22:32:45.872Z] Top recommended movies for user id 72: [2025-09-03T22:32:45.872Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:32:45.872Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:32:45.872Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:32:45.872Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:32:45.872Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:32:45.872Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (31286.720 ms) ====== [2025-09-03T22:32:45.872Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-03T22:32:45.872Z] GC before operation: completed in 305.630 ms, heap usage 522.505 MB -> 90.631 MB. [2025-09-03T22:32:50.835Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:32:56.338Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:33:01.840Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:33:06.251Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:33:09.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:33:12.971Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:33:15.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:33:18.733Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:33:18.733Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:33:19.493Z] The best model improves the baseline by 14.52%. [2025-09-03T22:33:19.493Z] Top recommended movies for user id 72: [2025-09-03T22:33:19.493Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:33:19.493Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:33:19.493Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:33:19.493Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:33:19.493Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:33:19.493Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (33270.122 ms) ====== [2025-09-03T22:33:19.493Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-03T22:33:19.493Z] GC before operation: completed in 332.777 ms, heap usage 358.305 MB -> 90.496 MB. [2025-09-03T22:33:25.003Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:33:30.489Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:33:34.871Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:33:39.255Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:33:42.603Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:33:45.034Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:33:48.913Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:33:52.287Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:33:53.040Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:33:53.040Z] The best model improves the baseline by 14.52%. [2025-09-03T22:33:53.810Z] Top recommended movies for user id 72: [2025-09-03T22:33:53.810Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:33:53.810Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:33:53.810Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:33:53.810Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:33:53.810Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:33:53.810Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (33768.958 ms) ====== [2025-09-03T22:33:53.810Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-03T22:33:53.810Z] GC before operation: completed in 282.007 ms, heap usage 279.655 MB -> 90.174 MB. [2025-09-03T22:34:01.970Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:34:06.338Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:34:11.862Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:34:16.238Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:34:18.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:34:22.044Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:34:24.485Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:34:27.854Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:34:28.612Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:34:28.612Z] The best model improves the baseline by 14.52%. [2025-09-03T22:34:28.612Z] Top recommended movies for user id 72: [2025-09-03T22:34:28.612Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:34:28.612Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:34:28.612Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:34:28.612Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:34:28.612Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:34:28.612Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (34941.096 ms) ====== [2025-09-03T22:34:28.612Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-03T22:34:29.359Z] GC before operation: completed in 276.646 ms, heap usage 211.061 MB -> 90.475 MB. [2025-09-03T22:34:37.539Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:34:43.059Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:34:47.449Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:34:53.607Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:34:56.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:34:59.383Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:35:02.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:35:05.251Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:35:05.997Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:35:05.997Z] The best model improves the baseline by 14.52%. [2025-09-03T22:35:05.997Z] Top recommended movies for user id 72: [2025-09-03T22:35:05.997Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:35:05.997Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:35:05.997Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:35:05.997Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:35:05.997Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:35:05.997Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (37028.869 ms) ====== [2025-09-03T22:35:05.997Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-03T22:35:05.997Z] GC before operation: completed in 288.275 ms, heap usage 717.292 MB -> 95.919 MB. [2025-09-03T22:35:11.532Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:35:17.031Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:35:21.453Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:35:25.861Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:35:29.231Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:35:32.592Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:35:35.956Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:35:38.380Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:35:39.125Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:35:39.125Z] The best model improves the baseline by 14.52%. [2025-09-03T22:35:39.125Z] Top recommended movies for user id 72: [2025-09-03T22:35:39.125Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:35:39.125Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:35:39.125Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:35:39.125Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:35:39.125Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:35:39.125Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (32925.184 ms) ====== [2025-09-03T22:35:39.125Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-03T22:35:39.879Z] GC before operation: completed in 213.947 ms, heap usage 610.394 MB -> 94.050 MB. [2025-09-03T22:35:45.428Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:35:49.310Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:35:54.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:35:59.355Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:36:01.793Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:36:05.146Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:36:07.574Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:36:10.940Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:36:11.691Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:36:11.691Z] The best model improves the baseline by 14.52%. [2025-09-03T22:36:12.446Z] Top recommended movies for user id 72: [2025-09-03T22:36:12.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:36:12.446Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:36:12.446Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:36:12.446Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:36:12.446Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:36:12.446Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (32685.688 ms) ====== [2025-09-03T22:36:12.446Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-03T22:36:12.446Z] GC before operation: completed in 250.500 ms, heap usage 530.994 MB -> 93.805 MB. [2025-09-03T22:36:19.178Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:36:23.601Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:36:28.021Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:36:33.588Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:36:36.943Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:36:41.306Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:36:44.670Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:36:47.103Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:36:47.859Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:36:47.859Z] The best model improves the baseline by 14.52%. [2025-09-03T22:36:47.859Z] Top recommended movies for user id 72: [2025-09-03T22:36:47.859Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:36:47.859Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:36:47.859Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:36:47.859Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:36:47.859Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:36:47.859Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (35673.995 ms) ====== [2025-09-03T22:36:47.859Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-03T22:36:52.648Z] GC before operation: completed in 349.057 ms, heap usage 526.421 MB -> 90.634 MB. [2025-09-03T22:36:57.173Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T22:37:02.676Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T22:37:07.041Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T22:37:11.412Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T22:37:13.831Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T22:37:16.259Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T22:37:19.601Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T22:37:22.023Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T22:37:22.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-03T22:37:22.782Z] The best model improves the baseline by 14.52%. [2025-09-03T22:37:23.594Z] Top recommended movies for user id 72: [2025-09-03T22:37:23.594Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-03T22:37:23.594Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-03T22:37:23.594Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-03T22:37:23.594Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-03T22:37:23.594Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-03T22:37:23.594Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (34710.780 ms) ====== [2025-09-03T22:37:24.346Z] ----------------------------------- [2025-09-03T22:37:24.346Z] renaissance-movie-lens_0_PASSED [2025-09-03T22:37:24.346Z] ----------------------------------- [2025-09-03T22:37:24.346Z] [2025-09-03T22:37:24.346Z] TEST TEARDOWN: [2025-09-03T22:37:24.346Z] Nothing to be done for teardown. [2025-09-03T22:37:24.346Z] renaissance-movie-lens_0 Finish Time: Wed Sep 3 22:37:23 2025 Epoch Time (ms): 1756939043693