[2025-11-05T23:20:24.244Z] Running test renaissance-movie-lens_0 ... [2025-11-05T23:20:24.244Z] =============================================== [2025-11-05T23:20:24.244Z] renaissance-movie-lens_0 Start Time: Wed Nov 5 23:20:23 2025 Epoch Time (ms): 1762384823641 [2025-11-05T23:20:24.244Z] variation: NoOptions [2025-11-05T23:20:24.244Z] JVM_OPTIONS: [2025-11-05T23:20:24.244Z] { \ [2025-11-05T23:20:24.244Z] echo ""; echo "TEST SETUP:"; \ [2025-11-05T23:20:24.244Z] echo "Nothing to be done for setup."; \ [2025-11-05T23:20:24.244Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623833915665/renaissance-movie-lens_0"; \ [2025-11-05T23:20:24.244Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623833915665/renaissance-movie-lens_0"; \ [2025-11-05T23:20:24.244Z] echo ""; echo "TESTING:"; \ [2025-11-05T23:20:24.244Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_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_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623833915665/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-05T23:20:24.244Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623833915665/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-05T23:20:24.244Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-05T23:20:24.244Z] echo "Nothing to be done for teardown."; \ [2025-11-05T23:20:24.244Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623833915665/TestTargetResult"; [2025-11-05T23:20:24.244Z] [2025-11-05T23:20:24.244Z] TEST SETUP: [2025-11-05T23:20:24.244Z] Nothing to be done for setup. [2025-11-05T23:20:24.244Z] [2025-11-05T23:20:24.244Z] TESTING: [2025-11-05T23:20:29.598Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-05T23:20:36.288Z] 23:20:35.503 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-11-05T23:20:38.274Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-05T23:20:38.274Z] Training: 60056, validation: 20285, test: 19854 [2025-11-05T23:20:38.274Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-05T23:20:38.274Z] GC before operation: completed in 132.208 ms, heap usage 202.441 MB -> 75.725 MB. [2025-11-05T23:20:43.637Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:20:47.790Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:20:50.816Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:20:52.784Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:20:54.753Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:20:56.718Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:20:58.686Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:20:59.640Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:20:59.640Z] 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. [2025-11-05T23:21:00.602Z] The best model improves the baseline by 14.52%. [2025-11-05T23:21:00.602Z] Top recommended movies for user id 72: [2025-11-05T23:21:00.602Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:21:00.602Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:21:00.602Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:21:00.602Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:21:00.602Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:21:00.602Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21692.828 ms) ====== [2025-11-05T23:21:00.602Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-05T23:21:00.602Z] GC before operation: completed in 140.045 ms, heap usage 262.622 MB -> 94.157 MB. [2025-11-05T23:21:03.646Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:21:05.757Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:21:07.724Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:21:10.866Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:21:11.824Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:21:13.792Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:21:14.745Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:21:16.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:21:16.694Z] 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. [2025-11-05T23:21:16.694Z] The best model improves the baseline by 14.52%. [2025-11-05T23:21:16.694Z] Top recommended movies for user id 72: [2025-11-05T23:21:16.694Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:21:16.694Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:21:16.694Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:21:16.694Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:21:16.694Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:21:16.694Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16341.592 ms) ====== [2025-11-05T23:21:16.694Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-05T23:21:16.694Z] GC before operation: completed in 126.225 ms, heap usage 366.646 MB -> 88.809 MB. [2025-11-05T23:21:19.705Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:21:21.665Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:21:24.685Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:21:26.636Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:21:27.587Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:21:29.536Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:21:31.564Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:21:32.524Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:21:32.524Z] 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. [2025-11-05T23:21:32.524Z] The best model improves the baseline by 14.52%. [2025-11-05T23:21:32.524Z] Top recommended movies for user id 72: [2025-11-05T23:21:32.524Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:21:32.524Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:21:32.524Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:21:32.524Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:21:32.524Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:21:32.524Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15849.073 ms) ====== [2025-11-05T23:21:32.524Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-05T23:21:33.475Z] GC before operation: completed in 112.738 ms, heap usage 346.634 MB -> 89.367 MB. [2025-11-05T23:21:35.600Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:21:37.560Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:21:40.579Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:21:42.596Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:21:44.563Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:21:45.523Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:21:47.490Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:21:49.451Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:21:49.451Z] 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. [2025-11-05T23:21:49.451Z] The best model improves the baseline by 14.52%. [2025-11-05T23:21:49.451Z] Top recommended movies for user id 72: [2025-11-05T23:21:49.451Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:21:49.451Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:21:49.451Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:21:49.451Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:21:49.451Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:21:49.451Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16630.828 ms) ====== [2025-11-05T23:21:49.451Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-05T23:21:49.451Z] GC before operation: completed in 141.130 ms, heap usage 116.080 MB -> 89.394 MB. [2025-11-05T23:21:52.464Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:21:54.414Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:21:57.438Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:22:00.508Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:22:01.812Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:22:02.783Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:22:04.761Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:22:05.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:22:05.724Z] 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. [2025-11-05T23:22:05.724Z] The best model improves the baseline by 14.52%. [2025-11-05T23:22:06.700Z] Top recommended movies for user id 72: [2025-11-05T23:22:06.700Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:22:06.700Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:22:06.700Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:22:06.700Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:22:06.700Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:22:06.700Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16457.034 ms) ====== [2025-11-05T23:22:06.700Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-05T23:22:06.700Z] GC before operation: completed in 128.008 ms, heap usage 289.270 MB -> 89.617 MB. [2025-11-05T23:22:08.681Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:22:11.709Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:22:13.666Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:22:15.722Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:22:17.704Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:22:18.660Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:22:20.625Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:22:21.586Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:22:22.547Z] 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. [2025-11-05T23:22:22.547Z] The best model improves the baseline by 14.52%. [2025-11-05T23:22:22.547Z] Top recommended movies for user id 72: [2025-11-05T23:22:22.547Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:22:22.547Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:22:22.547Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:22:22.547Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:22:22.547Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:22:22.547Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16049.060 ms) ====== [2025-11-05T23:22:22.547Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-05T23:22:22.547Z] GC before operation: completed in 121.233 ms, heap usage 119.592 MB -> 89.613 MB. [2025-11-05T23:22:24.523Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:22:26.497Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:22:29.520Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:22:31.497Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:22:32.453Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:22:34.420Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:22:35.393Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:22:37.353Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:22:37.353Z] 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. [2025-11-05T23:22:37.353Z] The best model improves the baseline by 14.52%. [2025-11-05T23:22:37.353Z] Top recommended movies for user id 72: [2025-11-05T23:22:37.353Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:22:37.353Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:22:37.353Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:22:37.353Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:22:37.353Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:22:37.353Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15156.593 ms) ====== [2025-11-05T23:22:37.353Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-05T23:22:37.353Z] GC before operation: completed in 126.389 ms, heap usage 360.978 MB -> 90.008 MB. [2025-11-05T23:22:40.360Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:22:42.342Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:22:45.355Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:22:47.307Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:22:49.264Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:22:50.214Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:22:52.166Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:22:54.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:22:54.115Z] 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. [2025-11-05T23:22:54.115Z] The best model improves the baseline by 14.52%. [2025-11-05T23:22:54.115Z] Top recommended movies for user id 72: [2025-11-05T23:22:54.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:22:54.115Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:22:54.115Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:22:54.115Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:22:54.115Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:22:54.115Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16497.507 ms) ====== [2025-11-05T23:22:54.115Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-05T23:22:54.115Z] GC before operation: completed in 136.485 ms, heap usage 98.771 MB -> 89.728 MB. [2025-11-05T23:22:57.128Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:22:59.081Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:23:01.165Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:23:03.115Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:23:05.061Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:23:06.025Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:23:07.974Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:23:08.925Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:23:09.879Z] 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. [2025-11-05T23:23:09.879Z] The best model improves the baseline by 14.52%. [2025-11-05T23:23:09.879Z] Top recommended movies for user id 72: [2025-11-05T23:23:09.879Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:23:09.879Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:23:09.879Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:23:09.879Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:23:09.879Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:23:09.879Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15237.741 ms) ====== [2025-11-05T23:23:09.879Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-05T23:23:09.879Z] GC before operation: completed in 117.898 ms, heap usage 431.742 MB -> 90.278 MB. [2025-11-05T23:23:11.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:23:14.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:23:16.826Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:23:18.781Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:23:20.729Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:23:21.678Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:23:23.626Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:23:24.578Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:23:24.578Z] 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. [2025-11-05T23:23:25.526Z] The best model improves the baseline by 14.52%. [2025-11-05T23:23:25.526Z] Top recommended movies for user id 72: [2025-11-05T23:23:25.526Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:23:25.526Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:23:25.526Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:23:25.526Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:23:25.526Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:23:25.526Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15405.187 ms) ====== [2025-11-05T23:23:25.526Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-05T23:23:25.526Z] GC before operation: completed in 115.614 ms, heap usage 398.086 MB -> 90.339 MB. [2025-11-05T23:23:27.482Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:23:29.430Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:23:32.518Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:23:34.467Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:23:35.418Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:23:37.371Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:23:38.325Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:23:39.273Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:23:40.226Z] 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. [2025-11-05T23:23:40.226Z] The best model improves the baseline by 14.52%. [2025-11-05T23:23:40.226Z] Top recommended movies for user id 72: [2025-11-05T23:23:40.226Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:23:40.226Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:23:40.226Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:23:40.226Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:23:40.226Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:23:40.226Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14733.736 ms) ====== [2025-11-05T23:23:40.226Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-05T23:23:40.226Z] GC before operation: completed in 118.479 ms, heap usage 211.256 MB -> 89.818 MB. [2025-11-05T23:23:42.176Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:23:45.211Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:23:47.167Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:23:49.125Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:23:51.100Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:23:53.089Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:23:54.056Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:23:55.010Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:23:55.010Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-05T23:23:55.010Z] The best model improves the baseline by 14.52%. [2025-11-05T23:23:55.967Z] Top recommended movies for user id 72: [2025-11-05T23:23:55.967Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:23:55.967Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:23:55.967Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:23:55.967Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:23:55.967Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:23:55.967Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15315.504 ms) ====== [2025-11-05T23:23:55.967Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-05T23:23:55.967Z] GC before operation: completed in 145.427 ms, heap usage 193.409 MB -> 89.961 MB. [2025-11-05T23:23:57.939Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:23:59.900Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:24:01.861Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:24:03.833Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:24:05.796Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:24:06.746Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:24:08.705Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:24:09.670Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:24:09.670Z] 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. [2025-11-05T23:24:09.670Z] The best model improves the baseline by 14.52%. [2025-11-05T23:24:09.670Z] Top recommended movies for user id 72: [2025-11-05T23:24:09.670Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:24:09.670Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:24:09.670Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:24:09.670Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:24:09.670Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:24:09.670Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14472.126 ms) ====== [2025-11-05T23:24:09.670Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-05T23:24:10.625Z] GC before operation: completed in 140.930 ms, heap usage 764.262 MB -> 94.150 MB. [2025-11-05T23:24:12.624Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:24:14.595Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:24:17.637Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:24:19.608Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:24:20.567Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:24:22.547Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:24:23.510Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:24:27.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:24:27.176Z] 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. [2025-11-05T23:24:27.176Z] The best model improves the baseline by 14.52%. [2025-11-05T23:24:27.176Z] Top recommended movies for user id 72: [2025-11-05T23:24:27.176Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:24:27.176Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:24:27.176Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:24:27.176Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:24:27.176Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:24:27.176Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15067.448 ms) ====== [2025-11-05T23:24:27.176Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-05T23:24:27.176Z] GC before operation: completed in 138.468 ms, heap usage 290.705 MB -> 90.087 MB. [2025-11-05T23:24:28.298Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:24:30.427Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:24:32.555Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:24:34.506Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:24:35.457Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:24:37.405Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:24:38.358Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:24:40.315Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:24:40.315Z] 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. [2025-11-05T23:24:40.315Z] The best model improves the baseline by 14.52%. [2025-11-05T23:24:40.315Z] Top recommended movies for user id 72: [2025-11-05T23:24:40.315Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:24:40.315Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:24:40.315Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:24:40.315Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:24:40.315Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:24:40.315Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15004.142 ms) ====== [2025-11-05T23:24:40.315Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-05T23:24:40.315Z] GC before operation: completed in 144.455 ms, heap usage 343.849 MB -> 90.205 MB. [2025-11-05T23:24:43.323Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:24:45.277Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:24:47.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:24:49.180Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:24:51.130Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:24:52.951Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:24:54.413Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:24:54.413Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:24:55.365Z] 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. [2025-11-05T23:24:55.365Z] The best model improves the baseline by 14.52%. [2025-11-05T23:24:55.365Z] Top recommended movies for user id 72: [2025-11-05T23:24:55.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:24:55.365Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:24:55.365Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:24:55.365Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:24:55.365Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:24:55.365Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14455.890 ms) ====== [2025-11-05T23:24:55.365Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-05T23:24:55.365Z] GC before operation: completed in 128.736 ms, heap usage 282.410 MB -> 90.143 MB. [2025-11-05T23:24:57.316Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:24:59.267Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:25:02.283Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:25:04.233Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:25:05.367Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:25:06.317Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:25:08.278Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:25:09.234Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:25:09.234Z] 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. [2025-11-05T23:25:09.234Z] The best model improves the baseline by 14.52%. [2025-11-05T23:25:10.192Z] Top recommended movies for user id 72: [2025-11-05T23:25:10.192Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:25:10.192Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:25:10.192Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:25:10.192Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:25:10.192Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:25:10.192Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14565.439 ms) ====== [2025-11-05T23:25:10.192Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-05T23:25:10.192Z] GC before operation: completed in 124.181 ms, heap usage 358.103 MB -> 90.337 MB. [2025-11-05T23:25:12.142Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:25:14.092Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:25:16.042Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:25:17.993Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:25:20.002Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:25:20.967Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:25:21.933Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:25:23.903Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:25:23.903Z] 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. [2025-11-05T23:25:23.903Z] The best model improves the baseline by 14.52%. [2025-11-05T23:25:23.903Z] Top recommended movies for user id 72: [2025-11-05T23:25:23.903Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:25:23.903Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:25:23.903Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:25:23.903Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:25:23.903Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:25:23.903Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14103.518 ms) ====== [2025-11-05T23:25:23.903Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-05T23:25:23.903Z] GC before operation: completed in 121.686 ms, heap usage 165.728 MB -> 89.882 MB. [2025-11-05T23:25:25.872Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:25:28.906Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:25:30.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:25:32.880Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:25:34.855Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:25:35.956Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:25:36.934Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:25:38.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:25:38.913Z] 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. [2025-11-05T23:25:38.913Z] The best model improves the baseline by 14.52%. [2025-11-05T23:25:38.913Z] Top recommended movies for user id 72: [2025-11-05T23:25:38.913Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:25:38.913Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:25:38.913Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:25:38.913Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:25:38.913Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:25:38.913Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15142.345 ms) ====== [2025-11-05T23:25:38.913Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-05T23:25:39.874Z] GC before operation: completed in 124.779 ms, heap usage 286.248 MB -> 90.190 MB. [2025-11-05T23:25:41.861Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-05T23:25:43.835Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-05T23:25:47.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-05T23:25:48.039Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-05T23:25:50.030Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-05T23:25:50.986Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-05T23:25:51.935Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-05T23:25:53.892Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-05T23:25:53.892Z] 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. [2025-11-05T23:25:53.892Z] The best model improves the baseline by 14.52%. [2025-11-05T23:25:53.892Z] Top recommended movies for user id 72: [2025-11-05T23:25:53.892Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-05T23:25:53.892Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-05T23:25:53.892Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-05T23:25:53.892Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-05T23:25:53.892Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-05T23:25:53.892Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14623.896 ms) ====== [2025-11-05T23:25:54.842Z] ----------------------------------- [2025-11-05T23:25:54.842Z] renaissance-movie-lens_0_PASSED [2025-11-05T23:25:54.842Z] ----------------------------------- [2025-11-05T23:25:54.842Z] [2025-11-05T23:25:54.842Z] TEST TEARDOWN: [2025-11-05T23:25:54.842Z] Nothing to be done for teardown. [2025-11-05T23:25:54.842Z] renaissance-movie-lens_0 Finish Time: Wed Nov 5 23:25:54 2025 Epoch Time (ms): 1762385154035