[2025-11-19T23:01:43.054Z] Running test renaissance-movie-lens_0 ... [2025-11-19T23:01:43.054Z] =============================================== [2025-11-19T23:01:43.054Z] renaissance-movie-lens_0 Start Time: Wed Nov 19 23:01:42 2025 Epoch Time (ms): 1763593302478 [2025-11-19T23:01:43.054Z] variation: NoOptions [2025-11-19T23:01:43.054Z] JVM_OPTIONS: [2025-11-19T23:01:43.054Z] { \ [2025-11-19T23:01:43.054Z] echo ""; echo "TEST SETUP:"; \ [2025-11-19T23:01:43.054Z] echo "Nothing to be done for setup."; \ [2025-11-19T23:01:43.054Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17635918785997/renaissance-movie-lens_0"; \ [2025-11-19T23:01:43.054Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17635918785997/renaissance-movie-lens_0"; \ [2025-11-19T23:01:43.054Z] echo ""; echo "TESTING:"; \ [2025-11-19T23:01:43.054Z] "/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_17635918785997/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-19T23:01:43.054Z] 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_17635918785997/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-19T23:01:43.054Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-19T23:01:43.054Z] echo "Nothing to be done for teardown."; \ [2025-11-19T23:01:43.054Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17635918785997/TestTargetResult"; [2025-11-19T23:01:43.054Z] [2025-11-19T23:01:43.054Z] TEST SETUP: [2025-11-19T23:01:43.054Z] Nothing to be done for setup. [2025-11-19T23:01:43.054Z] [2025-11-19T23:01:43.054Z] TESTING: [2025-11-19T23:01:48.614Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-19T23:01:55.932Z] 23:01:54.253 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. [2025-11-19T23:01:56.902Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-19T23:01:56.902Z] Training: 60056, validation: 20285, test: 19854 [2025-11-19T23:01:56.902Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-19T23:01:56.902Z] GC before operation: completed in 122.677 ms, heap usage 140.199 MB -> 75.777 MB. [2025-11-19T23:02:02.456Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:02:05.797Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:02:08.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:02:10.907Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:02:12.877Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:02:14.890Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:02:15.850Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:02:17.819Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:02:17.819Z] 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. [2025-11-19T23:02:17.819Z] The best model improves the baseline by 14.52%. [2025-11-19T23:02:18.778Z] Top recommended movies for user id 72: [2025-11-19T23:02:18.778Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:02:18.778Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:02:18.778Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:02:18.778Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:02:18.778Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:02:18.778Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21097.171 ms) ====== [2025-11-19T23:02:18.778Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-19T23:02:18.778Z] GC before operation: completed in 131.409 ms, heap usage 380.511 MB -> 87.910 MB. [2025-11-19T23:02:20.751Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:02:23.837Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:02:27.086Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:02:29.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:02:30.165Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:02:32.594Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:02:33.591Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:02:35.644Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:02:35.644Z] 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. [2025-11-19T23:02:35.644Z] The best model improves the baseline by 14.52%. [2025-11-19T23:02:35.644Z] Top recommended movies for user id 72: [2025-11-19T23:02:35.644Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:02:35.644Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:02:35.644Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:02:35.644Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:02:35.644Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:02:35.644Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17191.205 ms) ====== [2025-11-19T23:02:35.644Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-19T23:02:35.644Z] GC before operation: completed in 128.528 ms, heap usage 221.201 MB -> 88.716 MB. [2025-11-19T23:02:38.751Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:02:40.854Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:02:42.816Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:02:45.880Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:02:49.089Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:02:49.089Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:02:50.045Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:02:52.060Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:02:52.060Z] 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. [2025-11-19T23:02:52.060Z] The best model improves the baseline by 14.52%. [2025-11-19T23:02:52.060Z] Top recommended movies for user id 72: [2025-11-19T23:02:52.060Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:02:52.060Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:02:52.060Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:02:52.061Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:02:52.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:02:52.061Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16245.893 ms) ====== [2025-11-19T23:02:52.061Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-19T23:02:52.061Z] GC before operation: completed in 124.491 ms, heap usage 489.118 MB -> 89.698 MB. [2025-11-19T23:02:54.034Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:02:57.091Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:02:59.062Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:03:01.402Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:03:02.378Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:03:04.389Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:03:05.365Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:03:07.357Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:03:07.357Z] 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. [2025-11-19T23:03:07.357Z] The best model improves the baseline by 14.52%. [2025-11-19T23:03:08.329Z] Top recommended movies for user id 72: [2025-11-19T23:03:08.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:03:08.329Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:03:08.329Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:03:08.329Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:03:08.329Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:03:08.329Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15674.379 ms) ====== [2025-11-19T23:03:08.329Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-19T23:03:08.329Z] GC before operation: completed in 137.742 ms, heap usage 372.797 MB -> 89.915 MB. [2025-11-19T23:03:10.324Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:03:12.372Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:03:15.679Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:03:17.714Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:03:18.755Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:03:20.763Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:03:21.751Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:03:23.924Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:03:23.924Z] 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. [2025-11-19T23:03:23.924Z] The best model improves the baseline by 14.52%. [2025-11-19T23:03:23.924Z] Top recommended movies for user id 72: [2025-11-19T23:03:23.924Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:03:23.924Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:03:23.924Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:03:23.924Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:03:23.924Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:03:23.924Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16057.905 ms) ====== [2025-11-19T23:03:23.924Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-19T23:03:23.924Z] GC before operation: completed in 142.919 ms, heap usage 377.918 MB -> 89.770 MB. [2025-11-19T23:03:27.064Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:03:29.065Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:03:31.068Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:03:33.116Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:03:35.100Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:03:38.102Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:03:38.102Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:03:39.064Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:03:39.064Z] 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. [2025-11-19T23:03:39.064Z] The best model improves the baseline by 14.52%. [2025-11-19T23:03:39.064Z] Top recommended movies for user id 72: [2025-11-19T23:03:39.064Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:03:39.064Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:03:39.064Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:03:39.064Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:03:39.064Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:03:39.064Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14998.333 ms) ====== [2025-11-19T23:03:39.064Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-19T23:03:39.064Z] GC before operation: completed in 127.730 ms, heap usage 396.231 MB -> 90.076 MB. [2025-11-19T23:03:41.023Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:03:44.106Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:03:46.063Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:03:48.027Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:03:48.980Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:03:50.933Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:03:51.895Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:03:53.853Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:03:53.853Z] 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. [2025-11-19T23:03:53.853Z] The best model improves the baseline by 14.52%. [2025-11-19T23:03:53.853Z] Top recommended movies for user id 72: [2025-11-19T23:03:53.853Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:03:53.853Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:03:53.853Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:03:53.853Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:03:53.853Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:03:53.853Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14936.094 ms) ====== [2025-11-19T23:03:53.853Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-19T23:03:54.805Z] GC before operation: completed in 142.207 ms, heap usage 362.705 MB -> 90.092 MB. [2025-11-19T23:03:56.800Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:03:58.781Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:04:00.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:04:02.746Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:04:03.714Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:04:05.695Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:04:06.658Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:04:07.625Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:04:07.625Z] 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. [2025-11-19T23:04:08.586Z] The best model improves the baseline by 14.52%. [2025-11-19T23:04:08.586Z] Top recommended movies for user id 72: [2025-11-19T23:04:08.586Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:04:08.586Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:04:08.586Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:04:08.586Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:04:08.586Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:04:08.586Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13891.487 ms) ====== [2025-11-19T23:04:08.586Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-19T23:04:08.586Z] GC before operation: completed in 139.027 ms, heap usage 277.589 MB -> 90.122 MB. [2025-11-19T23:04:10.556Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:04:12.529Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:04:14.504Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:04:16.475Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:04:17.434Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:04:19.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:04:20.425Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:04:21.392Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:04:22.354Z] 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. [2025-11-19T23:04:22.354Z] The best model improves the baseline by 14.52%. [2025-11-19T23:04:22.354Z] Top recommended movies for user id 72: [2025-11-19T23:04:22.354Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:04:22.354Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:04:22.354Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:04:22.354Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:04:22.354Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:04:22.354Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13863.276 ms) ====== [2025-11-19T23:04:22.354Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-19T23:04:22.354Z] GC before operation: completed in 133.022 ms, heap usage 537.241 MB -> 93.557 MB. [2025-11-19T23:04:25.090Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:04:27.398Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:04:29.377Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:04:31.353Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:04:33.323Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:04:34.283Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:04:35.243Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:04:37.215Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:04:37.215Z] 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. [2025-11-19T23:04:37.215Z] The best model improves the baseline by 14.52%. [2025-11-19T23:04:37.215Z] Top recommended movies for user id 72: [2025-11-19T23:04:37.215Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:04:37.215Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:04:37.215Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:04:37.215Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:04:37.215Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:04:37.215Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15121.589 ms) ====== [2025-11-19T23:04:37.215Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-19T23:04:37.215Z] GC before operation: completed in 125.766 ms, heap usage 204.159 MB -> 90.132 MB. [2025-11-19T23:04:40.257Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:04:42.231Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:04:44.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:04:46.169Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:04:48.138Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:04:49.099Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:04:51.073Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:04:52.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:04:53.006Z] 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. [2025-11-19T23:04:53.006Z] The best model improves the baseline by 14.52%. [2025-11-19T23:04:53.006Z] Top recommended movies for user id 72: [2025-11-19T23:04:53.006Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:04:53.006Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:04:53.006Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:04:53.006Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:04:53.006Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:04:53.006Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15183.751 ms) ====== [2025-11-19T23:04:53.006Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-19T23:04:53.006Z] GC before operation: completed in 142.168 ms, heap usage 106.543 MB -> 91.934 MB. [2025-11-19T23:04:54.992Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:04:56.976Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:05:00.033Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:05:00.996Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:05:02.978Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:05:03.938Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:05:05.956Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:05:06.926Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:05:06.926Z] 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. [2025-11-19T23:05:06.926Z] The best model improves the baseline by 14.52%. [2025-11-19T23:05:06.926Z] Top recommended movies for user id 72: [2025-11-19T23:05:06.926Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:05:06.926Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:05:06.926Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:05:06.926Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:05:06.926Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:05:06.926Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14393.309 ms) ====== [2025-11-19T23:05:06.926Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-19T23:05:07.886Z] GC before operation: completed in 181.443 ms, heap usage 293.754 MB -> 90.303 MB. [2025-11-19T23:05:09.864Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:05:12.929Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:05:15.618Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:05:16.589Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:05:18.592Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:05:19.554Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:05:21.540Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:05:22.512Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:05:23.473Z] 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. [2025-11-19T23:05:23.473Z] The best model improves the baseline by 14.52%. [2025-11-19T23:05:23.473Z] Top recommended movies for user id 72: [2025-11-19T23:05:23.473Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:05:23.473Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:05:23.473Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:05:23.473Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:05:23.473Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:05:23.473Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15794.205 ms) ====== [2025-11-19T23:05:23.473Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-19T23:05:23.473Z] GC before operation: completed in 132.616 ms, heap usage 122.494 MB -> 90.158 MB. [2025-11-19T23:05:25.478Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:05:28.519Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:05:30.491Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:05:32.463Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:05:34.580Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:05:35.543Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:05:36.522Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:05:45.571Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:05:45.571Z] 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. [2025-11-19T23:05:45.571Z] The best model improves the baseline by 14.52%. [2025-11-19T23:05:45.571Z] Top recommended movies for user id 72: [2025-11-19T23:05:45.572Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:05:45.572Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:05:45.572Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:05:45.572Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:05:45.572Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:05:45.572Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15309.960 ms) ====== [2025-11-19T23:05:45.572Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-19T23:05:45.572Z] GC before operation: completed in 116.272 ms, heap usage 285.272 MB -> 90.136 MB. [2025-11-19T23:05:45.572Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:05:45.572Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:05:45.572Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:05:47.556Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:05:48.523Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:05:50.491Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:05:51.514Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:05:53.498Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:05:53.498Z] 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. [2025-11-19T23:05:53.499Z] The best model improves the baseline by 14.52%. [2025-11-19T23:05:53.499Z] Top recommended movies for user id 72: [2025-11-19T23:05:53.499Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:05:53.499Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:05:53.499Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:05:53.499Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:05:53.499Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:05:53.499Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14597.978 ms) ====== [2025-11-19T23:05:53.499Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-19T23:05:53.499Z] GC before operation: completed in 129.534 ms, heap usage 344.324 MB -> 90.372 MB. [2025-11-19T23:05:55.504Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:05:57.484Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:05:59.463Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:06:01.438Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:06:03.411Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:06:04.371Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:06:05.335Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:06:09.122Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:06:09.122Z] 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. [2025-11-19T23:06:09.122Z] The best model improves the baseline by 14.52%. [2025-11-19T23:06:09.122Z] Top recommended movies for user id 72: [2025-11-19T23:06:09.122Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:06:09.122Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:06:09.122Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:06:09.122Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:06:09.122Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:06:09.122Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13604.622 ms) ====== [2025-11-19T23:06:09.122Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-19T23:06:09.122Z] GC before operation: completed in 143.940 ms, heap usage 481.111 MB -> 91.803 MB. [2025-11-19T23:06:09.122Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:06:11.402Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:06:13.378Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:06:15.353Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:06:17.384Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:06:18.345Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:06:19.309Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:06:21.286Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:06:21.286Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-19T23:06:21.286Z] The best model improves the baseline by 14.52%. [2025-11-19T23:06:21.286Z] Top recommended movies for user id 72: [2025-11-19T23:06:21.286Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:06:21.286Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:06:21.286Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:06:21.286Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:06:21.286Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:06:21.286Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13983.263 ms) ====== [2025-11-19T23:06:21.286Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-19T23:06:21.286Z] GC before operation: completed in 132.813 ms, heap usage 341.387 MB -> 90.388 MB. [2025-11-19T23:06:23.261Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:06:26.316Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:06:28.293Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:06:30.269Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:06:31.369Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:06:32.508Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:06:34.482Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:06:35.445Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:06:36.407Z] 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. [2025-11-19T23:06:36.407Z] The best model improves the baseline by 14.52%. [2025-11-19T23:06:36.407Z] Top recommended movies for user id 72: [2025-11-19T23:06:36.407Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:06:36.407Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:06:36.407Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:06:36.407Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:06:36.407Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:06:36.407Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14695.457 ms) ====== [2025-11-19T23:06:36.407Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-19T23:06:36.407Z] GC before operation: completed in 144.002 ms, heap usage 461.710 MB -> 90.413 MB. [2025-11-19T23:06:38.376Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:06:40.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:06:42.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:06:44.342Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:06:46.310Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:06:47.270Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:06:49.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:06:50.198Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:06:51.157Z] 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. [2025-11-19T23:06:51.157Z] The best model improves the baseline by 14.52%. [2025-11-19T23:06:51.157Z] Top recommended movies for user id 72: [2025-11-19T23:06:51.157Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:06:51.157Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:06:51.157Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:06:51.157Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:06:51.157Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:06:51.157Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14561.293 ms) ====== [2025-11-19T23:06:51.157Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-19T23:06:51.157Z] GC before operation: completed in 139.194 ms, heap usage 129.078 MB -> 90.031 MB. [2025-11-19T23:06:53.129Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:06:55.099Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:06:57.442Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:06:59.738Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:07:00.697Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:07:02.669Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:07:03.629Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:07:05.601Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:07:05.601Z] 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. [2025-11-19T23:07:05.601Z] The best model improves the baseline by 14.52%. [2025-11-19T23:07:05.601Z] Top recommended movies for user id 72: [2025-11-19T23:07:05.601Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:07:05.601Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:07:05.601Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:07:05.601Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:07:05.601Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:07:05.601Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14591.168 ms) ====== [2025-11-19T23:07:06.561Z] ----------------------------------- [2025-11-19T23:07:06.561Z] renaissance-movie-lens_0_PASSED [2025-11-19T23:07:06.561Z] ----------------------------------- [2025-11-19T23:07:06.561Z] [2025-11-19T23:07:06.561Z] TEST TEARDOWN: [2025-11-19T23:07:06.561Z] Nothing to be done for teardown. [2025-11-19T23:07:06.561Z] renaissance-movie-lens_0 Finish Time: Wed Nov 19 23:07:05 2025 Epoch Time (ms): 1763593625560