[2025-09-05T16:57:55.009Z] Running test renaissance-movie-lens_0 ... [2025-09-05T16:57:55.009Z] =============================================== [2025-09-05T16:57:55.009Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 16:57:54 2025 Epoch Time (ms): 1757091474137 [2025-09-05T16:57:55.010Z] variation: NoOptions [2025-09-05T16:57:55.010Z] JVM_OPTIONS: [2025-09-05T16:57:55.010Z] { \ [2025-09-05T16:57:55.010Z] echo ""; echo "TEST SETUP:"; \ [2025-09-05T16:57:55.010Z] echo "Nothing to be done for setup."; \ [2025-09-05T16:57:55.010Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17570881862338/renaissance-movie-lens_0"; \ [2025-09-05T16:57:55.010Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17570881862338/renaissance-movie-lens_0"; \ [2025-09-05T16:57:55.010Z] echo ""; echo "TESTING:"; \ [2025-09-05T16:57:55.010Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_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_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17570881862338/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-05T16:57:55.010Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17570881862338/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-05T16:57:55.010Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-05T16:57:55.010Z] echo "Nothing to be done for teardown."; \ [2025-09-05T16:57:55.010Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17570881862338/TestTargetResult"; [2025-09-05T16:57:55.010Z] [2025-09-05T16:57:55.010Z] TEST SETUP: [2025-09-05T16:57:55.010Z] Nothing to be done for setup. [2025-09-05T16:57:55.010Z] [2025-09-05T16:57:55.010Z] TESTING: [2025-09-05T16:57:56.001Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-09-05T16:57:56.001Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/output_17570881862338/renaissance-movie-lens_0/launcher-165754-16584625203075381403/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-09-05T16:57:56.001Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-09-05T16:57:56.001Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-09-05T16:58:07.554Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-05T16:58:24.436Z] 16:58:24.146 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. [2025-09-05T16:58:29.817Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-05T16:58:30.809Z] Training: 60056, validation: 20285, test: 19854 [2025-09-05T16:58:30.809Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-05T16:58:30.809Z] GC before operation: completed in 284.980 ms, heap usage 177.174 MB -> 75.823 MB. [2025-09-05T16:58:46.675Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T16:58:54.948Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T16:59:03.112Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T16:59:11.334Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T16:59:15.496Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T16:59:20.914Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T16:59:25.606Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T16:59:28.601Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T16:59:29.560Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T16:59:29.560Z] The best model improves the baseline by 14.52%. [2025-09-05T16:59:30.519Z] Top recommended movies for user id 72: [2025-09-05T16:59:30.519Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T16:59:30.519Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T16:59:30.519Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T16:59:30.519Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T16:59:30.519Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T16:59:30.519Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (59369.271 ms) ====== [2025-09-05T16:59:30.519Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-05T16:59:30.519Z] GC before operation: completed in 272.248 ms, heap usage 411.929 MB -> 86.526 MB. [2025-09-05T16:59:37.232Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T16:59:43.898Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T16:59:49.280Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T16:59:55.986Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:00:01.496Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:00:05.841Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:00:11.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:00:15.645Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:00:16.618Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:00:16.618Z] The best model improves the baseline by 14.52%. [2025-09-05T17:00:16.618Z] Top recommended movies for user id 72: [2025-09-05T17:00:16.618Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:00:16.618Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:00:16.618Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:00:16.618Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:00:16.618Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:00:16.618Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (46323.221 ms) ====== [2025-09-05T17:00:16.618Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-05T17:00:17.675Z] GC before operation: completed in 357.982 ms, heap usage 737.485 MB -> 92.246 MB. [2025-09-05T17:00:25.399Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:00:33.786Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:00:39.356Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:00:46.209Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:00:50.414Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:00:55.941Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:01:00.241Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:01:04.497Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:01:04.497Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:01:04.497Z] The best model improves the baseline by 14.52%. [2025-09-05T17:01:05.523Z] Top recommended movies for user id 72: [2025-09-05T17:01:05.523Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:01:05.523Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:01:05.523Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:01:05.523Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:01:05.523Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:01:05.523Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (47951.368 ms) ====== [2025-09-05T17:01:05.523Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-05T17:01:05.523Z] GC before operation: completed in 233.979 ms, heap usage 694.671 MB -> 92.942 MB. [2025-09-05T17:01:12.344Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:01:17.825Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:01:24.046Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:01:30.995Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:01:35.275Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:01:39.501Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:01:43.748Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:01:47.994Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:01:48.987Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:01:48.987Z] The best model improves the baseline by 14.52%. [2025-09-05T17:01:49.948Z] Top recommended movies for user id 72: [2025-09-05T17:01:49.948Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:01:49.948Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:01:49.948Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:01:49.948Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:01:49.948Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:01:49.948Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (44387.734 ms) ====== [2025-09-05T17:01:49.948Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-05T17:01:49.948Z] GC before operation: completed in 324.577 ms, heap usage 794.898 MB -> 93.392 MB. [2025-09-05T17:01:58.209Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:02:05.097Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:02:11.948Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:02:20.238Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:02:24.021Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:02:28.293Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:02:32.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:02:36.734Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:02:37.715Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:02:37.715Z] The best model improves the baseline by 14.52%. [2025-09-05T17:02:37.715Z] Top recommended movies for user id 72: [2025-09-05T17:02:37.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:02:37.715Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:02:37.715Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:02:37.715Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:02:37.715Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:02:37.715Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (47808.957 ms) ====== [2025-09-05T17:02:37.715Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-05T17:02:38.669Z] GC before operation: completed in 335.183 ms, heap usage 443.431 MB -> 89.702 MB. [2025-09-05T17:02:45.625Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:02:52.434Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:03:00.683Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:03:07.692Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:03:10.918Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:03:15.194Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:03:19.401Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:03:23.314Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:03:24.273Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:03:24.273Z] The best model improves the baseline by 14.52%. [2025-09-05T17:03:24.273Z] Top recommended movies for user id 72: [2025-09-05T17:03:24.273Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:03:24.273Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:03:24.273Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:03:24.273Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:03:24.273Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:03:24.273Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (46439.768 ms) ====== [2025-09-05T17:03:24.273Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-05T17:03:25.234Z] GC before operation: completed in 296.643 ms, heap usage 214.617 MB -> 89.727 MB. [2025-09-05T17:03:31.989Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:03:37.523Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:03:44.306Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:03:51.072Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:03:54.154Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:03:58.359Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:04:02.612Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:04:05.756Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:04:06.698Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:04:06.698Z] The best model improves the baseline by 14.52%. [2025-09-05T17:04:07.654Z] Top recommended movies for user id 72: [2025-09-05T17:04:07.654Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:04:07.654Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:04:07.654Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:04:07.654Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:04:07.654Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:04:07.654Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42312.895 ms) ====== [2025-09-05T17:04:07.654Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-05T17:04:07.654Z] GC before operation: completed in 281.260 ms, heap usage 743.066 MB -> 93.697 MB. [2025-09-05T17:04:14.416Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:04:20.715Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:04:26.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:04:31.672Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:04:34.709Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:04:38.940Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:04:41.983Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:04:45.011Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:04:45.011Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:04:45.011Z] The best model improves the baseline by 14.52%. [2025-09-05T17:04:45.949Z] Top recommended movies for user id 72: [2025-09-05T17:04:45.949Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:04:45.949Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:04:45.949Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:04:45.949Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:04:45.949Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:04:45.949Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (37968.766 ms) ====== [2025-09-05T17:04:45.949Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-05T17:04:45.949Z] GC before operation: completed in 252.869 ms, heap usage 456.410 MB -> 90.325 MB. [2025-09-05T17:04:51.285Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:04:55.409Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:04:59.572Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:05:03.707Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:05:06.713Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:05:09.701Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:05:12.697Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:05:17.705Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:05:17.705Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:05:17.705Z] The best model improves the baseline by 14.52%. [2025-09-05T17:05:17.705Z] Top recommended movies for user id 72: [2025-09-05T17:05:17.705Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:05:17.705Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:05:17.705Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:05:17.705Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:05:17.705Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:05:17.706Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (32307.055 ms) ====== [2025-09-05T17:05:17.706Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-05T17:05:18.725Z] GC before operation: completed in 321.979 ms, heap usage 488.837 MB -> 90.216 MB. [2025-09-05T17:05:25.568Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:05:32.344Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:05:39.210Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:05:46.148Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:05:50.458Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:05:53.518Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:05:57.714Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:06:01.992Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:06:01.992Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:06:02.951Z] The best model improves the baseline by 14.52%. [2025-09-05T17:06:02.951Z] Top recommended movies for user id 72: [2025-09-05T17:06:02.951Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:06:02.951Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:06:02.951Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:06:02.951Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:06:02.951Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:06:02.951Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (44680.074 ms) ====== [2025-09-05T17:06:02.951Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-05T17:06:03.945Z] GC before operation: completed in 388.094 ms, heap usage 166.974 MB -> 93.444 MB. [2025-09-05T17:06:10.893Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:06:19.074Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:06:24.635Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:06:31.454Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:06:35.728Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:06:40.024Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:06:44.366Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:06:47.464Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:06:48.470Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:06:48.470Z] The best model improves the baseline by 14.52%. [2025-09-05T17:06:49.446Z] Top recommended movies for user id 72: [2025-09-05T17:06:49.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:06:49.446Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:06:49.446Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:06:49.446Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:06:49.446Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:06:49.446Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (45709.336 ms) ====== [2025-09-05T17:06:49.446Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-05T17:06:49.446Z] GC before operation: completed in 443.480 ms, heap usage 765.677 MB -> 93.670 MB. [2025-09-05T17:06:57.824Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:07:04.684Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:07:13.022Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:07:19.300Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:07:23.513Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:07:27.684Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:07:31.904Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:07:36.058Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:07:36.058Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:07:37.015Z] The best model improves the baseline by 14.52%. [2025-09-05T17:07:37.015Z] Top recommended movies for user id 72: [2025-09-05T17:07:37.015Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:07:37.015Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:07:37.015Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:07:37.015Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:07:37.015Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:07:37.015Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (47215.630 ms) ====== [2025-09-05T17:07:37.015Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-05T17:07:37.015Z] GC before operation: completed in 258.900 ms, heap usage 404.774 MB -> 90.247 MB. [2025-09-05T17:07:43.752Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:07:50.599Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:07:57.472Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:08:01.591Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:08:03.520Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:08:06.538Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:08:09.525Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:08:12.751Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:08:12.751Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:08:12.751Z] The best model improves the baseline by 14.52%. [2025-09-05T17:08:13.700Z] Top recommended movies for user id 72: [2025-09-05T17:08:13.700Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:08:13.700Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:08:13.700Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:08:13.700Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:08:13.700Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:08:13.700Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36322.220 ms) ====== [2025-09-05T17:08:13.700Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-05T17:08:13.700Z] GC before operation: completed in 245.803 ms, heap usage 99.559 MB -> 89.803 MB. [2025-09-05T17:08:17.805Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:08:22.597Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:08:26.699Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:08:30.814Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:08:32.742Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:08:35.752Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:08:38.820Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:08:40.750Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:08:41.689Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:08:41.689Z] The best model improves the baseline by 14.52%. [2025-09-05T17:08:41.689Z] Top recommended movies for user id 72: [2025-09-05T17:08:41.689Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:08:41.689Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:08:41.689Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:08:41.689Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:08:41.689Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:08:41.689Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (28023.469 ms) ====== [2025-09-05T17:08:41.689Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-05T17:08:41.689Z] GC before operation: completed in 191.929 ms, heap usage 521.324 MB -> 90.382 MB. [2025-09-05T17:08:46.999Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:08:49.991Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:08:55.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:09:00.731Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:09:02.660Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:09:05.726Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:09:08.708Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:09:10.638Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:09:10.638Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:09:12.291Z] The best model improves the baseline by 14.52%. [2025-09-05T17:09:12.292Z] Top recommended movies for user id 72: [2025-09-05T17:09:12.292Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:09:12.292Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:09:12.292Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:09:12.292Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:09:12.292Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:09:12.292Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (29621.463 ms) ====== [2025-09-05T17:09:12.292Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-05T17:09:12.292Z] GC before operation: completed in 197.654 ms, heap usage 193.394 MB -> 90.080 MB. [2025-09-05T17:09:16.404Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:09:19.379Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:09:23.505Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:09:27.598Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:09:29.525Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:09:31.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:09:34.457Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:09:36.382Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:09:36.382Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:09:36.382Z] The best model improves the baseline by 14.52%. [2025-09-05T17:09:37.321Z] Top recommended movies for user id 72: [2025-09-05T17:09:37.321Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:09:37.321Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:09:37.321Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:09:37.321Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:09:37.321Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:09:37.321Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (25252.843 ms) ====== [2025-09-05T17:09:37.321Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-05T17:09:37.321Z] GC before operation: completed in 196.765 ms, heap usage 200.673 MB -> 89.954 MB. [2025-09-05T17:09:41.439Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:09:45.540Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:09:49.662Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:09:53.773Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:09:56.747Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:09:58.690Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:10:01.675Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:10:03.617Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:10:04.677Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:10:04.677Z] The best model improves the baseline by 14.52%. [2025-09-05T17:10:05.619Z] Top recommended movies for user id 72: [2025-09-05T17:10:05.619Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:10:05.619Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:10:05.619Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:10:05.619Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:10:05.619Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:10:05.619Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (27902.422 ms) ====== [2025-09-05T17:10:05.619Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-05T17:10:05.619Z] GC before operation: completed in 226.130 ms, heap usage 123.240 MB -> 89.963 MB. [2025-09-05T17:10:10.423Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:10:14.554Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:10:18.665Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:10:22.769Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:10:25.761Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:10:28.743Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:10:30.678Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:10:33.670Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:10:33.670Z] 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. [2025-09-05T17:10:33.670Z] The best model improves the baseline by 14.52%. [2025-09-05T17:10:33.670Z] Top recommended movies for user id 72: [2025-09-05T17:10:33.670Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:10:33.670Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:10:33.670Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:10:33.670Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:10:33.670Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:10:33.670Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (28850.627 ms) ====== [2025-09-05T17:10:33.670Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-05T17:10:34.626Z] GC before operation: completed in 239.009 ms, heap usage 489.011 MB -> 90.367 MB. [2025-09-05T17:10:38.731Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:10:42.924Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:10:47.039Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:10:51.144Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:10:54.136Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:10:56.091Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:10:59.070Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:11:01.003Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:11:01.003Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:11:01.003Z] The best model improves the baseline by 14.52%. [2025-09-05T17:11:01.947Z] Top recommended movies for user id 72: [2025-09-05T17:11:01.947Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:11:01.947Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:11:01.947Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:11:01.947Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:11:01.947Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:11:01.947Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27283.148 ms) ====== [2025-09-05T17:11:01.947Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-05T17:11:01.947Z] GC before operation: completed in 189.425 ms, heap usage 369.722 MB -> 90.215 MB. [2025-09-05T17:11:06.439Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T17:11:09.418Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T17:11:13.545Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T17:11:16.517Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T17:11:18.450Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T17:11:20.379Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T17:11:23.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T17:11:25.309Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T17:11:25.309Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-05T17:11:25.309Z] The best model improves the baseline by 14.52%. [2025-09-05T17:11:25.309Z] Top recommended movies for user id 72: [2025-09-05T17:11:25.309Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-05T17:11:25.309Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-05T17:11:25.309Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-05T17:11:25.309Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-05T17:11:25.309Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-05T17:11:25.309Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (23856.267 ms) ====== [2025-09-05T17:11:27.241Z] ----------------------------------- [2025-09-05T17:11:27.241Z] renaissance-movie-lens_0_PASSED [2025-09-05T17:11:27.241Z] ----------------------------------- [2025-09-05T17:11:27.241Z] [2025-09-05T17:11:27.241Z] TEST TEARDOWN: [2025-09-05T17:11:27.241Z] Nothing to be done for teardown. [2025-09-05T17:11:27.241Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 17:11:26 2025 Epoch Time (ms): 1757092286729