[2025-11-29T13:30:49.125Z] Running test renaissance-movie-lens_0 ... [2025-11-29T13:30:49.125Z] =============================================== [2025-11-29T13:30:49.125Z] renaissance-movie-lens_0 Start Time: Sat Nov 29 08:30:49 2025 Epoch Time (ms): 1764423049040 [2025-11-29T13:30:49.125Z] variation: NoOptions [2025-11-29T13:30:49.125Z] JVM_OPTIONS: [2025-11-29T13:30:49.125Z] { \ [2025-11-29T13:30:49.125Z] echo ""; echo "TEST SETUP:"; \ [2025-11-29T13:30:49.125Z] echo "Nothing to be done for setup."; \ [2025-11-29T13:30:49.125Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1764420376198/renaissance-movie-lens_0"; \ [2025-11-29T13:30:49.126Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1764420376198/renaissance-movie-lens_0"; \ [2025-11-29T13:30:49.126Z] echo ""; echo "TESTING:"; \ [2025-11-29T13:30:49.126Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_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_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1764420376198/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-29T13:30:49.126Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1764420376198/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-29T13:30:49.126Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-29T13:30:49.126Z] echo "Nothing to be done for teardown."; \ [2025-11-29T13:30:49.126Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1764420376198/TestTargetResult"; [2025-11-29T13:30:49.126Z] [2025-11-29T13:30:49.126Z] TEST SETUP: [2025-11-29T13:30:49.126Z] Nothing to be done for setup. [2025-11-29T13:30:49.126Z] [2025-11-29T13:30:49.126Z] TESTING: [2025-11-29T13:30:49.841Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-11-29T13:30:49.841Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/output_1764420376198/renaissance-movie-lens_0/launcher-083049-3984765736879609494/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-11-29T13:30:49.841Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-11-29T13:30:49.841Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-11-29T13:30:56.247Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-11-29T13:31:04.187Z] 08:31:02.980 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-11-29T13:31:06.492Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-29T13:31:07.250Z] Training: 60056, validation: 20285, test: 19854 [2025-11-29T13:31:07.250Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-29T13:31:07.975Z] GC before operation: completed in 457.424 ms, heap usage 186.391 MB -> 75.559 MB. [2025-11-29T13:31:19.031Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:31:24.283Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:31:29.941Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:31:33.050Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:31:36.155Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:31:38.474Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:31:41.571Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:31:43.841Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:31:44.540Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:31:44.540Z] The best model improves the baseline by 14.34%. [2025-11-29T13:31:44.540Z] Top recommended movies for user id 72: [2025-11-29T13:31:44.540Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:31:44.540Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:31:44.540Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:31:44.540Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:31:44.540Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:31:44.540Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (37058.275 ms) ====== [2025-11-29T13:31:44.540Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-29T13:31:45.218Z] GC before operation: completed in 267.418 ms, heap usage 201.424 MB -> 97.194 MB. [2025-11-29T13:31:49.294Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:31:53.380Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:31:56.659Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:32:00.723Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:32:02.993Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:32:05.230Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:32:07.650Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:32:09.692Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:32:10.423Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:32:10.424Z] The best model improves the baseline by 14.34%. [2025-11-29T13:32:10.424Z] Top recommended movies for user id 72: [2025-11-29T13:32:10.424Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:32:10.424Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:32:10.424Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:32:10.424Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:32:10.424Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:32:10.424Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25553.326 ms) ====== [2025-11-29T13:32:10.424Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-29T13:32:11.146Z] GC before operation: completed in 206.348 ms, heap usage 187.143 MB -> 87.586 MB. [2025-11-29T13:32:14.284Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:32:18.372Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:32:22.486Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:32:26.707Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:32:29.055Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:32:31.184Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:32:33.554Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:32:36.751Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:32:36.751Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:32:36.751Z] The best model improves the baseline by 14.34%. [2025-11-29T13:32:36.751Z] Top recommended movies for user id 72: [2025-11-29T13:32:36.751Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:32:36.751Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:32:36.751Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:32:36.751Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:32:36.751Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:32:36.751Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (26121.664 ms) ====== [2025-11-29T13:32:36.751Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-29T13:32:37.498Z] GC before operation: completed in 299.530 ms, heap usage 219.104 MB -> 88.315 MB. [2025-11-29T13:32:40.590Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:32:44.695Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:32:48.830Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:32:51.941Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:32:53.411Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:32:55.639Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:32:58.640Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:33:00.104Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:33:00.837Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:33:00.837Z] The best model improves the baseline by 14.34%. [2025-11-29T13:33:00.837Z] Top recommended movies for user id 72: [2025-11-29T13:33:00.837Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:33:00.837Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:33:00.837Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:33:00.837Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:33:00.837Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:33:00.837Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23698.578 ms) ====== [2025-11-29T13:33:00.837Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-29T13:33:01.510Z] GC before operation: completed in 335.759 ms, heap usage 215.601 MB -> 88.509 MB. [2025-11-29T13:33:05.741Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:33:08.852Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:33:14.084Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:33:17.264Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:33:19.458Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:33:21.771Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:33:23.231Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:33:25.609Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:33:25.609Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:33:25.609Z] The best model improves the baseline by 14.34%. [2025-11-29T13:33:26.287Z] Top recommended movies for user id 72: [2025-11-29T13:33:26.287Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:33:26.287Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:33:26.287Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:33:26.287Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:33:26.287Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:33:26.287Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24849.410 ms) ====== [2025-11-29T13:33:26.287Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-29T13:33:26.287Z] GC before operation: completed in 306.416 ms, heap usage 197.528 MB -> 88.417 MB. [2025-11-29T13:33:30.352Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:33:33.456Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:33:37.534Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:33:40.768Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:33:42.966Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:33:44.847Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:33:47.040Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:33:48.501Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:33:49.183Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:33:49.183Z] The best model improves the baseline by 14.34%. [2025-11-29T13:33:49.183Z] Top recommended movies for user id 72: [2025-11-29T13:33:49.183Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:33:49.183Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:33:49.183Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:33:49.183Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:33:49.183Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:33:49.183Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (22962.348 ms) ====== [2025-11-29T13:33:49.183Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-29T13:33:49.881Z] GC before operation: completed in 268.286 ms, heap usage 142.447 MB -> 91.901 MB. [2025-11-29T13:33:53.097Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:33:56.197Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:34:00.296Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:34:03.378Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:34:06.512Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:34:07.839Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:34:10.984Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:34:13.386Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:34:13.386Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:34:14.099Z] The best model improves the baseline by 14.34%. [2025-11-29T13:34:14.099Z] Top recommended movies for user id 72: [2025-11-29T13:34:14.099Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:34:14.099Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:34:14.099Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:34:14.099Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:34:14.099Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:34:14.099Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (24380.395 ms) ====== [2025-11-29T13:34:14.099Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-29T13:34:14.099Z] GC before operation: completed in 265.735 ms, heap usage 233.242 MB -> 88.929 MB. [2025-11-29T13:34:18.162Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:34:22.224Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:34:26.271Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:34:29.971Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:34:32.194Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:34:35.483Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:34:38.610Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:34:40.883Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:34:40.883Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:34:40.883Z] The best model improves the baseline by 14.34%. [2025-11-29T13:34:41.558Z] Top recommended movies for user id 72: [2025-11-29T13:34:41.558Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:34:41.558Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:34:41.558Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:34:41.558Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:34:41.558Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:34:41.558Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (27088.084 ms) ====== [2025-11-29T13:34:41.558Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-29T13:34:41.558Z] GC before operation: completed in 242.220 ms, heap usage 448.124 MB -> 92.707 MB. [2025-11-29T13:34:45.710Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:34:50.930Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:34:54.161Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:34:58.312Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:34:59.784Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:35:02.041Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:35:04.305Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:35:06.626Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:35:07.364Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:35:07.364Z] The best model improves the baseline by 14.34%. [2025-11-29T13:35:08.060Z] Top recommended movies for user id 72: [2025-11-29T13:35:08.060Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:35:08.060Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:35:08.060Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:35:08.060Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:35:08.060Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:35:08.060Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (26123.003 ms) ====== [2025-11-29T13:35:08.060Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-29T13:35:08.060Z] GC before operation: completed in 232.924 ms, heap usage 328.673 MB -> 89.103 MB. [2025-11-29T13:35:12.145Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:35:20.359Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:35:20.359Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:35:22.596Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:35:25.651Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:35:27.990Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:35:30.329Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:35:33.543Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:35:34.237Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:35:34.237Z] The best model improves the baseline by 14.34%. [2025-11-29T13:35:34.237Z] Top recommended movies for user id 72: [2025-11-29T13:35:34.237Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:35:34.237Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:35:34.237Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:35:34.237Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:35:34.237Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:35:34.237Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26152.711 ms) ====== [2025-11-29T13:35:34.237Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-29T13:35:34.237Z] GC before operation: completed in 178.236 ms, heap usage 190.819 MB -> 89.035 MB. [2025-11-29T13:35:37.394Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:35:41.561Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:35:44.643Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:35:49.761Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:35:51.134Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:35:53.371Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:35:55.586Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:35:57.770Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:35:57.770Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:35:57.770Z] The best model improves the baseline by 14.34%. [2025-11-29T13:35:57.770Z] Top recommended movies for user id 72: [2025-11-29T13:35:57.770Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:35:57.770Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:35:57.770Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:35:57.770Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:35:57.770Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:35:57.770Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (23528.511 ms) ====== [2025-11-29T13:35:57.770Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-29T13:35:57.770Z] GC before operation: completed in 208.943 ms, heap usage 300.514 MB -> 89.008 MB. [2025-11-29T13:36:01.801Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:36:04.941Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:36:08.598Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:36:11.700Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:36:13.854Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:36:15.981Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:36:18.095Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:36:19.552Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:36:20.289Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:36:20.289Z] The best model improves the baseline by 14.34%. [2025-11-29T13:36:20.289Z] Top recommended movies for user id 72: [2025-11-29T13:36:20.289Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:36:20.289Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:36:20.289Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:36:20.289Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:36:20.289Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:36:20.289Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22414.654 ms) ====== [2025-11-29T13:36:20.289Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-29T13:36:21.170Z] GC before operation: completed in 221.381 ms, heap usage 202.195 MB -> 88.985 MB. [2025-11-29T13:36:24.252Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:36:27.349Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:36:31.460Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:36:34.713Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:36:36.140Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:36:37.529Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:36:39.862Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:36:43.022Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:36:43.022Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:36:43.022Z] The best model improves the baseline by 14.34%. [2025-11-29T13:36:43.022Z] Top recommended movies for user id 72: [2025-11-29T13:36:43.022Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:36:43.022Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:36:43.022Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:36:43.022Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:36:43.022Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:36:43.022Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22385.109 ms) ====== [2025-11-29T13:36:43.022Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-29T13:36:43.022Z] GC before operation: completed in 309.417 ms, heap usage 197.805 MB -> 89.112 MB. [2025-11-29T13:36:47.094Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:36:50.352Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:36:53.471Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:36:56.988Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:36:59.236Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:37:01.526Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:37:04.621Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:37:07.004Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:37:07.004Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:37:07.004Z] The best model improves the baseline by 14.34%. [2025-11-29T13:37:07.004Z] Top recommended movies for user id 72: [2025-11-29T13:37:07.005Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:37:07.005Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:37:07.005Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:37:07.005Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:37:07.005Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:37:07.005Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (24002.286 ms) ====== [2025-11-29T13:37:07.005Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-29T13:37:07.696Z] GC before operation: completed in 204.964 ms, heap usage 196.998 MB -> 88.958 MB. [2025-11-29T13:37:11.833Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:37:15.084Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:37:19.081Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:37:22.214Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:37:24.460Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:37:26.695Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:37:28.975Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:37:31.190Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:37:31.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:37:31.940Z] The best model improves the baseline by 14.34%. [2025-11-29T13:37:31.940Z] Top recommended movies for user id 72: [2025-11-29T13:37:31.940Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:37:31.940Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:37:31.940Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:37:31.940Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:37:31.940Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:37:31.940Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (24427.556 ms) ====== [2025-11-29T13:37:31.940Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-29T13:37:31.940Z] GC before operation: completed in 204.409 ms, heap usage 169.244 MB -> 89.218 MB. [2025-11-29T13:37:36.154Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:37:40.265Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:37:43.751Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:37:46.867Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:37:49.099Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:37:51.385Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:37:53.696Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:37:56.061Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:37:56.890Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:37:56.890Z] The best model improves the baseline by 14.34%. [2025-11-29T13:37:56.890Z] Top recommended movies for user id 72: [2025-11-29T13:37:56.890Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:37:56.890Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:37:56.890Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:37:56.890Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:37:56.890Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:37:56.890Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (24687.848 ms) ====== [2025-11-29T13:37:56.890Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-29T13:37:56.890Z] GC before operation: completed in 170.043 ms, heap usage 221.772 MB -> 89.143 MB. [2025-11-29T13:38:01.006Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:38:04.139Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:38:07.301Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:38:11.529Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:38:13.920Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:38:16.182Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:38:19.370Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:38:21.680Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:38:21.680Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:38:21.680Z] The best model improves the baseline by 14.34%. [2025-11-29T13:38:22.384Z] Top recommended movies for user id 72: [2025-11-29T13:38:22.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:38:22.384Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:38:22.384Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:38:22.384Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:38:22.384Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:38:22.384Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (25009.019 ms) ====== [2025-11-29T13:38:22.384Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-29T13:38:22.384Z] GC before operation: completed in 252.223 ms, heap usage 250.372 MB -> 89.298 MB. [2025-11-29T13:38:26.428Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:38:30.888Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:38:35.162Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:38:38.274Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:38:40.541Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:38:43.683Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:38:45.917Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:38:48.201Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:38:48.202Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:38:48.202Z] The best model improves the baseline by 14.34%. [2025-11-29T13:38:48.947Z] Top recommended movies for user id 72: [2025-11-29T13:38:48.947Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:38:48.947Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:38:48.947Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:38:48.947Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:38:48.947Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:38:48.947Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26408.237 ms) ====== [2025-11-29T13:38:48.947Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-29T13:38:48.947Z] GC before operation: completed in 213.950 ms, heap usage 303.404 MB -> 89.255 MB. [2025-11-29T13:38:52.076Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:38:56.192Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:39:00.411Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:39:03.540Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:39:05.718Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:39:07.950Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:39:10.224Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:39:12.455Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:39:12.455Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:39:12.455Z] The best model improves the baseline by 14.34%. [2025-11-29T13:39:12.455Z] Top recommended movies for user id 72: [2025-11-29T13:39:12.455Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:39:12.455Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:39:12.455Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:39:12.455Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:39:12.455Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:39:12.455Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (23786.749 ms) ====== [2025-11-29T13:39:12.455Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-29T13:39:13.141Z] GC before operation: completed in 205.580 ms, heap usage 350.900 MB -> 89.386 MB. [2025-11-29T13:39:16.675Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:39:19.865Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:39:24.147Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:39:27.318Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:39:28.777Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:39:31.060Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:39:33.745Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:39:35.184Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:39:35.184Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:39:35.184Z] The best model improves the baseline by 14.34%. [2025-11-29T13:39:35.184Z] Top recommended movies for user id 72: [2025-11-29T13:39:35.184Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:39:35.184Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:39:35.184Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:39:35.184Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:39:35.184Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:39:35.184Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (22469.446 ms) ====== [2025-11-29T13:39:35.880Z] ----------------------------------- [2025-11-29T13:39:35.880Z] renaissance-movie-lens_0_PASSED [2025-11-29T13:39:35.880Z] ----------------------------------- [2025-11-29T13:39:35.880Z] [2025-11-29T13:39:35.880Z] TEST TEARDOWN: [2025-11-29T13:39:35.880Z] Nothing to be done for teardown. [2025-11-29T13:39:35.880Z] renaissance-movie-lens_0 Finish Time: Sat Nov 29 08:39:35 2025 Epoch Time (ms): 1764423575602