[2025-12-27T14:41:01.908Z] Running test renaissance-movie-lens_0 ... [2025-12-27T14:41:01.908Z] =============================================== [2025-12-27T14:41:01.908Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 14:41:00 2025 Epoch Time (ms): 1766846460989 [2025-12-27T14:41:01.908Z] variation: NoOptions [2025-12-27T14:41:01.908Z] JVM_OPTIONS: [2025-12-27T14:41:01.908Z] { \ [2025-12-27T14:41:01.908Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T14:41:01.908Z] echo "Nothing to be done for setup."; \ [2025-12-27T14:41:01.909Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668443579572/renaissance-movie-lens_0"; \ [2025-12-27T14:41:01.909Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668443579572/renaissance-movie-lens_0"; \ [2025-12-27T14:41:01.909Z] echo ""; echo "TESTING:"; \ [2025-12-27T14:41:01.909Z] "/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_17668443579572/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T14:41:01.909Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668443579572/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T14:41:01.909Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T14:41:01.909Z] echo "Nothing to be done for teardown."; \ [2025-12-27T14:41:01.909Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17668443579572/TestTargetResult"; [2025-12-27T14:41:01.909Z] [2025-12-27T14:41:01.909Z] TEST SETUP: [2025-12-27T14:41:01.909Z] Nothing to be done for setup. [2025-12-27T14:41:01.909Z] [2025-12-27T14:41:01.909Z] TESTING: [2025-12-27T14:41:02.877Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T14:41:02.877Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_linux/aqa-tests/TKG/output_17668443579572/renaissance-movie-lens_0/launcher-144101-10457427532315193886/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T14:41:02.877Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T14:41:02.877Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T14:41:11.146Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-27T14:41:24.852Z] 14:41:23.031 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-27T14:41:26.849Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T14:41:27.822Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T14:41:27.822Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T14:41:28.800Z] GC before operation: completed in 175.637 ms, heap usage 213.991 MB -> 75.925 MB. [2025-12-27T14:41:38.731Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:41:44.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:41:49.690Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:41:54.996Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:41:58.073Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:42:01.149Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:42:03.146Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:42:06.220Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:42:07.194Z] 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. [2025-12-27T14:42:07.194Z] The best model improves the baseline by 14.52%. [2025-12-27T14:42:07.194Z] Top recommended movies for user id 72: [2025-12-27T14:42:07.194Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:42:07.194Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:42:07.194Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:42:07.194Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:42:07.194Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:42:07.194Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (39064.041 ms) ====== [2025-12-27T14:42:07.194Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T14:42:07.194Z] GC before operation: completed in 194.375 ms, heap usage 272.262 MB -> 87.704 MB. [2025-12-27T14:42:12.663Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:42:16.892Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:42:20.756Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:42:24.982Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:42:26.985Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:42:30.058Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:42:33.136Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:42:35.135Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:42:35.135Z] 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. [2025-12-27T14:42:35.135Z] The best model improves the baseline by 14.52%. [2025-12-27T14:42:36.109Z] Top recommended movies for user id 72: [2025-12-27T14:42:36.109Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:42:36.109Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:42:36.109Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:42:36.109Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:42:36.109Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:42:36.109Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (28082.571 ms) ====== [2025-12-27T14:42:36.109Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T14:42:36.109Z] GC before operation: completed in 183.888 ms, heap usage 352.160 MB -> 88.864 MB. [2025-12-27T14:42:40.346Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:42:44.584Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:42:47.660Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:42:51.911Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:42:53.918Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:42:55.910Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:42:58.989Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:43:00.985Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:43:00.985Z] 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. [2025-12-27T14:43:00.985Z] The best model improves the baseline by 14.52%. [2025-12-27T14:43:00.985Z] Top recommended movies for user id 72: [2025-12-27T14:43:00.985Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:43:00.985Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:43:00.985Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:43:00.985Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:43:00.985Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:43:00.985Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (25581.389 ms) ====== [2025-12-27T14:43:00.985Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T14:43:01.958Z] GC before operation: completed in 181.729 ms, heap usage 236.386 MB -> 89.337 MB. [2025-12-27T14:43:06.200Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:43:09.270Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:43:13.495Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:43:16.585Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:43:19.669Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:43:21.662Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:43:24.744Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:43:26.737Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:43:26.737Z] 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. [2025-12-27T14:43:26.737Z] The best model improves the baseline by 14.52%. [2025-12-27T14:43:28.255Z] Top recommended movies for user id 72: [2025-12-27T14:43:28.255Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:43:28.255Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:43:28.255Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:43:28.255Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:43:28.255Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:43:28.255Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (25809.454 ms) ====== [2025-12-27T14:43:28.255Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T14:43:28.255Z] GC before operation: completed in 207.881 ms, heap usage 499.347 MB -> 90.038 MB. [2025-12-27T14:43:31.329Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:43:35.551Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:43:38.622Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:43:41.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:43:43.688Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:43:45.679Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:43:48.753Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:43:50.818Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:43:50.818Z] 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. [2025-12-27T14:43:50.818Z] The best model improves the baseline by 14.52%. [2025-12-27T14:43:50.818Z] Top recommended movies for user id 72: [2025-12-27T14:43:50.818Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:43:50.818Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:43:50.818Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:43:50.818Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:43:50.818Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:43:50.818Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (23571.140 ms) ====== [2025-12-27T14:43:50.818Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T14:43:51.787Z] GC before operation: completed in 227.379 ms, heap usage 161.614 MB -> 89.545 MB. [2025-12-27T14:43:54.863Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:43:59.084Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:44:03.318Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:44:06.392Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:44:08.381Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:44:10.379Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:44:14.017Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:44:14.984Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:44:15.954Z] 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. [2025-12-27T14:44:15.954Z] The best model improves the baseline by 14.52%. [2025-12-27T14:44:15.954Z] Top recommended movies for user id 72: [2025-12-27T14:44:15.954Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:44:15.954Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:44:15.954Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:44:15.954Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:44:15.954Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:44:15.954Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (24637.347 ms) ====== [2025-12-27T14:44:15.954Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T14:44:15.954Z] GC before operation: completed in 175.309 ms, heap usage 260.524 MB -> 90.050 MB. [2025-12-27T14:44:20.181Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:44:23.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:44:27.475Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:44:30.541Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:44:32.533Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:44:34.524Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:44:37.595Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:44:39.590Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:44:39.590Z] 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. [2025-12-27T14:44:39.590Z] The best model improves the baseline by 14.52%. [2025-12-27T14:44:39.590Z] Top recommended movies for user id 72: [2025-12-27T14:44:39.590Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:44:39.590Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:44:39.590Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:44:39.590Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:44:39.590Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:44:39.590Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23762.104 ms) ====== [2025-12-27T14:44:39.590Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T14:44:40.559Z] GC before operation: completed in 192.075 ms, heap usage 224.685 MB -> 89.923 MB. [2025-12-27T14:44:43.630Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:44:47.855Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:44:50.934Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:44:54.041Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:44:57.117Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:44:59.107Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:45:01.110Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:45:03.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:45:03.102Z] 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. [2025-12-27T14:45:03.102Z] The best model improves the baseline by 14.52%. [2025-12-27T14:45:04.075Z] Top recommended movies for user id 72: [2025-12-27T14:45:04.075Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:45:04.075Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:45:04.075Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:45:04.075Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:45:04.075Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:45:04.075Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (23544.862 ms) ====== [2025-12-27T14:45:04.075Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T14:45:04.075Z] GC before operation: completed in 188.750 ms, heap usage 145.652 MB -> 90.084 MB. [2025-12-27T14:45:07.155Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:45:10.781Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:45:15.003Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:45:18.079Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:45:20.072Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:45:22.063Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:45:24.059Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:45:26.048Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:45:27.021Z] 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. [2025-12-27T14:45:27.021Z] The best model improves the baseline by 14.52%. [2025-12-27T14:45:27.021Z] Top recommended movies for user id 72: [2025-12-27T14:45:27.021Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:45:27.021Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:45:27.021Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:45:27.021Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:45:27.021Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:45:27.021Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (23292.601 ms) ====== [2025-12-27T14:45:27.021Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T14:45:27.021Z] GC before operation: completed in 177.908 ms, heap usage 261.351 MB -> 89.945 MB. [2025-12-27T14:45:31.255Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:45:34.937Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:45:38.030Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:45:41.100Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:45:44.171Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:45:46.159Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:45:48.148Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:45:50.141Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:45:50.141Z] 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. [2025-12-27T14:45:50.141Z] The best model improves the baseline by 14.52%. [2025-12-27T14:45:51.110Z] Top recommended movies for user id 72: [2025-12-27T14:45:51.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:45:51.110Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:45:51.110Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:45:51.110Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:45:51.110Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:45:51.110Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (23355.378 ms) ====== [2025-12-27T14:45:51.110Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T14:45:51.110Z] GC before operation: completed in 179.176 ms, heap usage 433.069 MB -> 90.399 MB. [2025-12-27T14:45:55.338Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:45:58.407Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:46:02.840Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:46:05.004Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:46:06.995Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:46:08.986Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:46:12.058Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:46:14.049Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:46:14.049Z] 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. [2025-12-27T14:46:14.049Z] The best model improves the baseline by 14.52%. [2025-12-27T14:46:14.049Z] Top recommended movies for user id 72: [2025-12-27T14:46:14.049Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:46:14.049Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:46:14.049Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:46:14.049Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:46:14.049Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:46:14.049Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (23558.419 ms) ====== [2025-12-27T14:46:14.049Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T14:46:15.022Z] GC before operation: completed in 182.307 ms, heap usage 290.292 MB -> 89.995 MB. [2025-12-27T14:46:18.102Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:46:22.345Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:46:25.419Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:46:28.491Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:46:30.481Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:46:32.505Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:46:34.499Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:46:36.495Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:46:37.468Z] 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. [2025-12-27T14:46:37.468Z] The best model improves the baseline by 14.52%. [2025-12-27T14:46:37.468Z] Top recommended movies for user id 72: [2025-12-27T14:46:37.468Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:46:37.468Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:46:37.468Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:46:37.468Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:46:37.468Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:46:37.468Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22927.924 ms) ====== [2025-12-27T14:46:37.468Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T14:46:37.468Z] GC before operation: completed in 181.321 ms, heap usage 485.858 MB -> 90.477 MB. [2025-12-27T14:46:41.831Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:46:44.909Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:46:47.981Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:46:52.210Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:46:54.200Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:46:56.186Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:46:59.644Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:47:00.786Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:47:00.786Z] 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. [2025-12-27T14:47:00.786Z] The best model improves the baseline by 14.52%. [2025-12-27T14:47:01.757Z] Top recommended movies for user id 72: [2025-12-27T14:47:01.757Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:47:01.757Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:47:01.757Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:47:01.757Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:47:01.757Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:47:01.757Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (23502.252 ms) ====== [2025-12-27T14:47:01.757Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T14:47:01.757Z] GC before operation: completed in 179.656 ms, heap usage 204.886 MB -> 90.207 MB. [2025-12-27T14:47:04.829Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:47:09.055Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:47:12.128Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:47:15.201Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:47:18.279Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:47:20.274Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:47:22.266Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:47:24.257Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:47:24.257Z] 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. [2025-12-27T14:47:24.257Z] The best model improves the baseline by 14.52%. [2025-12-27T14:47:25.228Z] Top recommended movies for user id 72: [2025-12-27T14:47:25.228Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:47:25.228Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:47:25.228Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:47:25.228Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:47:25.228Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:47:25.228Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (23411.095 ms) ====== [2025-12-27T14:47:25.228Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T14:47:25.228Z] GC before operation: completed in 182.969 ms, heap usage 560.174 MB -> 93.804 MB. [2025-12-27T14:47:28.296Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:47:31.372Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:47:35.591Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:47:37.581Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:47:39.576Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:47:41.574Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:47:43.561Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:47:45.553Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:47:45.553Z] 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. [2025-12-27T14:47:45.553Z] The best model improves the baseline by 14.52%. [2025-12-27T14:47:46.524Z] Top recommended movies for user id 72: [2025-12-27T14:47:46.524Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:47:46.524Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:47:46.524Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:47:46.524Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:47:46.524Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:47:46.524Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (21093.213 ms) ====== [2025-12-27T14:47:46.524Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T14:47:46.524Z] GC before operation: completed in 182.127 ms, heap usage 238.975 MB -> 90.307 MB. [2025-12-27T14:47:49.608Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:47:53.569Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:47:56.654Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:47:59.727Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:48:00.845Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:48:02.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:48:04.838Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:48:06.856Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:48:07.842Z] 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. [2025-12-27T14:48:07.842Z] The best model improves the baseline by 14.52%. [2025-12-27T14:48:07.842Z] Top recommended movies for user id 72: [2025-12-27T14:48:07.842Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:48:07.842Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:48:07.842Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:48:07.842Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:48:07.842Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:48:07.842Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21682.862 ms) ====== [2025-12-27T14:48:07.842Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T14:48:07.842Z] GC before operation: completed in 223.192 ms, heap usage 344.041 MB -> 90.243 MB. [2025-12-27T14:48:12.075Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:48:15.157Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:48:19.411Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:48:22.488Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:48:24.474Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:48:26.471Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:48:28.465Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:48:30.455Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:48:31.429Z] 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. [2025-12-27T14:48:31.429Z] The best model improves the baseline by 14.52%. [2025-12-27T14:48:31.429Z] Top recommended movies for user id 72: [2025-12-27T14:48:31.429Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:48:31.429Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:48:31.429Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:48:31.429Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:48:31.429Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:48:31.429Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (23230.599 ms) ====== [2025-12-27T14:48:31.429Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T14:48:31.429Z] GC before operation: completed in 177.485 ms, heap usage 96.909 MB -> 90.396 MB. [2025-12-27T14:48:35.675Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:48:38.758Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:48:41.833Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:48:44.908Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:48:47.618Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:48:48.586Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:48:50.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:48:52.569Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:48:52.569Z] 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. [2025-12-27T14:48:52.569Z] The best model improves the baseline by 14.52%. [2025-12-27T14:48:52.569Z] Top recommended movies for user id 72: [2025-12-27T14:48:52.569Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:48:52.569Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:48:52.569Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:48:52.569Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:48:52.569Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:48:52.569Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (21217.163 ms) ====== [2025-12-27T14:48:52.569Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T14:48:53.541Z] GC before operation: completed in 187.342 ms, heap usage 883.780 MB -> 94.815 MB. [2025-12-27T14:48:56.609Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:48:59.677Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:49:03.904Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:49:06.971Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:49:08.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:49:10.961Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:49:12.949Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:49:14.944Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:49:14.944Z] 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. [2025-12-27T14:49:15.917Z] The best model improves the baseline by 14.52%. [2025-12-27T14:49:15.917Z] Top recommended movies for user id 72: [2025-12-27T14:49:15.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:49:15.917Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:49:15.917Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:49:15.917Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:49:15.917Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:49:15.917Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22641.518 ms) ====== [2025-12-27T14:49:15.917Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T14:49:15.917Z] GC before operation: completed in 193.894 ms, heap usage 259.946 MB -> 90.334 MB. [2025-12-27T14:49:20.146Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:49:23.220Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:49:26.291Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:49:29.367Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:49:31.355Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:49:33.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:49:35.331Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:49:37.324Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:49:38.841Z] 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. [2025-12-27T14:49:38.841Z] The best model improves the baseline by 14.52%. [2025-12-27T14:49:38.841Z] Top recommended movies for user id 72: [2025-12-27T14:49:38.841Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:49:38.841Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:49:38.841Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:49:38.841Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:49:38.841Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:49:38.841Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (22439.804 ms) ====== [2025-12-27T14:49:39.810Z] ----------------------------------- [2025-12-27T14:49:39.810Z] renaissance-movie-lens_0_PASSED [2025-12-27T14:49:39.810Z] ----------------------------------- [2025-12-27T14:49:39.810Z] [2025-12-27T14:49:39.810Z] TEST TEARDOWN: [2025-12-27T14:49:39.810Z] Nothing to be done for teardown. [2025-12-27T14:49:39.810Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 14:49:39 2025 Epoch Time (ms): 1766846979200