renaissance-movie-lens_0
[2025-12-27T14:35:43.644Z] Running test renaissance-movie-lens_0 ...
[2025-12-27T14:35:43.644Z] ===============================================
[2025-12-27T14:35:43.644Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 14:35:41 2025 Epoch Time (ms): 1766846141373
[2025-12-27T14:35:43.644Z] variation: NoOptions
[2025-12-27T14:35:43.644Z] JVM_OPTIONS:
[2025-12-27T14:35:43.644Z] { \
[2025-12-27T14:35:43.644Z] echo ""; echo "TEST SETUP:"; \
[2025-12-27T14:35:43.644Z] echo "Nothing to be done for setup."; \
[2025-12-27T14:35:43.644Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668445173805/renaissance-movie-lens_0"; \
[2025-12-27T14:35:43.644Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668445173805/renaissance-movie-lens_0"; \
[2025-12-27T14:35:43.644Z] echo ""; echo "TESTING:"; \
[2025-12-27T14:35:43.644Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/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_riscv64_linux_testList_2/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668445173805/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-27T14:35:43.644Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668445173805/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-27T14:35:43.644Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-27T14:35:43.644Z] echo "Nothing to be done for teardown."; \
[2025-12-27T14:35:43.644Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668445173805/TestTargetResult";
[2025-12-27T14:35:43.644Z]
[2025-12-27T14:35:43.644Z] TEST SETUP:
[2025-12-27T14:35:43.644Z] Nothing to be done for setup.
[2025-12-27T14:35:43.644Z]
[2025-12-27T14:35:43.644Z] TESTING:
[2025-12-27T14:35:43.967Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-27T14:35:43.967Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/output_17668445173805/renaissance-movie-lens_0/launcher-143542-15645226298943108539/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-27T14:35:43.967Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-27T14:35:43.967Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-27T14:36:06.923Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-27T14:36:40.161Z] 14:36:35.887 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-27T14:36:46.015Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-27T14:36:48.240Z] Training: 60056, validation: 20285, test: 19854
[2025-12-27T14:36:48.241Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-27T14:36:48.563Z] GC before operation: completed in 612.413 ms, heap usage 267.382 MB -> 75.820 MB.
[2025-12-27T14:37:16.243Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:37:29.691Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:37:42.826Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:37:55.880Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:38:01.769Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:38:09.033Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:38:16.246Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:38:22.106Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:38:23.234Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T14:38:23.234Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:38:24.370Z] Top recommended movies for user id 72:
[2025-12-27T14:38:24.370Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:38:24.370Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:38:24.370Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:38:24.370Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:38:24.370Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:38:24.370Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (95914.945 ms) ======
[2025-12-27T14:38:24.370Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-27T14:38:25.078Z] GC before operation: completed in 850.733 ms, heap usage 133.152 MB -> 86.312 MB.
[2025-12-27T14:38:38.124Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:38:46.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:38:57.735Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:39:08.525Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:39:13.228Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:39:19.075Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:39:26.292Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:39:33.523Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:39:33.523Z] 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.
[2025-12-27T14:39:33.523Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:39:34.218Z] Top recommended movies for user id 72:
[2025-12-27T14:39:34.218Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:39:34.218Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:39:34.218Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:39:34.218Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:39:34.218Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:39:34.218Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (69040.966 ms) ======
[2025-12-27T14:39:34.218Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-27T14:39:35.379Z] GC before operation: completed in 907.232 ms, heap usage 395.766 MB -> 88.752 MB.
[2025-12-27T14:39:46.144Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:39:56.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:40:06.122Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:40:14.953Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:40:20.810Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:40:25.521Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:40:31.396Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:40:37.266Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:40:37.963Z] 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.
[2025-12-27T14:40:37.963Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:40:38.669Z] Top recommended movies for user id 72:
[2025-12-27T14:40:38.669Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:40:38.669Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:40:38.669Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:40:38.669Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:40:38.669Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:40:38.669Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63525.655 ms) ======
[2025-12-27T14:40:38.669Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-27T14:40:39.827Z] GC before operation: completed in 891.410 ms, heap usage 146.090 MB -> 89.023 MB.
[2025-12-27T14:40:50.594Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:40:57.818Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:41:05.092Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:41:13.934Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:41:18.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:41:24.512Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:41:29.227Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:41:32.974Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:41:34.617Z] 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.
[2025-12-27T14:41:34.617Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:41:34.940Z] Top recommended movies for user id 72:
[2025-12-27T14:41:34.940Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:41:34.940Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:41:34.940Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:41:34.940Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:41:34.940Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:41:34.940Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (55440.858 ms) ======
[2025-12-27T14:41:34.940Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-27T14:41:36.105Z] GC before operation: completed in 960.875 ms, heap usage 506.750 MB -> 89.936 MB.
[2025-12-27T14:41:44.952Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:41:53.790Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:42:02.657Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:42:11.497Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:42:16.487Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:42:21.216Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:42:25.951Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:42:31.813Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:42:32.941Z] 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.
[2025-12-27T14:42:32.941Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:42:33.638Z] Top recommended movies for user id 72:
[2025-12-27T14:42:33.639Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:42:33.639Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:42:33.639Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:42:33.639Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:42:33.639Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:42:33.639Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (57639.821 ms) ======
[2025-12-27T14:42:33.639Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-27T14:42:34.775Z] GC before operation: completed in 919.591 ms, heap usage 100.017 MB -> 89.450 MB.
[2025-12-27T14:42:43.611Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:42:52.447Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:43:01.283Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:43:10.112Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:43:14.819Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:43:19.523Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:43:25.391Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:43:30.101Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:43:30.796Z] 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.
[2025-12-27T14:43:30.796Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:43:31.497Z] Top recommended movies for user id 72:
[2025-12-27T14:43:31.497Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:43:31.497Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:43:31.497Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:43:31.497Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:43:31.497Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:43:31.497Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57015.554 ms) ======
[2025-12-27T14:43:31.497Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-27T14:43:32.667Z] GC before operation: completed in 903.052 ms, heap usage 133.712 MB -> 89.707 MB.
[2025-12-27T14:43:41.483Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:43:50.332Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:43:57.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:44:06.416Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:44:11.118Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:44:15.834Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:44:20.956Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:44:25.654Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:44:25.978Z] 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.
[2025-12-27T14:44:25.978Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:44:27.120Z] Top recommended movies for user id 72:
[2025-12-27T14:44:27.120Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:44:27.120Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:44:27.120Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:44:27.120Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:44:27.120Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:44:27.120Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (54375.722 ms) ======
[2025-12-27T14:44:27.120Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-27T14:44:27.842Z] GC before operation: completed in 941.760 ms, heap usage 128.316 MB -> 89.694 MB.
[2025-12-27T14:44:36.853Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:44:44.079Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:44:52.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:45:00.158Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:45:04.858Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:45:09.607Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:45:15.455Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:45:20.160Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:45:20.860Z] 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.
[2025-12-27T14:45:20.860Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:45:21.565Z] Top recommended movies for user id 72:
[2025-12-27T14:45:21.565Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:45:21.565Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:45:21.565Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:45:21.565Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:45:21.565Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:45:21.565Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (53706.399 ms) ======
[2025-12-27T14:45:21.565Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-27T14:45:22.288Z] GC before operation: completed in 902.547 ms, heap usage 387.840 MB -> 90.250 MB.
[2025-12-27T14:45:31.245Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:45:40.070Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:45:47.291Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:45:56.113Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:46:00.874Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:46:05.699Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:46:11.541Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:46:16.262Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:46:17.393Z] 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.
[2025-12-27T14:46:17.393Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:46:18.098Z] Top recommended movies for user id 72:
[2025-12-27T14:46:18.098Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:46:18.098Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:46:18.098Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:46:18.098Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:46:18.098Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:46:18.098Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55566.435 ms) ======
[2025-12-27T14:46:18.098Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-27T14:46:18.828Z] GC before operation: completed in 936.822 ms, heap usage 499.737 MB -> 90.295 MB.
[2025-12-27T14:46:27.665Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:46:36.489Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:46:45.369Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:46:52.643Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:46:58.539Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:47:03.284Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:47:09.127Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:47:13.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:47:14.542Z] 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.
[2025-12-27T14:47:14.542Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:47:15.253Z] Top recommended movies for user id 72:
[2025-12-27T14:47:15.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:47:15.253Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:47:15.253Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:47:15.253Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:47:15.253Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:47:15.253Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (56199.666 ms) ======
[2025-12-27T14:47:15.253Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-27T14:47:15.960Z] GC before operation: completed in 940.204 ms, heap usage 122.354 MB -> 89.878 MB.
[2025-12-27T14:47:24.830Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:47:33.775Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:47:41.033Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:47:49.857Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:47:53.612Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:47:59.472Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:48:05.385Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:48:10.089Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:48:10.417Z] 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.
[2025-12-27T14:48:10.417Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:48:11.166Z] Top recommended movies for user id 72:
[2025-12-27T14:48:11.166Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:48:11.166Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:48:11.166Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:48:11.166Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:48:11.166Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:48:11.166Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54986.735 ms) ======
[2025-12-27T14:48:11.166Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-27T14:48:11.888Z] GC before operation: completed in 925.680 ms, heap usage 429.489 MB -> 89.981 MB.
[2025-12-27T14:48:20.866Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:48:28.082Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:48:36.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:48:45.784Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:48:49.518Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:48:54.247Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:49:00.096Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:49:04.801Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:49:05.928Z] 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.
[2025-12-27T14:49:05.928Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:49:06.625Z] Top recommended movies for user id 72:
[2025-12-27T14:49:06.625Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:49:06.625Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:49:06.625Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:49:06.625Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:49:06.625Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:49:06.625Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (54627.067 ms) ======
[2025-12-27T14:49:06.625Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-27T14:49:07.774Z] GC before operation: completed in 952.470 ms, heap usage 253.559 MB -> 90.085 MB.
[2025-12-27T14:49:16.607Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:49:23.816Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:49:31.020Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:49:38.221Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:49:42.921Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:49:47.680Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:49:52.386Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:49:57.088Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:49:57.843Z] 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.
[2025-12-27T14:49:58.168Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:49:58.865Z] Top recommended movies for user id 72:
[2025-12-27T14:49:58.865Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:49:58.865Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:49:58.865Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:49:58.865Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:49:58.865Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:49:58.865Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (51269.174 ms) ======
[2025-12-27T14:49:58.865Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-27T14:50:00.014Z] GC before operation: completed in 935.405 ms, heap usage 170.051 MB -> 90.133 MB.
[2025-12-27T14:50:09.082Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:50:16.293Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:50:25.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:50:32.377Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:50:38.242Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:50:42.958Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:50:48.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:50:53.531Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:50:54.230Z] 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.
[2025-12-27T14:50:54.553Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:50:55.261Z] Top recommended movies for user id 72:
[2025-12-27T14:50:55.261Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:50:55.261Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:50:55.261Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:50:55.261Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:50:55.261Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:50:55.261Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (55318.802 ms) ======
[2025-12-27T14:50:55.261Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-27T14:50:55.976Z] GC before operation: completed in 955.787 ms, heap usage 134.571 MB -> 89.760 MB.
[2025-12-27T14:51:04.811Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:51:13.708Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:51:22.551Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:51:29.772Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:51:34.490Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:51:39.205Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:51:45.051Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:51:49.748Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:51:50.443Z] 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.
[2025-12-27T14:51:50.443Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:51:51.139Z] Top recommended movies for user id 72:
[2025-12-27T14:51:51.139Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:51:51.139Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:51:51.139Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:51:51.139Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:51:51.139Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:51:51.139Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (55038.188 ms) ======
[2025-12-27T14:51:51.139Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-27T14:51:52.398Z] GC before operation: completed in 1022.555 ms, heap usage 582.014 MB -> 93.814 MB.
[2025-12-27T14:52:01.217Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:52:08.433Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:52:15.647Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:52:22.870Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:52:27.588Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:52:31.333Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:52:37.312Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:52:41.072Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:52:42.214Z] 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.
[2025-12-27T14:52:42.214Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:52:42.912Z] Top recommended movies for user id 72:
[2025-12-27T14:52:42.912Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:52:42.912Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:52:42.912Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:52:42.912Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:52:42.912Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:52:42.912Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (50739.270 ms) ======
[2025-12-27T14:52:42.912Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-27T14:52:44.072Z] GC before operation: completed in 1000.439 ms, heap usage 391.276 MB -> 90.174 MB.
[2025-12-27T14:52:52.964Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:53:00.202Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:53:07.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:53:14.646Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:53:18.463Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:53:23.188Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:53:27.901Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:53:32.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:53:32.939Z] 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.
[2025-12-27T14:53:32.939Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:53:33.638Z] Top recommended movies for user id 72:
[2025-12-27T14:53:33.638Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:53:33.638Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:53:33.638Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:53:33.638Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:53:33.638Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:53:33.638Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (49708.942 ms) ======
[2025-12-27T14:53:33.638Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-27T14:53:34.791Z] GC before operation: completed in 979.982 ms, heap usage 554.793 MB -> 93.762 MB.
[2025-12-27T14:53:43.669Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:53:50.917Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:53:58.145Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:54:05.546Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:54:10.265Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:54:14.009Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:54:18.714Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:54:23.430Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:54:24.128Z] 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.
[2025-12-27T14:54:24.128Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:54:24.842Z] Top recommended movies for user id 72:
[2025-12-27T14:54:24.842Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:54:24.842Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:54:24.842Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:54:24.842Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:54:24.842Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:54:24.842Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (50126.314 ms) ======
[2025-12-27T14:54:24.842Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-27T14:54:25.566Z] GC before operation: completed in 987.646 ms, heap usage 835.570 MB -> 94.055 MB.
[2025-12-27T14:54:34.426Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:54:41.748Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:54:48.954Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:54:56.156Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:54:59.892Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:55:04.638Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:55:09.353Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:55:14.058Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:55:15.188Z] 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.
[2025-12-27T14:55:15.188Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:55:15.904Z] Top recommended movies for user id 72:
[2025-12-27T14:55:15.904Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:55:15.904Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:55:15.904Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:55:15.904Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:55:15.904Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:55:15.904Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (50105.089 ms) ======
[2025-12-27T14:55:15.904Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-27T14:55:16.623Z] GC before operation: completed in 937.145 ms, heap usage 380.766 MB -> 90.404 MB.
[2025-12-27T14:55:25.651Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:55:32.876Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:55:41.742Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:55:48.974Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:55:53.675Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:55:58.382Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:56:03.088Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:56:07.942Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:56:09.076Z] 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.
[2025-12-27T14:56:09.076Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:56:09.779Z] Top recommended movies for user id 72:
[2025-12-27T14:56:09.779Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:56:09.779Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:56:09.779Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:56:09.779Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:56:09.779Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:56:09.779Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53060.389 ms) ======
[2025-12-27T14:56:13.523Z] -----------------------------------
[2025-12-27T14:56:13.523Z] renaissance-movie-lens_0_PASSED
[2025-12-27T14:56:13.523Z] -----------------------------------
[2025-12-27T14:56:13.523Z]
[2025-12-27T14:56:13.523Z] TEST TEARDOWN:
[2025-12-27T14:56:13.523Z] Nothing to be done for teardown.
[2025-12-27T14:56:13.523Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 14:56:12 2025 Epoch Time (ms): 1766847372906