renaissance-movie-lens_0
[2025-11-12T23:47:21.269Z] Running test renaissance-movie-lens_0 ...
[2025-11-12T23:47:21.269Z] ===============================================
[2025-11-12T23:47:21.269Z] renaissance-movie-lens_0 Start Time: Wed Nov 12 23:47:21 2025 Epoch Time (ms): 1762991241039
[2025-11-12T23:47:21.269Z] variation: NoOptions
[2025-11-12T23:47:21.269Z] JVM_OPTIONS:
[2025-11-12T23:47:21.269Z] { \
[2025-11-12T23:47:21.269Z] echo ""; echo "TEST SETUP:"; \
[2025-11-12T23:47:21.269Z] echo "Nothing to be done for setup."; \
[2025-11-12T23:47:21.269Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17629898258623/renaissance-movie-lens_0"; \
[2025-11-12T23:47:21.269Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17629898258623/renaissance-movie-lens_0"; \
[2025-11-12T23:47:21.269Z] echo ""; echo "TESTING:"; \
[2025-11-12T23:47:21.269Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17629898258623/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-12T23:47:21.269Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17629898258623/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-12T23:47:21.269Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-12T23:47:21.269Z] echo "Nothing to be done for teardown."; \
[2025-11-12T23:47:21.269Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17629898258623/TestTargetResult";
[2025-11-12T23:47:21.269Z]
[2025-11-12T23:47:21.269Z] TEST SETUP:
[2025-11-12T23:47:21.269Z] Nothing to be done for setup.
[2025-11-12T23:47:21.269Z]
[2025-11-12T23:47:21.269Z] TESTING:
[2025-11-12T23:47:26.358Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-12T23:47:33.111Z] 23:47:32.899 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-12T23:47:35.087Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-12T23:47:36.055Z] Training: 60056, validation: 20285, test: 19854
[2025-11-12T23:47:36.055Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-12T23:47:36.055Z] GC before operation: completed in 131.721 ms, heap usage 139.018 MB -> 75.797 MB.
[2025-11-12T23:47:41.501Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:47:44.553Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:47:47.683Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:47:50.728Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:47:52.712Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:47:53.675Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:47:55.659Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:47:57.633Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:47:57.633Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:47:57.633Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:47:58.595Z] Top recommended movies for user id 72:
[2025-11-12T23:47:58.595Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:47:58.595Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:47:58.595Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:47:58.595Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:47:58.595Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:47:58.595Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22071.116 ms) ======
[2025-11-12T23:47:58.595Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-12T23:47:58.595Z] GC before operation: completed in 174.866 ms, heap usage 343.505 MB -> 89.733 MB.
[2025-11-12T23:48:01.645Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:48:03.618Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:48:05.763Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:48:08.811Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:48:09.772Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:48:11.750Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:48:13.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:48:14.685Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:48:14.685Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:48:14.685Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:48:15.649Z] Top recommended movies for user id 72:
[2025-11-12T23:48:15.649Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:48:15.649Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:48:15.649Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:48:15.649Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:48:15.649Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:48:15.649Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16877.233 ms) ======
[2025-11-12T23:48:15.649Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-12T23:48:15.649Z] GC before operation: completed in 141.343 ms, heap usage 497.851 MB -> 90.282 MB.
[2025-11-12T23:48:18.334Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:48:20.307Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:48:23.353Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:48:25.328Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:48:26.400Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:48:28.371Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:48:30.345Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:48:31.307Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:48:31.307Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:48:31.307Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:48:32.267Z] Top recommended movies for user id 72:
[2025-11-12T23:48:32.267Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:48:32.267Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:48:32.267Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:48:32.267Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:48:32.267Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:48:32.267Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16551.271 ms) ======
[2025-11-12T23:48:32.267Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-12T23:48:32.267Z] GC before operation: completed in 134.672 ms, heap usage 202.178 MB -> 89.203 MB.
[2025-11-12T23:48:34.239Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:48:36.222Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:48:39.294Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:48:41.268Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:48:43.249Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:48:44.213Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:48:46.285Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:48:47.428Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:48:48.398Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:48:48.398Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:48:48.398Z] Top recommended movies for user id 72:
[2025-11-12T23:48:48.398Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:48:48.398Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:48:48.398Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:48:48.398Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:48:48.398Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:48:48.398Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16078.842 ms) ======
[2025-11-12T23:48:48.398Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-12T23:48:48.398Z] GC before operation: completed in 134.602 ms, heap usage 289.568 MB -> 89.692 MB.
[2025-11-12T23:48:50.371Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:48:53.444Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:48:55.415Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:48:58.464Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:49:00.450Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:49:01.413Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:49:03.444Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:49:04.419Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:49:05.382Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:49:05.382Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:49:05.382Z] Top recommended movies for user id 72:
[2025-11-12T23:49:05.382Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:49:05.382Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:49:05.382Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:49:05.382Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:49:05.382Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:49:05.382Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16921.244 ms) ======
[2025-11-12T23:49:05.382Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-12T23:49:05.382Z] GC before operation: completed in 150.125 ms, heap usage 394.793 MB -> 89.747 MB.
[2025-11-12T23:49:07.364Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:49:10.431Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:49:13.052Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:49:15.028Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:49:15.989Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:49:17.965Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:49:18.930Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:49:20.903Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:49:20.903Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:49:20.903Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:49:20.903Z] Top recommended movies for user id 72:
[2025-11-12T23:49:20.903Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:49:20.903Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:49:20.903Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:49:20.903Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:49:20.903Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:49:20.903Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15540.953 ms) ======
[2025-11-12T23:49:20.903Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-12T23:49:20.903Z] GC before operation: completed in 190.931 ms, heap usage 487.688 MB -> 90.260 MB.
[2025-11-12T23:49:23.961Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:49:25.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:49:27.907Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:49:29.878Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:49:30.839Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:49:32.813Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:49:33.775Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:49:34.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:49:35.701Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:49:35.702Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:49:35.702Z] Top recommended movies for user id 72:
[2025-11-12T23:49:35.702Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:49:35.702Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:49:35.702Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:49:35.702Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:49:35.702Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:49:35.702Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14414.226 ms) ======
[2025-11-12T23:49:35.702Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-12T23:49:35.702Z] GC before operation: completed in 165.207 ms, heap usage 238.052 MB -> 89.853 MB.
[2025-11-12T23:49:37.682Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:49:39.660Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:49:42.715Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:49:44.690Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:49:45.807Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:49:46.768Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:49:48.744Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:49:49.705Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:49:49.705Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:49:49.705Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:49:50.669Z] Top recommended movies for user id 72:
[2025-11-12T23:49:50.670Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:49:50.670Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:49:50.670Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:49:50.670Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:49:50.670Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:49:50.670Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14644.715 ms) ======
[2025-11-12T23:49:50.670Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-12T23:49:50.670Z] GC before operation: completed in 124.849 ms, heap usage 237.147 MB -> 90.101 MB.
[2025-11-12T23:49:52.644Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:49:54.624Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:49:57.685Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:49:59.663Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:50:00.625Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:50:02.634Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:50:03.599Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:50:06.463Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:50:06.463Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:50:06.463Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:50:06.463Z] Top recommended movies for user id 72:
[2025-11-12T23:50:06.463Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:50:06.463Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:50:06.463Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:50:06.463Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:50:06.463Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:50:06.463Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15474.164 ms) ======
[2025-11-12T23:50:06.463Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-12T23:50:06.463Z] GC before operation: completed in 145.477 ms, heap usage 291.790 MB -> 90.151 MB.
[2025-11-12T23:50:08.439Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:50:10.413Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:50:13.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:50:15.434Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:50:16.395Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:50:18.380Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:50:19.359Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:50:21.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:50:21.331Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:50:21.331Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:50:21.331Z] Top recommended movies for user id 72:
[2025-11-12T23:50:21.331Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:50:21.331Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:50:21.331Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:50:21.331Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:50:21.331Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:50:21.331Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15524.065 ms) ======
[2025-11-12T23:50:21.331Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-12T23:50:21.331Z] GC before operation: completed in 141.634 ms, heap usage 360.230 MB -> 90.414 MB.
[2025-11-12T23:50:24.377Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:50:26.351Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:50:28.326Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:50:30.298Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:50:31.260Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:50:32.221Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:50:34.191Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:50:35.156Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:50:35.156Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:50:35.156Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:50:35.156Z] Top recommended movies for user id 72:
[2025-11-12T23:50:35.157Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:50:35.157Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:50:35.157Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:50:35.157Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:50:35.157Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:50:35.157Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13641.524 ms) ======
[2025-11-12T23:50:35.157Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-12T23:50:35.157Z] GC before operation: completed in 154.070 ms, heap usage 260.057 MB -> 89.961 MB.
[2025-11-12T23:50:38.203Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:50:40.178Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:50:42.162Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:50:44.149Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:50:45.258Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:50:46.222Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:50:47.182Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:50:49.165Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:50:49.165Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:50:49.165Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:50:49.165Z] Top recommended movies for user id 72:
[2025-11-12T23:50:49.165Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:50:49.165Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:50:49.165Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:50:49.165Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:50:49.165Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:50:49.165Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13773.438 ms) ======
[2025-11-12T23:50:49.165Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-12T23:50:49.165Z] GC before operation: completed in 123.178 ms, heap usage 237.521 MB -> 90.079 MB.
[2025-11-12T23:50:51.141Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:50:54.188Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:50:56.162Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:50:58.857Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:50:58.857Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:51:00.839Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:51:01.800Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:51:03.782Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:51:03.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:51:03.782Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:51:03.782Z] Top recommended movies for user id 72:
[2025-11-12T23:51:03.782Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:51:03.782Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:51:03.782Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:51:03.782Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:51:03.782Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:51:03.782Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14673.100 ms) ======
[2025-11-12T23:51:03.782Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-12T23:51:03.782Z] GC before operation: completed in 123.376 ms, heap usage 202.708 MB -> 90.162 MB.
[2025-11-12T23:51:06.830Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:51:08.806Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:51:10.781Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:51:12.755Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:51:13.717Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:51:15.695Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:51:16.657Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:51:17.620Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:51:18.583Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:51:18.583Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:51:18.583Z] Top recommended movies for user id 72:
[2025-11-12T23:51:18.583Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:51:18.583Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:51:18.583Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:51:18.583Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:51:18.583Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:51:18.583Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14315.685 ms) ======
[2025-11-12T23:51:18.583Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-12T23:51:18.583Z] GC before operation: completed in 125.349 ms, heap usage 432.568 MB -> 90.326 MB.
[2025-11-12T23:51:20.563Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:51:23.631Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:51:25.609Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:51:27.585Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:51:29.569Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:51:30.531Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:51:31.493Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:51:33.473Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:51:33.473Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:51:33.473Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:51:33.473Z] Top recommended movies for user id 72:
[2025-11-12T23:51:33.473Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:51:33.473Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:51:33.473Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:51:33.473Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:51:33.473Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:51:33.473Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15148.541 ms) ======
[2025-11-12T23:51:33.473Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-12T23:51:34.436Z] GC before operation: completed in 125.611 ms, heap usage 340.451 MB -> 90.401 MB.
[2025-11-12T23:51:36.412Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:51:38.385Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:51:41.433Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:51:43.405Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:51:44.370Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:51:45.453Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:51:47.437Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:51:48.398Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:51:48.398Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:51:48.398Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:51:49.360Z] Top recommended movies for user id 72:
[2025-11-12T23:51:49.360Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:51:49.360Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:51:49.360Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:51:49.360Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:51:49.360Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:51:49.360Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15028.018 ms) ======
[2025-11-12T23:51:49.360Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-12T23:51:49.360Z] GC before operation: completed in 139.240 ms, heap usage 719.702 MB -> 94.046 MB.
[2025-11-12T23:51:51.212Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:51:53.188Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:51:55.165Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:51:57.225Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:51:59.198Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:52:00.158Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:52:01.122Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:52:03.093Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:52:03.093Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:52:03.093Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:52:03.093Z] Top recommended movies for user id 72:
[2025-11-12T23:52:03.093Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:52:03.093Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:52:03.093Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:52:03.093Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:52:03.093Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:52:03.093Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13961.416 ms) ======
[2025-11-12T23:52:03.093Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-12T23:52:03.093Z] GC before operation: completed in 141.902 ms, heap usage 213.913 MB -> 90.231 MB.
[2025-11-12T23:52:05.065Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:52:07.037Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:52:09.014Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:52:12.068Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:52:13.028Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:52:13.988Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:52:15.966Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:52:16.927Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:52:16.927Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:52:16.927Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:52:16.927Z] Top recommended movies for user id 72:
[2025-11-12T23:52:16.927Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:52:16.927Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:52:16.927Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:52:16.927Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:52:16.927Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:52:16.927Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14013.871 ms) ======
[2025-11-12T23:52:16.927Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-12T23:52:16.927Z] GC before operation: completed in 148.603 ms, heap usage 524.439 MB -> 93.659 MB.
[2025-11-12T23:52:19.970Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:52:21.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:52:23.934Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:52:26.039Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:52:27.001Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:52:27.962Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:52:29.934Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:52:30.925Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:52:30.925Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:52:30.925Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:52:30.925Z] Top recommended movies for user id 72:
[2025-11-12T23:52:30.925Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:52:30.925Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:52:30.925Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:52:30.925Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:52:30.925Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:52:30.925Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13945.363 ms) ======
[2025-11-12T23:52:30.925Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-12T23:52:31.887Z] GC before operation: completed in 168.554 ms, heap usage 425.819 MB -> 90.507 MB.
[2025-11-12T23:52:33.861Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-12T23:52:35.835Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-12T23:52:37.809Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-12T23:52:39.781Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-12T23:52:41.761Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-12T23:52:42.726Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-12T23:52:44.702Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-12T23:52:46.491Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-12T23:52:46.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-12T23:52:46.491Z] The best model improves the baseline by 14.52%.
[2025-11-12T23:52:46.491Z] Top recommended movies for user id 72:
[2025-11-12T23:52:46.491Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-12T23:52:46.491Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-12T23:52:46.491Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-12T23:52:46.491Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-12T23:52:46.491Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-12T23:52:46.491Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14571.364 ms) ======
[2025-11-12T23:52:46.491Z] -----------------------------------
[2025-11-12T23:52:46.491Z] renaissance-movie-lens_0_PASSED
[2025-11-12T23:52:46.491Z] -----------------------------------
[2025-11-12T23:52:46.491Z]
[2025-11-12T23:52:46.491Z] TEST TEARDOWN:
[2025-11-12T23:52:46.491Z] Nothing to be done for teardown.
[2025-11-12T23:52:46.491Z] renaissance-movie-lens_0 Finish Time: Wed Nov 12 23:52:45 2025 Epoch Time (ms): 1762991565996