[2025-11-13T08:27:01.083Z] Running test renaissance-movie-lens_0 ... [2025-11-13T08:27:01.083Z] =============================================== [2025-11-13T08:27:01.083Z] renaissance-movie-lens_0 Start Time: Thu Nov 13 08:27:00 2025 Epoch Time (ms): 1763022420400 [2025-11-13T08:27:01.083Z] variation: NoOptions [2025-11-13T08:27:01.083Z] JVM_OPTIONS: [2025-11-13T08:27:01.083Z] { \ [2025-11-13T08:27:01.083Z] echo ""; echo "TEST SETUP:"; \ [2025-11-13T08:27:01.083Z] echo "Nothing to be done for setup."; \ [2025-11-13T08:27:01.083Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630217123315/renaissance-movie-lens_0"; \ [2025-11-13T08:27:01.083Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630217123315/renaissance-movie-lens_0"; \ [2025-11-13T08:27:01.083Z] echo ""; echo "TESTING:"; \ [2025-11-13T08:27:01.083Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/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_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630217123315/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-13T08:27:01.083Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630217123315/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-13T08:27:01.083Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-13T08:27:01.083Z] echo "Nothing to be done for teardown."; \ [2025-11-13T08:27:01.083Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630217123315/TestTargetResult"; [2025-11-13T08:27:01.083Z] [2025-11-13T08:27:01.083Z] TEST SETUP: [2025-11-13T08:27:01.083Z] Nothing to be done for setup. [2025-11-13T08:27:01.083Z] [2025-11-13T08:27:01.083Z] TESTING: [2025-11-13T08:27:05.518Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-13T08:27:12.370Z] 08:27:11.684 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. [2025-11-13T08:27:13.966Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-13T08:27:14.732Z] Training: 60056, validation: 20285, test: 19854 [2025-11-13T08:27:14.732Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-13T08:27:14.732Z] GC before operation: completed in 128.026 ms, heap usage 277.122 MB -> 75.806 MB. [2025-11-13T08:27:21.603Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:27:26.055Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:27:29.462Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:27:32.867Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:27:34.449Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:27:36.031Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:27:37.619Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:27:39.211Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:27:39.977Z] 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. [2025-11-13T08:27:39.977Z] The best model improves the baseline by 14.52%. [2025-11-13T08:27:39.977Z] Top recommended movies for user id 72: [2025-11-13T08:27:39.977Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:27:39.977Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:27:39.977Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:27:39.977Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:27:39.977Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:27:39.977Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25033.187 ms) ====== [2025-11-13T08:27:39.977Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-13T08:27:39.977Z] GC before operation: completed in 140.747 ms, heap usage 185.239 MB -> 96.927 MB. [2025-11-13T08:27:43.388Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:27:45.855Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:27:49.810Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:27:51.403Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:27:52.984Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:27:54.577Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:27:57.071Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:27:58.653Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:27:58.653Z] 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. [2025-11-13T08:27:58.653Z] The best model improves the baseline by 14.52%. [2025-11-13T08:27:58.653Z] Top recommended movies for user id 72: [2025-11-13T08:27:58.653Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:27:58.653Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:27:58.653Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:27:58.653Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:27:58.653Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:27:58.653Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18446.983 ms) ====== [2025-11-13T08:27:58.653Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-13T08:27:58.653Z] GC before operation: completed in 110.739 ms, heap usage 102.647 MB -> 90.913 MB. [2025-11-13T08:28:01.115Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:28:04.514Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:28:06.973Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:28:09.434Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:28:11.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:28:12.612Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:28:14.196Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:28:15.795Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:28:16.564Z] 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. [2025-11-13T08:28:16.564Z] The best model improves the baseline by 14.52%. [2025-11-13T08:28:16.564Z] Top recommended movies for user id 72: [2025-11-13T08:28:16.564Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:28:16.564Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:28:16.564Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:28:16.564Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:28:16.564Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:28:16.564Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17739.310 ms) ====== [2025-11-13T08:28:16.564Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-13T08:28:16.564Z] GC before operation: completed in 114.647 ms, heap usage 160.781 MB -> 89.336 MB. [2025-11-13T08:28:19.019Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:28:21.484Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:28:24.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:28:26.728Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:28:28.326Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:28:30.781Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:28:32.371Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:28:33.953Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:28:33.953Z] 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. [2025-11-13T08:28:33.953Z] The best model improves the baseline by 14.52%. [2025-11-13T08:28:33.953Z] Top recommended movies for user id 72: [2025-11-13T08:28:33.953Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:28:33.953Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:28:33.953Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:28:33.953Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:28:33.953Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:28:33.953Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17542.631 ms) ====== [2025-11-13T08:28:33.953Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-13T08:28:33.953Z] GC before operation: completed in 116.621 ms, heap usage 154.756 MB -> 89.515 MB. [2025-11-13T08:28:37.375Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:28:39.839Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:28:42.306Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:28:44.781Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:28:46.494Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:28:48.086Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:28:49.667Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:28:51.255Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:28:51.255Z] 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. [2025-11-13T08:28:51.255Z] The best model improves the baseline by 14.52%. [2025-11-13T08:28:51.255Z] Top recommended movies for user id 72: [2025-11-13T08:28:51.255Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:28:51.255Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:28:51.255Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:28:51.255Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:28:51.255Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:28:51.255Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17239.291 ms) ====== [2025-11-13T08:28:51.255Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-13T08:28:51.255Z] GC before operation: completed in 108.666 ms, heap usage 373.588 MB -> 89.798 MB. [2025-11-13T08:28:54.659Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:28:57.132Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:28:59.586Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:29:02.051Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:29:03.638Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:29:05.219Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:29:06.805Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:29:08.385Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:29:08.385Z] 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. [2025-11-13T08:29:08.385Z] The best model improves the baseline by 14.52%. [2025-11-13T08:29:08.385Z] Top recommended movies for user id 72: [2025-11-13T08:29:08.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:29:08.385Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:29:08.385Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:29:08.385Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:29:08.385Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:29:08.385Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16927.053 ms) ====== [2025-11-13T08:29:08.385Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-13T08:29:08.385Z] GC before operation: completed in 107.725 ms, heap usage 462.008 MB -> 90.228 MB. [2025-11-13T08:29:11.361Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:29:13.821Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:29:16.289Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:29:18.750Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:29:20.329Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:29:21.913Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:29:23.496Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:29:25.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:29:25.078Z] 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. [2025-11-13T08:29:25.078Z] The best model improves the baseline by 14.52%. [2025-11-13T08:29:25.078Z] Top recommended movies for user id 72: [2025-11-13T08:29:25.078Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:29:25.078Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:29:25.078Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:29:25.078Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:29:25.078Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:29:25.078Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16450.930 ms) ====== [2025-11-13T08:29:25.078Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-13T08:29:25.078Z] GC before operation: completed in 111.452 ms, heap usage 159.342 MB -> 89.828 MB. [2025-11-13T08:29:27.536Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:29:29.999Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:29:32.463Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:29:34.923Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:29:36.508Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:29:37.275Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:29:38.863Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:29:40.450Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:29:40.450Z] 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. [2025-11-13T08:29:40.450Z] The best model improves the baseline by 14.52%. [2025-11-13T08:29:41.213Z] Top recommended movies for user id 72: [2025-11-13T08:29:41.213Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:29:41.213Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:29:41.213Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:29:41.213Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:29:41.213Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:29:41.213Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15703.116 ms) ====== [2025-11-13T08:29:41.213Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-13T08:29:41.213Z] GC before operation: completed in 115.869 ms, heap usage 457.585 MB -> 90.349 MB. [2025-11-13T08:29:43.673Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:29:46.253Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:29:48.715Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:29:50.800Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:29:52.389Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:29:53.969Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:29:55.550Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:29:57.135Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:29:57.135Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T08:29:57.135Z] The best model improves the baseline by 14.52%. [2025-11-13T08:29:57.135Z] Top recommended movies for user id 72: [2025-11-13T08:29:57.135Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:29:57.135Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:29:57.135Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:29:57.135Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:29:57.135Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:29:57.135Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16173.756 ms) ====== [2025-11-13T08:29:57.135Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-13T08:29:57.135Z] GC before operation: completed in 105.092 ms, heap usage 298.049 MB -> 90.052 MB. [2025-11-13T08:29:59.598Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:30:02.087Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:30:04.563Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:30:07.043Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:30:08.626Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:30:10.217Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:30:11.808Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:30:13.403Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:30:13.403Z] 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. [2025-11-13T08:30:13.403Z] The best model improves the baseline by 14.52%. [2025-11-13T08:30:13.403Z] Top recommended movies for user id 72: [2025-11-13T08:30:13.403Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:30:13.403Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:30:13.403Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:30:13.403Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:30:13.403Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:30:13.403Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16194.964 ms) ====== [2025-11-13T08:30:13.403Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-13T08:30:13.403Z] GC before operation: completed in 109.709 ms, heap usage 266.965 MB -> 90.227 MB. [2025-11-13T08:30:16.002Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:30:18.481Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:30:20.956Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:30:23.425Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:30:24.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:30:25.781Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:30:27.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:30:28.957Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:30:28.957Z] 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. [2025-11-13T08:30:28.957Z] The best model improves the baseline by 14.52%. [2025-11-13T08:30:29.720Z] Top recommended movies for user id 72: [2025-11-13T08:30:29.720Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:30:29.720Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:30:29.720Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:30:29.720Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:30:29.720Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:30:29.720Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15803.523 ms) ====== [2025-11-13T08:30:29.720Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-13T08:30:29.720Z] GC before operation: completed in 109.855 ms, heap usage 204.831 MB -> 89.884 MB. [2025-11-13T08:30:32.192Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:30:34.830Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:30:36.432Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:30:38.905Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:30:40.502Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:30:42.090Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:30:43.682Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:30:45.398Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:30:45.398Z] 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. [2025-11-13T08:30:45.398Z] The best model improves the baseline by 14.52%. [2025-11-13T08:30:45.398Z] Top recommended movies for user id 72: [2025-11-13T08:30:45.398Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:30:45.398Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:30:45.398Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:30:45.398Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:30:45.398Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:30:45.398Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15920.548 ms) ====== [2025-11-13T08:30:45.398Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-13T08:30:45.398Z] GC before operation: completed in 104.707 ms, heap usage 462.667 MB -> 90.419 MB. [2025-11-13T08:30:47.961Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:30:50.449Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:30:53.030Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:30:55.496Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:30:57.088Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:30:58.680Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:31:00.266Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:31:01.032Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:31:01.799Z] 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. [2025-11-13T08:31:01.799Z] The best model improves the baseline by 14.52%. [2025-11-13T08:31:01.799Z] Top recommended movies for user id 72: [2025-11-13T08:31:01.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:31:01.799Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:31:01.799Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:31:01.799Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:31:01.799Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:31:01.799Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16155.953 ms) ====== [2025-11-13T08:31:01.799Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-13T08:31:01.799Z] GC before operation: completed in 99.241 ms, heap usage 110.587 MB -> 90.082 MB. [2025-11-13T08:31:04.262Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:31:06.729Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:31:09.218Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:31:11.710Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:31:13.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:31:15.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:31:15.972Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:31:17.565Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:31:18.329Z] 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. [2025-11-13T08:31:18.329Z] The best model improves the baseline by 14.52%. [2025-11-13T08:31:18.329Z] Top recommended movies for user id 72: [2025-11-13T08:31:18.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:31:18.329Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:31:18.329Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:31:18.329Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:31:18.329Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:31:18.329Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16349.191 ms) ====== [2025-11-13T08:31:18.329Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-13T08:31:18.329Z] GC before operation: completed in 108.298 ms, heap usage 412.137 MB -> 90.281 MB. [2025-11-13T08:31:20.788Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:31:23.299Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:31:25.804Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:31:28.303Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:31:29.102Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:31:30.698Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:31:32.304Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:31:33.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:31:33.901Z] 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. [2025-11-13T08:31:33.901Z] The best model improves the baseline by 14.52%. [2025-11-13T08:31:33.901Z] Top recommended movies for user id 72: [2025-11-13T08:31:33.901Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:31:33.901Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:31:33.901Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:31:33.901Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:31:33.901Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:31:33.901Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15777.150 ms) ====== [2025-11-13T08:31:33.901Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-13T08:31:33.901Z] GC before operation: completed in 104.876 ms, heap usage 153.133 MB -> 90.133 MB. [2025-11-13T08:31:36.378Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:31:38.852Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:31:41.342Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:31:43.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:31:45.558Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:31:46.327Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:31:47.948Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:31:49.554Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:31:49.554Z] 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. [2025-11-13T08:31:49.554Z] The best model improves the baseline by 14.52%. [2025-11-13T08:31:50.319Z] Top recommended movies for user id 72: [2025-11-13T08:31:50.319Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:31:50.319Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:31:50.319Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:31:50.319Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:31:50.319Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:31:50.319Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15844.376 ms) ====== [2025-11-13T08:31:50.319Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-13T08:31:50.319Z] GC before operation: completed in 112.187 ms, heap usage 548.516 MB -> 93.849 MB. [2025-11-13T08:31:52.795Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:31:55.325Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:31:57.435Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:31:59.028Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:32:00.614Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:32:02.219Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:32:02.995Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:32:04.605Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:32:04.605Z] 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. [2025-11-13T08:32:04.605Z] The best model improves the baseline by 14.52%. [2025-11-13T08:32:04.605Z] Top recommended movies for user id 72: [2025-11-13T08:32:04.605Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:32:04.605Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:32:04.605Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:32:04.605Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:32:04.605Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:32:04.605Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14830.136 ms) ====== [2025-11-13T08:32:04.605Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-13T08:32:05.370Z] GC before operation: completed in 111.086 ms, heap usage 260.328 MB -> 91.271 MB. [2025-11-13T08:32:07.829Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:32:09.426Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:32:11.904Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:32:14.373Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:32:15.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:32:16.747Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:32:18.330Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:32:19.933Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:32:19.933Z] 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. [2025-11-13T08:32:19.933Z] The best model improves the baseline by 14.52%. [2025-11-13T08:32:19.933Z] Top recommended movies for user id 72: [2025-11-13T08:32:19.933Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:32:19.933Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:32:19.933Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:32:19.933Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:32:19.933Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:32:19.933Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15220.149 ms) ====== [2025-11-13T08:32:19.933Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-13T08:32:20.702Z] GC before operation: completed in 114.460 ms, heap usage 212.764 MB -> 90.068 MB. [2025-11-13T08:32:23.174Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:32:24.780Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:32:27.301Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:32:29.784Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:32:31.375Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:32:32.971Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:32:34.557Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:32:35.325Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:32:36.098Z] 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. [2025-11-13T08:32:36.098Z] The best model improves the baseline by 14.52%. [2025-11-13T08:32:36.098Z] Top recommended movies for user id 72: [2025-11-13T08:32:36.098Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:32:36.098Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:32:36.098Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:32:36.098Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:32:36.098Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:32:36.098Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15685.326 ms) ====== [2025-11-13T08:32:36.098Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-13T08:32:36.098Z] GC before operation: completed in 101.588 ms, heap usage 252.101 MB -> 90.231 MB. [2025-11-13T08:32:38.583Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T08:32:41.080Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T08:32:42.954Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T08:32:45.437Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T08:32:46.211Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T08:32:47.794Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T08:32:49.391Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T08:32:50.981Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T08:32:50.981Z] 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. [2025-11-13T08:32:50.981Z] The best model improves the baseline by 14.52%. [2025-11-13T08:32:50.981Z] Top recommended movies for user id 72: [2025-11-13T08:32:50.981Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T08:32:50.981Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T08:32:50.981Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T08:32:50.981Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T08:32:50.981Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T08:32:50.981Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14727.024 ms) ====== [2025-11-13T08:32:50.981Z] ----------------------------------- [2025-11-13T08:32:50.981Z] renaissance-movie-lens_0_PASSED [2025-11-13T08:32:50.981Z] ----------------------------------- [2025-11-13T08:32:50.981Z] [2025-11-13T08:32:50.981Z] TEST TEARDOWN: [2025-11-13T08:32:50.981Z] Nothing to be done for teardown. [2025-11-13T08:32:50.981Z] renaissance-movie-lens_0 Finish Time: Thu Nov 13 08:32:50 2025 Epoch Time (ms): 1763022770890