[2025-12-04T09:13:13.174Z] Running test renaissance-movie-lens_0 ... [2025-12-04T09:13:13.174Z] =============================================== [2025-12-04T09:13:13.174Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 09:13:13 2025 Epoch Time (ms): 1764839593045 [2025-12-04T09:13:13.174Z] variation: NoOptions [2025-12-04T09:13:13.174Z] JVM_OPTIONS: [2025-12-04T09:13:13.174Z] { \ [2025-12-04T09:13:13.174Z] echo ""; echo "TEST SETUP:"; \ [2025-12-04T09:13:13.174Z] echo "Nothing to be done for setup."; \ [2025-12-04T09:13:13.174Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17648383431592/renaissance-movie-lens_0"; \ [2025-12-04T09:13:13.174Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17648383431592/renaissance-movie-lens_0"; \ [2025-12-04T09:13:13.174Z] echo ""; echo "TESTING:"; \ [2025-12-04T09:13:13.174Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-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_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17648383431592/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-04T09:13:13.174Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17648383431592/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-04T09:13:13.174Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-04T09:13:13.174Z] echo "Nothing to be done for teardown."; \ [2025-12-04T09:13:13.174Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17648383431592/TestTargetResult"; [2025-12-04T09:13:13.174Z] [2025-12-04T09:13:13.174Z] TEST SETUP: [2025-12-04T09:13:13.174Z] Nothing to be done for setup. [2025-12-04T09:13:13.174Z] [2025-12-04T09:13:13.174Z] TESTING: [2025-12-04T09:13:21.843Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-04T09:13:28.621Z] 09:13:28.479 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. [2025-12-04T09:13:32.007Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-04T09:13:32.007Z] Training: 60056, validation: 20285, test: 19854 [2025-12-04T09:13:32.007Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-04T09:13:32.007Z] GC before operation: completed in 118.606 ms, heap usage 298.028 MB -> 75.782 MB. [2025-12-04T09:13:40.262Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:13:45.825Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:13:49.219Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:13:52.589Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:13:54.157Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:13:55.727Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:13:58.167Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:13:59.738Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:13:59.738Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:14:00.508Z] The best model improves the baseline by 14.52%. [2025-12-04T09:14:00.508Z] Top recommended movies for user id 72: [2025-12-04T09:14:00.508Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:14:00.508Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:14:00.508Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:14:00.508Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:14:00.508Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:14:00.508Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28085.056 ms) ====== [2025-12-04T09:14:00.508Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-04T09:14:00.508Z] GC before operation: completed in 106.998 ms, heap usage 406.091 MB -> 86.745 MB. [2025-12-04T09:14:04.384Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:14:07.777Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:14:11.145Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:14:13.582Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:14:16.014Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:14:17.577Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:14:19.152Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:14:20.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:14:20.724Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:14:20.724Z] The best model improves the baseline by 14.52%. [2025-12-04T09:14:21.482Z] Top recommended movies for user id 72: [2025-12-04T09:14:21.482Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:14:21.482Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:14:21.482Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:14:21.482Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:14:21.482Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:14:21.482Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20653.427 ms) ====== [2025-12-04T09:14:21.482Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-04T09:14:21.482Z] GC before operation: completed in 106.446 ms, heap usage 272.879 MB -> 94.612 MB. [2025-12-04T09:14:23.919Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:14:26.416Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:14:29.808Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:14:32.246Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:14:33.807Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:14:35.371Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:14:36.935Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:14:38.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:14:38.517Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:14:38.517Z] The best model improves the baseline by 14.52%. [2025-12-04T09:14:38.517Z] Top recommended movies for user id 72: [2025-12-04T09:14:38.517Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:14:38.517Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:14:38.517Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:14:38.517Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:14:38.517Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:14:38.517Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17374.131 ms) ====== [2025-12-04T09:14:38.517Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-04T09:14:38.517Z] GC before operation: completed in 104.138 ms, heap usage 451.359 MB -> 89.556 MB. [2025-12-04T09:14:41.328Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:14:43.766Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:14:46.239Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:14:49.608Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:14:50.389Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:14:51.966Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:14:53.529Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:14:55.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:14:55.861Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:14:55.861Z] The best model improves the baseline by 14.52%. [2025-12-04T09:14:55.861Z] Top recommended movies for user id 72: [2025-12-04T09:14:55.861Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:14:55.861Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:14:55.861Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:14:55.861Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:14:55.861Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:14:55.861Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16999.306 ms) ====== [2025-12-04T09:14:55.861Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-04T09:14:55.861Z] GC before operation: completed in 113.487 ms, heap usage 217.641 MB -> 89.509 MB. [2025-12-04T09:14:58.294Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:15:00.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:15:04.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:15:05.682Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:15:07.255Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:15:08.822Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:15:10.387Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:15:11.957Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:15:11.958Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:15:12.715Z] The best model improves the baseline by 14.52%. [2025-12-04T09:15:12.715Z] Top recommended movies for user id 72: [2025-12-04T09:15:12.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:15:12.715Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:15:12.715Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:15:12.715Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:15:12.715Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:15:12.715Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16625.651 ms) ====== [2025-12-04T09:15:12.715Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-04T09:15:12.715Z] GC before operation: completed in 110.953 ms, heap usage 443.389 MB -> 89.827 MB. [2025-12-04T09:15:15.161Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:15:17.599Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:15:20.031Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:15:22.473Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:15:24.040Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:15:25.610Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:15:27.680Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:15:28.441Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:15:28.441Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:15:28.441Z] The best model improves the baseline by 14.52%. [2025-12-04T09:15:29.200Z] Top recommended movies for user id 72: [2025-12-04T09:15:29.200Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:15:29.200Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:15:29.200Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:15:29.200Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:15:29.200Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:15:29.200Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16312.447 ms) ====== [2025-12-04T09:15:29.200Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-04T09:15:29.200Z] GC before operation: completed in 104.315 ms, heap usage 288.815 MB -> 90.027 MB. [2025-12-04T09:15:31.631Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:15:34.056Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:15:36.493Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:15:38.935Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:15:40.503Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:15:41.274Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:15:42.844Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:15:44.645Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:15:44.645Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:15:44.645Z] The best model improves the baseline by 14.52%. [2025-12-04T09:15:44.645Z] Top recommended movies for user id 72: [2025-12-04T09:15:44.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:15:44.645Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:15:44.645Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:15:44.645Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:15:44.645Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:15:44.645Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15675.549 ms) ====== [2025-12-04T09:15:44.645Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-04T09:15:45.402Z] GC before operation: completed in 109.794 ms, heap usage 276.059 MB -> 89.955 MB. [2025-12-04T09:15:47.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:15:53.353Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:15:56.731Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:15:59.161Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:16:00.729Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:16:02.306Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:16:03.062Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:16:04.624Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:16:04.624Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:16:04.624Z] The best model improves the baseline by 14.52%. [2025-12-04T09:16:05.387Z] Top recommended movies for user id 72: [2025-12-04T09:16:05.387Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:16:05.387Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:16:05.387Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:16:05.387Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:16:05.387Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:16:05.387Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20292.043 ms) ====== [2025-12-04T09:16:05.387Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-04T09:16:05.387Z] GC before operation: completed in 110.211 ms, heap usage 393.798 MB -> 95.776 MB. [2025-12-04T09:16:08.069Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:16:10.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:16:12.973Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:16:14.545Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:16:16.110Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:16:17.720Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:16:19.285Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:16:20.859Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:16:20.859Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:16:20.859Z] The best model improves the baseline by 14.52%. [2025-12-04T09:16:20.859Z] Top recommended movies for user id 72: [2025-12-04T09:16:20.859Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:16:20.859Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:16:20.859Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:16:20.859Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:16:20.859Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:16:20.859Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15759.538 ms) ====== [2025-12-04T09:16:20.859Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-04T09:16:20.859Z] GC before operation: completed in 105.654 ms, heap usage 501.492 MB -> 92.587 MB. [2025-12-04T09:16:23.285Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:16:25.714Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:16:28.146Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:16:30.575Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:16:32.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:16:32.896Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:16:34.479Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:16:36.053Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:16:36.053Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:16:36.053Z] The best model improves the baseline by 14.52%. [2025-12-04T09:16:36.053Z] Top recommended movies for user id 72: [2025-12-04T09:16:36.053Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:16:36.053Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:16:36.053Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:16:36.053Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:16:36.053Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:16:36.053Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15343.105 ms) ====== [2025-12-04T09:16:36.053Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-04T09:16:36.805Z] GC before operation: completed in 101.718 ms, heap usage 516.106 MB -> 90.481 MB. [2025-12-04T09:16:39.257Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:16:41.693Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:16:44.598Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:16:47.032Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:16:49.154Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:16:49.906Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:16:51.473Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:16:53.038Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:16:53.038Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:16:53.038Z] The best model improves the baseline by 14.52%. [2025-12-04T09:16:53.038Z] Top recommended movies for user id 72: [2025-12-04T09:16:53.038Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:16:53.038Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:16:53.038Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:16:53.038Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:16:53.038Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:16:53.038Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16513.750 ms) ====== [2025-12-04T09:16:53.038Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-04T09:16:53.038Z] GC before operation: completed in 105.651 ms, heap usage 263.835 MB -> 89.934 MB. [2025-12-04T09:16:55.478Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:16:57.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:17:00.349Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:17:02.960Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:17:03.727Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:17:05.288Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:17:06.850Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:17:08.431Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:17:08.431Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:17:08.431Z] The best model improves the baseline by 14.52%. [2025-12-04T09:17:08.431Z] Top recommended movies for user id 72: [2025-12-04T09:17:08.431Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:17:08.431Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:17:08.431Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:17:08.431Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:17:08.431Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:17:08.431Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15401.759 ms) ====== [2025-12-04T09:17:08.431Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-04T09:17:08.431Z] GC before operation: completed in 106.698 ms, heap usage 257.395 MB -> 90.122 MB. [2025-12-04T09:17:10.859Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:17:13.335Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:17:15.764Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:17:18.194Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:17:19.759Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:17:21.318Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:17:22.882Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:17:23.637Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:17:24.394Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:17:24.394Z] The best model improves the baseline by 14.52%. [2025-12-04T09:17:24.394Z] Top recommended movies for user id 72: [2025-12-04T09:17:24.394Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:17:24.394Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:17:24.394Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:17:24.394Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:17:24.394Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:17:24.394Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15699.382 ms) ====== [2025-12-04T09:17:24.394Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-04T09:17:24.394Z] GC before operation: completed in 106.302 ms, heap usage 235.528 MB -> 90.256 MB. [2025-12-04T09:17:26.957Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:17:29.392Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:17:31.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:17:33.897Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:17:35.455Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:17:37.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:17:38.587Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:17:39.342Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:17:40.107Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:17:40.107Z] The best model improves the baseline by 14.52%. [2025-12-04T09:17:40.107Z] Top recommended movies for user id 72: [2025-12-04T09:17:40.107Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:17:40.107Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:17:40.107Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:17:40.107Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:17:40.107Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:17:40.107Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15587.305 ms) ====== [2025-12-04T09:17:40.107Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-04T09:17:40.107Z] GC before operation: completed in 108.040 ms, heap usage 642.070 MB -> 93.723 MB. [2025-12-04T09:17:42.544Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:17:44.978Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:17:47.407Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:17:49.840Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:17:51.410Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:17:52.974Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:17:54.543Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:17:56.107Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:17:56.107Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:17:56.107Z] The best model improves the baseline by 14.52%. [2025-12-04T09:17:56.107Z] Top recommended movies for user id 72: [2025-12-04T09:17:56.107Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:17:56.107Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:17:56.107Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:17:56.107Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:17:56.107Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:17:56.107Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16008.186 ms) ====== [2025-12-04T09:17:56.107Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-04T09:17:56.107Z] GC before operation: completed in 106.932 ms, heap usage 179.776 MB -> 94.798 MB. [2025-12-04T09:18:00.805Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:18:03.237Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:18:05.685Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:18:08.118Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:18:09.681Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:18:10.442Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:18:12.882Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:18:13.639Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:18:13.639Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:18:13.639Z] The best model improves the baseline by 14.52%. [2025-12-04T09:18:14.890Z] Top recommended movies for user id 72: [2025-12-04T09:18:14.890Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:18:14.890Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:18:14.890Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:18:14.890Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:18:14.890Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:18:14.890Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17895.337 ms) ====== [2025-12-04T09:18:14.890Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-04T09:18:14.890Z] GC before operation: completed in 102.823 ms, heap usage 122.312 MB -> 90.005 MB. [2025-12-04T09:18:16.469Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:18:18.920Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:18:21.360Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:18:23.788Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:18:25.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:18:26.122Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:18:27.688Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:18:29.254Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:18:30.817Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:18:30.817Z] The best model improves the baseline by 14.52%. [2025-12-04T09:18:30.817Z] Top recommended movies for user id 72: [2025-12-04T09:18:30.817Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:18:30.817Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:18:30.817Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:18:30.817Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:18:30.817Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:18:30.817Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16409.294 ms) ====== [2025-12-04T09:18:30.817Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-04T09:18:30.817Z] GC before operation: completed in 101.951 ms, heap usage 183.049 MB -> 90.147 MB. [2025-12-04T09:18:33.254Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:18:40.434Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:18:43.806Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:18:50.523Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:18:56.423Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:18:57.185Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:18:58.757Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:19:00.339Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:19:00.339Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:19:00.339Z] The best model improves the baseline by 14.52%. [2025-12-04T09:19:00.339Z] Top recommended movies for user id 72: [2025-12-04T09:19:00.339Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:19:00.339Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:19:00.339Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:19:00.339Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:19:00.339Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:19:00.339Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (29931.757 ms) ====== [2025-12-04T09:19:00.339Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-04T09:19:01.092Z] GC before operation: completed in 108.117 ms, heap usage 577.716 MB -> 93.709 MB. [2025-12-04T09:19:03.570Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:19:05.652Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:19:09.015Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:19:10.579Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:19:12.146Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:19:13.740Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:19:14.504Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:19:16.090Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:19:16.090Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:19:16.090Z] The best model improves the baseline by 14.52%. [2025-12-04T09:19:16.846Z] Top recommended movies for user id 72: [2025-12-04T09:19:16.846Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:19:16.846Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:19:16.846Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:19:16.846Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:19:16.846Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:19:16.846Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15790.802 ms) ====== [2025-12-04T09:19:16.846Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-04T09:19:16.846Z] GC before operation: completed in 104.192 ms, heap usage 530.914 MB -> 92.988 MB. [2025-12-04T09:19:19.283Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T09:19:21.728Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T09:19:24.157Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T09:19:25.726Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T09:19:27.289Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T09:19:28.899Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T09:19:30.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T09:19:31.226Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T09:19:31.980Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T09:19:31.980Z] The best model improves the baseline by 14.52%. [2025-12-04T09:19:31.980Z] Top recommended movies for user id 72: [2025-12-04T09:19:31.980Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T09:19:31.981Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T09:19:31.981Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T09:19:31.981Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T09:19:31.981Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T09:19:31.981Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15132.749 ms) ====== [2025-12-04T09:19:31.981Z] ----------------------------------- [2025-12-04T09:19:31.981Z] renaissance-movie-lens_0_PASSED [2025-12-04T09:19:31.981Z] ----------------------------------- [2025-12-04T09:19:31.981Z] [2025-12-04T09:19:31.981Z] TEST TEARDOWN: [2025-12-04T09:19:31.981Z] Nothing to be done for teardown. [2025-12-04T09:19:31.981Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 09:19:31 2025 Epoch Time (ms): 1764839971880