[2025-09-04T02:47:39.522Z] Running test renaissance-movie-lens_0 ... [2025-09-04T02:47:39.522Z] =============================================== [2025-09-04T02:47:39.522Z] renaissance-movie-lens_0 Start Time: Thu Sep 4 02:47:38 2025 Epoch Time (ms): 1756954058466 [2025-09-04T02:47:39.522Z] variation: NoOptions [2025-09-04T02:47:39.522Z] JVM_OPTIONS: [2025-09-04T02:47:39.522Z] { \ [2025-09-04T02:47:39.522Z] echo ""; echo "TEST SETUP:"; \ [2025-09-04T02:47:39.522Z] echo "Nothing to be done for setup."; \ [2025-09-04T02:47:39.522Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1_rerun/aqa-tests/TKG/../TKG/output_17569521881397/renaissance-movie-lens_0"; \ [2025-09-04T02:47:39.522Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1_rerun/aqa-tests/TKG/../TKG/output_17569521881397/renaissance-movie-lens_0"; \ [2025-09-04T02:47:39.522Z] echo ""; echo "TESTING:"; \ [2025-09-04T02:47:39.522Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1_rerun/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_aarch64_linux_testList_1_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1_rerun/aqa-tests/TKG/../TKG/output_17569521881397/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-04T02:47:39.522Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1_rerun/aqa-tests/TKG/../TKG/output_17569521881397/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-04T02:47:39.522Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-04T02:47:39.522Z] echo "Nothing to be done for teardown."; \ [2025-09-04T02:47:39.522Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1_rerun/aqa-tests/TKG/../TKG/output_17569521881397/TestTargetResult"; [2025-09-04T02:47:39.522Z] [2025-09-04T02:47:39.522Z] TEST SETUP: [2025-09-04T02:47:39.522Z] Nothing to be done for setup. [2025-09-04T02:47:39.522Z] [2025-09-04T02:47:39.522Z] TESTING: [2025-09-04T02:47:53.196Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-04T02:48:14.869Z] 02:48:14.694 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-09-04T02:48:23.196Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-04T02:48:24.179Z] Training: 60056, validation: 20285, test: 19854 [2025-09-04T02:48:24.179Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-04T02:48:24.179Z] GC before operation: completed in 378.642 ms, heap usage 278.528 MB -> 76.077 MB. [2025-09-04T02:48:45.921Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:48:58.185Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:49:08.152Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:49:19.899Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:49:25.416Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:49:30.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:49:36.381Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:49:41.851Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:49:41.851Z] 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. [2025-09-04T02:49:42.826Z] The best model improves the baseline by 14.52%. [2025-09-04T02:49:43.799Z] Top recommended movies for user id 72: [2025-09-04T02:49:43.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:49:43.799Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:49:43.799Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:49:43.799Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:49:43.799Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:49:43.799Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (79252.601 ms) ====== [2025-09-04T02:49:43.799Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-04T02:49:43.799Z] GC before operation: completed in 399.003 ms, heap usage 234.029 MB -> 86.658 MB. [2025-09-04T02:49:53.707Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:50:02.442Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:50:10.738Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:50:19.056Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:50:23.299Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:50:28.832Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:50:34.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:50:38.563Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:50:39.536Z] 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. [2025-09-04T02:50:39.536Z] The best model improves the baseline by 14.52%. [2025-09-04T02:50:39.536Z] Top recommended movies for user id 72: [2025-09-04T02:50:39.536Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:50:39.536Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:50:39.536Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:50:39.536Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:50:39.536Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:50:39.536Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (55789.486 ms) ====== [2025-09-04T02:50:39.536Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-04T02:50:40.508Z] GC before operation: completed in 377.622 ms, heap usage 176.357 MB -> 88.845 MB. [2025-09-04T02:50:47.346Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:50:54.161Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:51:01.735Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:51:08.537Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:51:14.034Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:51:18.274Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:51:22.522Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:51:26.864Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:51:26.864Z] 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. [2025-09-04T02:51:27.836Z] The best model improves the baseline by 14.52%. [2025-09-04T02:51:27.837Z] Top recommended movies for user id 72: [2025-09-04T02:51:27.837Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:51:27.837Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:51:27.837Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:51:27.837Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:51:27.837Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:51:27.837Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (47579.054 ms) ====== [2025-09-04T02:51:27.837Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-04T02:51:27.837Z] GC before operation: completed in 407.760 ms, heap usage 377.457 MB -> 89.669 MB. [2025-09-04T02:51:34.850Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:51:41.652Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:51:48.467Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:51:56.785Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:52:01.715Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:52:05.981Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:52:09.044Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:52:13.288Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:52:14.256Z] 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. [2025-09-04T02:52:14.256Z] The best model improves the baseline by 14.52%. [2025-09-04T02:52:15.248Z] Top recommended movies for user id 72: [2025-09-04T02:52:15.248Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:52:15.248Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:52:15.248Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:52:15.248Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:52:15.248Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:52:15.248Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (46806.216 ms) ====== [2025-09-04T02:52:15.248Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-04T02:52:15.248Z] GC before operation: completed in 375.123 ms, heap usage 139.212 MB -> 91.588 MB. [2025-09-04T02:52:22.091Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:52:28.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:52:37.263Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:52:44.092Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:52:48.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:52:53.837Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:52:58.050Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:53:01.116Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:53:02.556Z] 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. [2025-09-04T02:53:02.556Z] The best model improves the baseline by 14.52%. [2025-09-04T02:53:02.556Z] Top recommended movies for user id 72: [2025-09-04T02:53:02.556Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:53:02.556Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:53:02.556Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:53:02.556Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:53:02.556Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:53:02.556Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (47077.788 ms) ====== [2025-09-04T02:53:02.556Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-04T02:53:02.556Z] GC before operation: completed in 397.443 ms, heap usage 161.617 MB -> 89.656 MB. [2025-09-04T02:53:09.396Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:53:16.313Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:53:21.774Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:53:28.687Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:53:32.956Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:53:37.216Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:53:41.444Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:53:44.540Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:53:45.515Z] 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. [2025-09-04T02:53:45.515Z] The best model improves the baseline by 14.52%. [2025-09-04T02:53:46.492Z] Top recommended movies for user id 72: [2025-09-04T02:53:46.492Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:53:46.492Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:53:46.492Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:53:46.492Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:53:46.492Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:53:46.492Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43326.125 ms) ====== [2025-09-04T02:53:46.492Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-04T02:53:46.492Z] GC before operation: completed in 347.671 ms, heap usage 160.405 MB -> 89.938 MB. [2025-09-04T02:53:53.328Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:53:58.809Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:54:05.922Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:54:11.400Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:54:15.617Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:54:19.874Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:54:24.106Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:54:27.348Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:54:28.322Z] 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. [2025-09-04T02:54:28.322Z] The best model improves the baseline by 14.52%. [2025-09-04T02:54:29.291Z] Top recommended movies for user id 72: [2025-09-04T02:54:29.291Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:54:29.291Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:54:29.291Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:54:29.291Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:54:29.291Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:54:29.291Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42277.752 ms) ====== [2025-09-04T02:54:29.291Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-04T02:54:29.291Z] GC before operation: completed in 399.169 ms, heap usage 232.715 MB -> 89.896 MB. [2025-09-04T02:54:36.094Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:54:41.574Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:54:48.426Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:54:55.275Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:54:59.504Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:55:03.359Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:55:07.642Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:55:11.896Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:55:11.896Z] 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. [2025-09-04T02:55:11.896Z] The best model improves the baseline by 14.52%. [2025-09-04T02:55:12.873Z] Top recommended movies for user id 72: [2025-09-04T02:55:12.873Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:55:12.873Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:55:12.873Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:55:12.873Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:55:12.873Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:55:12.873Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (43394.001 ms) ====== [2025-09-04T02:55:12.873Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-04T02:55:12.873Z] GC before operation: completed in 342.089 ms, heap usage 387.454 MB -> 90.403 MB. [2025-09-04T02:55:19.740Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:55:25.231Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:55:32.207Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:55:39.026Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:55:42.094Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:55:46.340Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:55:49.424Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:55:53.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:55:54.629Z] 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. [2025-09-04T02:55:54.629Z] The best model improves the baseline by 14.52%. [2025-09-04T02:55:54.629Z] Top recommended movies for user id 72: [2025-09-04T02:55:54.629Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:55:54.629Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:55:54.629Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:55:54.629Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:55:54.629Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:55:54.629Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (41725.433 ms) ====== [2025-09-04T02:55:54.629Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-04T02:55:54.629Z] GC before operation: completed in 381.475 ms, heap usage 99.617 MB -> 90.246 MB. [2025-09-04T02:56:01.454Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:56:07.380Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:56:12.831Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:56:18.306Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:56:22.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:56:25.622Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:56:28.776Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:56:33.199Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:56:33.199Z] 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. [2025-09-04T02:56:33.199Z] The best model improves the baseline by 14.52%. [2025-09-04T02:56:34.173Z] Top recommended movies for user id 72: [2025-09-04T02:56:34.173Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:56:34.173Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:56:34.173Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:56:34.173Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:56:34.173Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:56:34.173Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (39045.602 ms) ====== [2025-09-04T02:56:34.173Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-04T02:56:34.173Z] GC before operation: completed in 334.951 ms, heap usage 291.948 MB -> 90.367 MB. [2025-09-04T02:56:41.041Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:56:46.495Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:56:51.958Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:56:58.770Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:57:01.844Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:57:05.626Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:57:08.705Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:57:11.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:57:12.757Z] 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. [2025-09-04T02:57:12.757Z] The best model improves the baseline by 14.52%. [2025-09-04T02:57:12.757Z] Top recommended movies for user id 72: [2025-09-04T02:57:12.757Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:57:12.757Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:57:12.757Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:57:12.757Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:57:12.757Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:57:12.757Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (38597.459 ms) ====== [2025-09-04T02:57:12.757Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-04T02:57:13.732Z] GC before operation: completed in 292.533 ms, heap usage 139.669 MB -> 92.735 MB. [2025-09-04T02:57:19.197Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:57:24.652Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:57:30.249Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:57:35.701Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:57:38.777Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:57:43.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:57:46.097Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:57:50.332Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:57:50.332Z] 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. [2025-09-04T02:57:51.301Z] The best model improves the baseline by 14.52%. [2025-09-04T02:57:51.301Z] Top recommended movies for user id 72: [2025-09-04T02:57:51.301Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:57:51.301Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:57:51.301Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:57:51.301Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:57:51.301Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:57:51.301Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (37840.779 ms) ====== [2025-09-04T02:57:51.301Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-04T02:57:51.301Z] GC before operation: completed in 373.768 ms, heap usage 153.879 MB -> 90.071 MB. [2025-09-04T02:57:58.100Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:58:04.322Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:58:09.788Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:58:14.002Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:58:18.224Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:58:21.298Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:58:24.358Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:58:27.443Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:58:28.416Z] 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. [2025-09-04T02:58:28.416Z] The best model improves the baseline by 14.52%. [2025-09-04T02:58:28.416Z] Top recommended movies for user id 72: [2025-09-04T02:58:28.416Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:58:28.416Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:58:28.416Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:58:28.417Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:58:28.417Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:58:28.417Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (37260.477 ms) ====== [2025-09-04T02:58:28.417Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-04T02:58:29.390Z] GC before operation: completed in 331.466 ms, heap usage 789.611 MB -> 94.227 MB. [2025-09-04T02:58:34.838Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:58:40.309Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:58:45.765Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:58:51.246Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:58:55.484Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:58:58.588Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:59:03.538Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:59:06.622Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:59:06.622Z] 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. [2025-09-04T02:59:06.622Z] The best model improves the baseline by 14.52%. [2025-09-04T02:59:07.597Z] Top recommended movies for user id 72: [2025-09-04T02:59:07.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:59:07.597Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:59:07.597Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:59:07.597Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:59:07.597Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:59:07.597Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38165.133 ms) ====== [2025-09-04T02:59:07.597Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-04T02:59:07.597Z] GC before operation: completed in 470.005 ms, heap usage 154.283 MB -> 90.040 MB. [2025-09-04T02:59:13.062Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T02:59:19.877Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T02:59:25.339Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T02:59:32.180Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T02:59:36.421Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T02:59:39.505Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T02:59:43.734Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T02:59:47.963Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T02:59:48.934Z] 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. [2025-09-04T02:59:48.934Z] The best model improves the baseline by 14.52%. [2025-09-04T02:59:48.934Z] Top recommended movies for user id 72: [2025-09-04T02:59:48.934Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T02:59:48.934Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T02:59:48.934Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T02:59:48.934Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T02:59:48.934Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T02:59:48.934Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (41260.345 ms) ====== [2025-09-04T02:59:48.934Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-04T02:59:49.905Z] GC before operation: completed in 398.200 ms, heap usage 100.981 MB -> 90.336 MB. [2025-09-04T02:59:56.711Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:00:03.121Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:00:08.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:00:14.071Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:00:17.142Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:00:21.380Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:00:24.453Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:00:27.504Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:00:28.473Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-04T03:00:28.473Z] The best model improves the baseline by 14.52%. [2025-09-04T03:00:29.446Z] Top recommended movies for user id 72: [2025-09-04T03:00:29.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T03:00:29.446Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T03:00:29.446Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T03:00:29.446Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T03:00:29.446Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T03:00:29.446Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (39720.281 ms) ====== [2025-09-04T03:00:29.446Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-04T03:00:29.446Z] GC before operation: completed in 314.503 ms, heap usage 133.448 MB -> 90.084 MB. [2025-09-04T03:00:34.907Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:00:41.704Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:00:48.497Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:00:53.979Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:00:57.054Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:01:01.287Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:01:05.100Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:01:08.191Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:01:08.191Z] 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. [2025-09-04T03:01:09.153Z] The best model improves the baseline by 14.52%. [2025-09-04T03:01:09.153Z] Top recommended movies for user id 72: [2025-09-04T03:01:09.153Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T03:01:09.153Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T03:01:09.153Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T03:01:09.153Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T03:01:09.153Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T03:01:09.153Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (39614.446 ms) ====== [2025-09-04T03:01:09.153Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-04T03:01:09.153Z] GC before operation: completed in 339.067 ms, heap usage 516.513 MB -> 90.684 MB. [2025-09-04T03:01:15.961Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:01:21.418Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:01:26.970Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:01:32.618Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:01:35.685Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:01:39.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:01:43.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:01:46.079Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:01:47.050Z] 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. [2025-09-04T03:01:47.050Z] The best model improves the baseline by 14.52%. [2025-09-04T03:01:48.027Z] Top recommended movies for user id 72: [2025-09-04T03:01:48.027Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T03:01:48.027Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T03:01:48.027Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T03:01:48.027Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T03:01:48.027Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T03:01:48.027Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (38207.323 ms) ====== [2025-09-04T03:01:48.027Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-04T03:01:48.027Z] GC before operation: completed in 427.311 ms, heap usage 249.711 MB -> 90.167 MB. [2025-09-04T03:01:53.501Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:02:00.302Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:02:05.253Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:02:12.069Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:02:15.141Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:02:18.208Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:02:21.278Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:02:25.478Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:02:25.478Z] 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. [2025-09-04T03:02:25.478Z] The best model improves the baseline by 14.52%. [2025-09-04T03:02:26.455Z] Top recommended movies for user id 72: [2025-09-04T03:02:26.455Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T03:02:26.455Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T03:02:26.455Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T03:02:26.455Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T03:02:26.455Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T03:02:26.455Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (37942.587 ms) ====== [2025-09-04T03:02:26.455Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-04T03:02:26.455Z] GC before operation: completed in 415.264 ms, heap usage 495.825 MB -> 90.618 MB. [2025-09-04T03:02:31.898Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:02:37.395Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:02:44.210Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:02:49.674Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:02:52.733Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:02:56.955Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:03:00.020Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:03:03.441Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:03:04.421Z] 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. [2025-09-04T03:03:04.421Z] The best model improves the baseline by 14.52%. [2025-09-04T03:03:04.421Z] Top recommended movies for user id 72: [2025-09-04T03:03:04.421Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T03:03:04.421Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T03:03:04.421Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T03:03:04.421Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T03:03:04.421Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T03:03:04.421Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (38052.787 ms) ====== [2025-09-04T03:03:06.416Z] ----------------------------------- [2025-09-04T03:03:06.416Z] renaissance-movie-lens_0_PASSED [2025-09-04T03:03:06.416Z] ----------------------------------- [2025-09-04T03:03:06.416Z] [2025-09-04T03:03:06.416Z] TEST TEARDOWN: [2025-09-04T03:03:06.416Z] Nothing to be done for teardown. [2025-09-04T03:03:06.416Z] renaissance-movie-lens_0 Finish Time: Thu Sep 4 03:03:05 2025 Epoch Time (ms): 1756954985816