[2025-12-04T05:10:12.484Z] Running test renaissance-movie-lens_0 ... [2025-12-04T05:10:12.484Z] =============================================== [2025-12-04T05:10:12.484Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 05:10:12 2025 Epoch Time (ms): 1764825012394 [2025-12-04T05:10:12.484Z] variation: NoOptions [2025-12-04T05:10:12.484Z] JVM_OPTIONS: [2025-12-04T05:10:12.484Z] { \ [2025-12-04T05:10:12.484Z] echo ""; echo "TEST SETUP:"; \ [2025-12-04T05:10:12.484Z] echo "Nothing to be done for setup."; \ [2025-12-04T05:10:12.484Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17648250118574/renaissance-movie-lens_0"; \ [2025-12-04T05:10:12.484Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17648250118574/renaissance-movie-lens_0"; \ [2025-12-04T05:10:12.484Z] echo ""; echo "TESTING:"; \ [2025-12-04T05:10:12.484Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_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_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17648250118574/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-04T05:10:12.484Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17648250118574/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-04T05:10:12.484Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-04T05:10:12.484Z] echo "Nothing to be done for teardown."; \ [2025-12-04T05:10:12.484Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17648250118574/TestTargetResult"; [2025-12-04T05:10:12.484Z] [2025-12-04T05:10:12.484Z] TEST SETUP: [2025-12-04T05:10:12.484Z] Nothing to be done for setup. [2025-12-04T05:10:12.484Z] [2025-12-04T05:10:12.484Z] TESTING: [2025-12-04T05:10:23.428Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-04T05:10:34.243Z] 05:10:33.798 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-12-04T05:10:38.351Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-04T05:10:39.887Z] Training: 60056, validation: 20285, test: 19854 [2025-12-04T05:10:39.887Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-04T05:10:39.887Z] GC before operation: completed in 522.836 ms, heap usage 259.999 MB -> 74.465 MB. [2025-12-04T05:10:52.987Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:11:02.238Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:11:11.708Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:11:18.228Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:11:26.228Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:11:29.427Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:11:34.658Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:11:38.900Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:11:39.610Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:11:40.428Z] The best model improves the baseline by 14.34%. [2025-12-04T05:11:40.428Z] Top recommended movies for user id 72: [2025-12-04T05:11:40.428Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:11:40.428Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:11:40.428Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:11:40.428Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:11:40.428Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:11:40.428Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (60219.446 ms) ====== [2025-12-04T05:11:40.428Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-04T05:11:41.099Z] GC before operation: completed in 488.892 ms, heap usage 279.821 MB -> 88.546 MB. [2025-12-04T05:11:48.723Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:11:55.079Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:12:03.057Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:12:11.001Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:12:15.272Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:12:19.198Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:12:24.616Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:12:30.026Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:12:30.728Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:12:30.728Z] The best model improves the baseline by 14.34%. [2025-12-04T05:12:31.421Z] Top recommended movies for user id 72: [2025-12-04T05:12:31.421Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:12:31.421Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:12:31.421Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:12:31.421Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:12:31.421Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:12:31.421Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (50334.268 ms) ====== [2025-12-04T05:12:31.421Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-04T05:12:32.118Z] GC before operation: completed in 668.586 ms, heap usage 147.227 MB -> 86.651 MB. [2025-12-04T05:12:39.980Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:12:46.478Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:12:52.811Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:12:58.008Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:13:02.098Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:13:06.128Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:13:10.386Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:13:13.630Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:13:14.363Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:13:14.363Z] The best model improves the baseline by 14.34%. [2025-12-04T05:13:15.008Z] Top recommended movies for user id 72: [2025-12-04T05:13:15.008Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:13:15.008Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:13:15.008Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:13:15.008Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:13:15.008Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:13:15.008Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (42813.448 ms) ====== [2025-12-04T05:13:15.008Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-04T05:13:15.008Z] GC before operation: completed in 327.771 ms, heap usage 327.138 MB -> 87.508 MB. [2025-12-04T05:13:21.564Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:13:26.738Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:13:32.989Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:13:39.391Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:13:43.527Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:13:46.654Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:13:50.731Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:13:54.856Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:13:54.856Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:13:54.856Z] The best model improves the baseline by 14.34%. [2025-12-04T05:13:55.558Z] Top recommended movies for user id 72: [2025-12-04T05:13:55.558Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:13:55.558Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:13:55.558Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:13:55.558Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:13:55.558Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:13:55.558Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (40224.308 ms) ====== [2025-12-04T05:13:55.558Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-04T05:13:55.558Z] GC before operation: completed in 371.756 ms, heap usage 268.668 MB -> 87.700 MB. [2025-12-04T05:14:01.892Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:14:11.318Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:14:19.236Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:14:25.596Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:14:28.677Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:14:33.938Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:14:37.989Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:14:41.973Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:14:41.973Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:14:41.973Z] The best model improves the baseline by 14.34%. [2025-12-04T05:14:42.693Z] Top recommended movies for user id 72: [2025-12-04T05:14:42.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:14:42.693Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:14:42.693Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:14:42.693Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:14:42.693Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:14:42.693Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (46704.894 ms) ====== [2025-12-04T05:14:42.693Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-04T05:14:42.693Z] GC before operation: completed in 418.632 ms, heap usage 184.344 MB -> 87.480 MB. [2025-12-04T05:14:49.045Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:14:55.552Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:15:03.178Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:15:08.258Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:15:12.463Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:15:15.659Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:15:19.673Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:15:23.735Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:15:24.391Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:15:24.391Z] The best model improves the baseline by 14.34%. [2025-12-04T05:15:24.391Z] Top recommended movies for user id 72: [2025-12-04T05:15:24.391Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:15:24.391Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:15:24.391Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:15:24.391Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:15:24.391Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:15:24.391Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (41845.660 ms) ====== [2025-12-04T05:15:24.391Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-04T05:15:25.109Z] GC before operation: completed in 343.304 ms, heap usage 177.772 MB -> 87.807 MB. [2025-12-04T05:15:31.648Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:15:38.069Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:15:45.819Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:15:51.004Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:15:55.140Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:15:59.137Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:16:06.552Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:16:06.552Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:16:07.234Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:16:07.234Z] The best model improves the baseline by 14.34%. [2025-12-04T05:16:07.234Z] Top recommended movies for user id 72: [2025-12-04T05:16:07.234Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:16:07.234Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:16:07.234Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:16:07.234Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:16:07.234Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:16:07.234Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42346.190 ms) ====== [2025-12-04T05:16:07.234Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-04T05:16:08.018Z] GC before operation: completed in 417.052 ms, heap usage 288.535 MB -> 87.989 MB. [2025-12-04T05:16:19.753Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:16:20.473Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:16:26.259Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:16:34.266Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:16:37.418Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:16:40.539Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:16:45.375Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:16:51.156Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:16:51.156Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:16:51.156Z] The best model improves the baseline by 14.34%. [2025-12-04T05:16:51.878Z] Top recommended movies for user id 72: [2025-12-04T05:16:51.878Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:16:51.878Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:16:51.878Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:16:51.878Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:16:51.878Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:16:51.878Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (41260.192 ms) ====== [2025-12-04T05:16:51.878Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-04T05:16:51.878Z] GC before operation: completed in 307.011 ms, heap usage 197.565 MB -> 90.129 MB. [2025-12-04T05:16:54.981Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:17:01.752Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:17:10.508Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:17:18.713Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:17:18.713Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:17:28.637Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:17:28.637Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:17:28.637Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:17:28.637Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:17:28.637Z] The best model improves the baseline by 14.34%. [2025-12-04T05:17:29.342Z] Top recommended movies for user id 72: [2025-12-04T05:17:29.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:17:29.342Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:17:29.342Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:17:29.342Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:17:29.342Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:17:29.342Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (39928.814 ms) ====== [2025-12-04T05:17:29.342Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-04T05:17:30.036Z] GC before operation: completed in 511.893 ms, heap usage 176.093 MB -> 87.831 MB. [2025-12-04T05:17:35.334Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:17:41.720Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:17:47.963Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:17:52.551Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:17:55.697Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:17:58.800Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:18:02.767Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:18:05.828Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:18:06.549Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:18:06.549Z] The best model improves the baseline by 14.34%. [2025-12-04T05:18:06.549Z] Top recommended movies for user id 72: [2025-12-04T05:18:06.549Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:18:06.549Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:18:06.549Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:18:06.549Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:18:06.549Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:18:06.549Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (36724.497 ms) ====== [2025-12-04T05:18:06.549Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-04T05:18:06.549Z] GC before operation: completed in 387.537 ms, heap usage 300.571 MB -> 88.164 MB. [2025-12-04T05:18:14.168Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:18:20.509Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:18:26.934Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:18:32.147Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:18:36.149Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:18:40.278Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:18:44.609Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:18:47.248Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:18:47.950Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:18:47.950Z] The best model improves the baseline by 14.34%. [2025-12-04T05:18:47.950Z] Top recommended movies for user id 72: [2025-12-04T05:18:47.950Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:18:47.950Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:18:47.950Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:18:47.950Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:18:47.950Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:18:47.950Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (41209.117 ms) ====== [2025-12-04T05:18:47.950Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-04T05:18:48.694Z] GC before operation: completed in 285.621 ms, heap usage 290.166 MB -> 87.916 MB. [2025-12-04T05:18:55.370Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:19:01.555Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:19:09.230Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:19:13.419Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:19:17.494Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:19:21.500Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:19:25.661Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:19:28.794Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:19:29.467Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:19:29.468Z] The best model improves the baseline by 14.34%. [2025-12-04T05:19:30.157Z] Top recommended movies for user id 72: [2025-12-04T05:19:30.158Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:19:30.158Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:19:30.158Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:19:30.158Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:19:30.158Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:19:30.158Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (41647.061 ms) ====== [2025-12-04T05:19:30.158Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-04T05:19:30.158Z] GC before operation: completed in 321.438 ms, heap usage 166.426 MB -> 87.966 MB. [2025-12-04T05:19:35.203Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:19:40.455Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:19:46.909Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:19:52.245Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:19:55.380Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:19:58.567Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:20:02.559Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:20:05.720Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:20:06.407Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:20:06.407Z] The best model improves the baseline by 14.34%. [2025-12-04T05:20:07.062Z] Top recommended movies for user id 72: [2025-12-04T05:20:07.062Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:20:07.062Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:20:07.062Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:20:07.062Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:20:07.062Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:20:07.062Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36640.981 ms) ====== [2025-12-04T05:20:07.062Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-04T05:20:07.062Z] GC before operation: completed in 377.505 ms, heap usage 143.894 MB -> 88.062 MB. [2025-12-04T05:20:15.140Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:20:20.252Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:20:26.530Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:20:32.931Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:20:36.034Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:20:39.140Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:20:41.849Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:20:45.165Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:20:45.165Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:20:45.165Z] The best model improves the baseline by 14.34%. [2025-12-04T05:20:45.858Z] Top recommended movies for user id 72: [2025-12-04T05:20:45.858Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:20:45.858Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:20:45.858Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:20:45.858Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:20:45.858Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:20:45.858Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38287.193 ms) ====== [2025-12-04T05:20:45.858Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-04T05:20:45.858Z] GC before operation: completed in 308.913 ms, heap usage 206.597 MB -> 87.934 MB. [2025-12-04T05:20:52.147Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:20:57.404Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:21:03.870Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:21:07.892Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:21:12.048Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:21:15.198Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:21:19.238Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:21:22.468Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:21:23.157Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:21:23.157Z] The best model improves the baseline by 14.34%. [2025-12-04T05:21:23.157Z] Top recommended movies for user id 72: [2025-12-04T05:21:23.157Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:21:23.157Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:21:23.157Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:21:23.157Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:21:23.157Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:21:23.157Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (37319.704 ms) ====== [2025-12-04T05:21:23.157Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-04T05:21:23.910Z] GC before operation: completed in 265.589 ms, heap usage 263.080 MB -> 88.273 MB. [2025-12-04T05:21:30.348Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:21:35.412Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:21:40.728Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:21:45.899Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:21:48.942Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:21:53.055Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:21:56.138Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:21:59.281Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:21:59.938Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:21:59.938Z] The best model improves the baseline by 14.34%. [2025-12-04T05:21:59.938Z] Top recommended movies for user id 72: [2025-12-04T05:21:59.938Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:21:59.938Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:21:59.938Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:21:59.938Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:21:59.938Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:21:59.938Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (36599.149 ms) ====== [2025-12-04T05:21:59.938Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-04T05:22:00.643Z] GC before operation: completed in 242.079 ms, heap usage 336.983 MB -> 88.218 MB. [2025-12-04T05:22:06.927Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:22:13.182Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:22:18.286Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:22:22.278Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:22:26.398Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:22:29.454Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:22:33.409Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:22:36.508Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:22:37.178Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:22:37.178Z] The best model improves the baseline by 14.34%. [2025-12-04T05:22:37.178Z] Top recommended movies for user id 72: [2025-12-04T05:22:37.178Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:22:37.178Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:22:37.178Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:22:37.178Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:22:37.178Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:22:37.178Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (36775.534 ms) ====== [2025-12-04T05:22:37.178Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-04T05:22:37.178Z] GC before operation: completed in 288.940 ms, heap usage 143.928 MB -> 88.040 MB. [2025-12-04T05:22:43.345Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:22:48.778Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:22:53.910Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:23:00.184Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:23:03.232Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:23:06.531Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:23:09.715Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:23:13.929Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:23:13.929Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:23:13.929Z] The best model improves the baseline by 14.34%. [2025-12-04T05:23:13.929Z] Top recommended movies for user id 72: [2025-12-04T05:23:13.929Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:23:13.929Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:23:13.929Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:23:13.929Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:23:13.929Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:23:13.929Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (36593.972 ms) ====== [2025-12-04T05:23:13.929Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-04T05:23:13.929Z] GC before operation: completed in 258.407 ms, heap usage 203.208 MB -> 87.919 MB. [2025-12-04T05:23:20.099Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:23:25.120Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:23:32.808Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:23:37.871Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:23:41.952Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:23:44.722Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:23:48.744Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:23:51.829Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:23:52.528Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:23:52.528Z] The best model improves the baseline by 14.34%. [2025-12-04T05:23:52.528Z] Top recommended movies for user id 72: [2025-12-04T05:23:52.528Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:23:52.528Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:23:52.528Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:23:52.528Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:23:52.528Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:23:52.528Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (38478.744 ms) ====== [2025-12-04T05:23:52.528Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-04T05:23:53.228Z] GC before operation: completed in 328.830 ms, heap usage 143.321 MB -> 87.997 MB. [2025-12-04T05:23:58.350Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T05:24:04.618Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T05:24:09.572Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T05:24:14.654Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T05:24:17.724Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T05:24:21.029Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T05:24:25.137Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T05:24:27.331Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T05:24:28.042Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-04T05:24:28.042Z] The best model improves the baseline by 14.34%. [2025-12-04T05:24:28.042Z] Top recommended movies for user id 72: [2025-12-04T05:24:28.042Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-04T05:24:28.042Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-04T05:24:28.042Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-04T05:24:28.042Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-04T05:24:28.042Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-04T05:24:28.042Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (35229.793 ms) ====== [2025-12-04T05:24:29.188Z] ----------------------------------- [2025-12-04T05:24:29.188Z] renaissance-movie-lens_0_PASSED [2025-12-04T05:24:29.188Z] ----------------------------------- [2025-12-04T05:24:29.188Z] [2025-12-04T05:24:29.188Z] TEST TEARDOWN: [2025-12-04T05:24:29.188Z] Nothing to be done for teardown. [2025-12-04T05:24:29.188Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 05:24:28 2025 Epoch Time (ms): 1764825868589