[2025-07-15T13:09:12.480Z] Running test renaissance-movie-lens_0 ... [2025-07-15T13:09:12.480Z] =============================================== [2025-07-15T13:09:12.480Z] renaissance-movie-lens_0 Start Time: Tue Jul 15 13:09:12 2025 Epoch Time (ms): 1752584952386 [2025-07-15T13:09:12.480Z] variation: NoOptions [2025-07-15T13:09:12.480Z] JVM_OPTIONS: [2025-07-15T13:09:12.480Z] { \ [2025-07-15T13:09:12.480Z] echo ""; echo "TEST SETUP:"; \ [2025-07-15T13:09:12.480Z] echo "Nothing to be done for setup."; \ [2025-07-15T13:09:12.480Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17525849518091/renaissance-movie-lens_0"; \ [2025-07-15T13:09:12.480Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17525849518091/renaissance-movie-lens_0"; \ [2025-07-15T13:09:12.480Z] echo ""; echo "TESTING:"; \ [2025-07-15T13:09:12.480Z] "/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_17525849518091/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-07-15T13:09:12.480Z] 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_17525849518091/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-07-15T13:09:12.480Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-07-15T13:09:12.480Z] echo "Nothing to be done for teardown."; \ [2025-07-15T13:09:12.480Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17525849518091/TestTargetResult"; [2025-07-15T13:09:12.480Z] [2025-07-15T13:09:12.480Z] TEST SETUP: [2025-07-15T13:09:12.480Z] Nothing to be done for setup. [2025-07-15T13:09:13.197Z] [2025-07-15T13:09:13.197Z] TESTING: [2025-07-15T13:09:21.191Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-07-15T13:09:31.448Z] 13:09:31.004 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. [2025-07-15T13:09:35.606Z] Got 100004 ratings from 671 users on 9066 movies. [2025-07-15T13:09:36.309Z] Training: 60056, validation: 20285, test: 19854 [2025-07-15T13:09:36.309Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-07-15T13:09:37.059Z] GC before operation: completed in 389.906 ms, heap usage 134.738 MB -> 74.449 MB. [2025-07-15T13:09:50.438Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:09:58.677Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:10:06.700Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:10:14.591Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:10:18.597Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:10:24.087Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:10:29.416Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:10:33.640Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:10:33.640Z] 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. [2025-07-15T13:10:34.367Z] The best model improves the baseline by 14.34%. [2025-07-15T13:10:34.367Z] Top recommended movies for user id 72: [2025-07-15T13:10:34.367Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:10:34.367Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:10:34.367Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:10:34.367Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:10:34.367Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:10:34.367Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (57451.775 ms) ====== [2025-07-15T13:10:34.367Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-07-15T13:10:34.367Z] GC before operation: completed in 387.506 ms, heap usage 118.608 MB -> 87.047 MB. [2025-07-15T13:10:41.047Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:10:47.688Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:10:55.818Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:11:01.128Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:11:05.227Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:11:07.580Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:11:11.889Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:11:16.381Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:11:17.084Z] 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. [2025-07-15T13:11:17.084Z] The best model improves the baseline by 14.34%. [2025-07-15T13:11:17.084Z] Top recommended movies for user id 72: [2025-07-15T13:11:17.084Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:11:17.084Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:11:17.084Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:11:17.084Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:11:17.084Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:11:17.084Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (42723.168 ms) ====== [2025-07-15T13:11:17.084Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-07-15T13:11:17.876Z] GC before operation: completed in 358.338 ms, heap usage 383.013 MB -> 87.013 MB. [2025-07-15T13:11:25.897Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:11:32.556Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:11:40.867Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:11:47.589Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:11:51.916Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:11:56.196Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:12:00.459Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:12:05.809Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:12:05.809Z] 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. [2025-07-15T13:12:05.809Z] The best model improves the baseline by 14.34%. [2025-07-15T13:12:06.551Z] Top recommended movies for user id 72: [2025-07-15T13:12:06.551Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:12:06.551Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:12:06.551Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:12:06.551Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:12:06.551Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:12:06.551Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (48828.448 ms) ====== [2025-07-15T13:12:06.551Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-07-15T13:12:07.296Z] GC before operation: completed in 723.054 ms, heap usage 204.085 MB -> 87.260 MB. [2025-07-15T13:12:15.139Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:12:23.190Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:12:31.352Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:12:38.179Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:12:41.608Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:12:45.968Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:12:50.387Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:12:53.708Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:12:54.429Z] 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. [2025-07-15T13:12:54.430Z] The best model improves the baseline by 14.34%. [2025-07-15T13:12:54.430Z] Top recommended movies for user id 72: [2025-07-15T13:12:54.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:12:54.430Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:12:54.430Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:12:54.430Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:12:54.430Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:12:54.430Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (47367.099 ms) ====== [2025-07-15T13:12:54.430Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-07-15T13:12:55.151Z] GC before operation: completed in 334.012 ms, heap usage 145.687 MB -> 87.503 MB. [2025-07-15T13:13:01.787Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:13:09.829Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:13:15.199Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:13:20.525Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:13:24.825Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:13:28.107Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:13:34.916Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:13:38.209Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:13:39.213Z] 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. [2025-07-15T13:13:39.213Z] The best model improves the baseline by 14.34%. [2025-07-15T13:13:39.213Z] Top recommended movies for user id 72: [2025-07-15T13:13:39.213Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:13:39.213Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:13:39.213Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:13:39.213Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:13:39.213Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:13:39.213Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (44416.672 ms) ====== [2025-07-15T13:13:39.213Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-07-15T13:13:39.960Z] GC before operation: completed in 254.927 ms, heap usage 294.070 MB -> 87.624 MB. [2025-07-15T13:13:46.654Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:13:53.429Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:13:59.996Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:14:08.033Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:14:11.306Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:14:15.808Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:14:20.050Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:14:24.299Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:14:24.299Z] 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. [2025-07-15T13:14:24.300Z] The best model improves the baseline by 14.34%. [2025-07-15T13:14:25.056Z] Top recommended movies for user id 72: [2025-07-15T13:14:25.056Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:14:25.056Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:14:25.056Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:14:25.056Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:14:25.056Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:14:25.056Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (45133.169 ms) ====== [2025-07-15T13:14:25.056Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-07-15T13:14:25.056Z] GC before operation: completed in 522.711 ms, heap usage 289.925 MB -> 87.923 MB. [2025-07-15T13:14:31.653Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:14:39.868Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:14:47.982Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:14:54.661Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:14:59.026Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:15:03.329Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:15:07.940Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:15:11.197Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:15:11.936Z] 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. [2025-07-15T13:15:11.936Z] The best model improves the baseline by 14.34%. [2025-07-15T13:15:12.628Z] Top recommended movies for user id 72: [2025-07-15T13:15:12.628Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:15:12.628Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:15:12.628Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:15:12.628Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:15:12.628Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:15:12.628Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (47011.868 ms) ====== [2025-07-15T13:15:12.628Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-07-15T13:15:12.628Z] GC before operation: completed in 485.852 ms, heap usage 239.202 MB -> 87.849 MB. [2025-07-15T13:15:22.280Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:15:28.849Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:15:35.345Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:15:42.044Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:15:46.219Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:15:50.516Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:15:55.614Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:16:00.087Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:16:00.818Z] 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. [2025-07-15T13:16:00.818Z] The best model improves the baseline by 14.34%. [2025-07-15T13:16:01.623Z] Top recommended movies for user id 72: [2025-07-15T13:16:01.623Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:16:01.623Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:16:01.623Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:16:01.623Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:16:01.623Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:16:01.623Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (48754.192 ms) ====== [2025-07-15T13:16:01.623Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-07-15T13:16:02.407Z] GC before operation: completed in 574.220 ms, heap usage 136.956 MB -> 87.856 MB. [2025-07-15T13:16:12.155Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:16:23.922Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:16:34.113Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:16:41.103Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:16:45.517Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:16:49.882Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:16:54.419Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:16:58.670Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:16:58.670Z] 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. [2025-07-15T13:16:58.670Z] The best model improves the baseline by 14.34%. [2025-07-15T13:16:59.373Z] Top recommended movies for user id 72: [2025-07-15T13:16:59.373Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:16:59.373Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:16:59.373Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:16:59.373Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:16:59.373Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:16:59.373Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (56994.177 ms) ====== [2025-07-15T13:16:59.373Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-07-15T13:16:59.373Z] GC before operation: completed in 300.476 ms, heap usage 146.333 MB -> 87.818 MB. [2025-07-15T13:17:04.659Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:17:12.914Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:17:19.633Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:17:29.311Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:17:33.708Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:17:38.072Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:17:41.088Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:17:44.311Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:17:45.037Z] 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. [2025-07-15T13:17:45.037Z] The best model improves the baseline by 14.34%. [2025-07-15T13:17:45.762Z] Top recommended movies for user id 72: [2025-07-15T13:17:45.762Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:17:45.762Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:17:45.762Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:17:45.762Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:17:45.762Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:17:45.762Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (46121.675 ms) ====== [2025-07-15T13:17:45.762Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-07-15T13:17:46.542Z] GC before operation: completed in 524.390 ms, heap usage 169.649 MB -> 88.003 MB. [2025-07-15T13:17:54.620Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:18:02.628Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:18:12.408Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:18:17.818Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:18:22.140Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:18:25.405Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:18:29.708Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:18:32.940Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:18:32.940Z] 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. [2025-07-15T13:18:32.940Z] The best model improves the baseline by 14.34%. [2025-07-15T13:18:32.941Z] Top recommended movies for user id 72: [2025-07-15T13:18:32.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:18:32.941Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:18:32.941Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:18:32.941Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:18:32.941Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:18:32.941Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (47134.949 ms) ====== [2025-07-15T13:18:32.941Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-07-15T13:18:33.641Z] GC before operation: completed in 311.590 ms, heap usage 111.874 MB -> 87.677 MB. [2025-07-15T13:18:38.250Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:18:43.521Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:18:47.651Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:18:51.773Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:18:54.072Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:18:57.235Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:18:59.518Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:19:01.795Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:19:01.795Z] 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. [2025-07-15T13:19:01.795Z] The best model improves the baseline by 14.34%. [2025-07-15T13:19:01.795Z] Top recommended movies for user id 72: [2025-07-15T13:19:01.795Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:19:01.795Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:19:01.795Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:19:01.795Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:19:01.795Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:19:01.795Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (28452.418 ms) ====== [2025-07-15T13:19:01.795Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-07-15T13:19:02.499Z] GC before operation: completed in 292.572 ms, heap usage 238.162 MB -> 88.106 MB. [2025-07-15T13:19:06.645Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:19:10.860Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:19:16.257Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:19:22.088Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:19:26.340Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:19:29.535Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:19:33.770Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:19:36.945Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:19:37.697Z] 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. [2025-07-15T13:19:37.697Z] The best model improves the baseline by 14.34%. [2025-07-15T13:19:37.697Z] Top recommended movies for user id 72: [2025-07-15T13:19:37.697Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:19:37.697Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:19:37.697Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:19:37.697Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:19:37.697Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:19:37.697Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (35698.561 ms) ====== [2025-07-15T13:19:37.697Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-07-15T13:19:38.457Z] GC before operation: completed in 289.225 ms, heap usage 184.709 MB -> 88.075 MB. [2025-07-15T13:19:43.840Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:19:49.136Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:19:54.504Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:19:58.635Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:20:01.869Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:20:04.185Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:20:06.955Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:20:10.157Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:20:10.157Z] 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. [2025-07-15T13:20:10.157Z] The best model improves the baseline by 14.34%. [2025-07-15T13:20:10.890Z] Top recommended movies for user id 72: [2025-07-15T13:20:10.890Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:20:10.890Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:20:10.890Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:20:10.890Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:20:10.890Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:20:10.890Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (32349.335 ms) ====== [2025-07-15T13:20:10.890Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-07-15T13:20:10.890Z] GC before operation: completed in 304.044 ms, heap usage 210.202 MB -> 87.932 MB. [2025-07-15T13:20:16.168Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:20:21.478Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:20:26.733Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:20:30.913Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:20:34.121Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:20:36.437Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:20:39.731Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:20:42.036Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:20:42.738Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-07-15T13:20:42.738Z] The best model improves the baseline by 14.34%. [2025-07-15T13:20:43.436Z] Top recommended movies for user id 72: [2025-07-15T13:20:43.436Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:20:43.436Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:20:43.436Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:20:43.436Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:20:43.436Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:20:43.436Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (32166.144 ms) ====== [2025-07-15T13:20:43.436Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-07-15T13:20:43.436Z] GC before operation: completed in 236.874 ms, heap usage 219.342 MB -> 88.197 MB. [2025-07-15T13:20:47.635Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:20:50.901Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:20:55.015Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:20:59.101Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:21:00.588Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:21:03.748Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:21:06.045Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:21:08.320Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:21:08.320Z] 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. [2025-07-15T13:21:09.045Z] The best model improves the baseline by 14.34%. [2025-07-15T13:21:09.045Z] Top recommended movies for user id 72: [2025-07-15T13:21:09.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:21:09.045Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:21:09.045Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:21:09.045Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:21:09.045Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:21:09.045Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (25581.800 ms) ====== [2025-07-15T13:21:09.045Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-07-15T13:21:09.045Z] GC before operation: completed in 265.638 ms, heap usage 194.380 MB -> 87.993 MB. [2025-07-15T13:21:13.207Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:21:17.315Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:21:22.479Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:21:25.617Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:21:27.965Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:21:30.240Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:21:32.466Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:21:34.728Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:21:34.728Z] 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. [2025-07-15T13:21:34.728Z] The best model improves the baseline by 14.34%. [2025-07-15T13:21:34.728Z] Top recommended movies for user id 72: [2025-07-15T13:21:34.728Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:21:34.728Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:21:34.728Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:21:34.728Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:21:34.728Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:21:34.728Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (25744.407 ms) ====== [2025-07-15T13:21:34.728Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-07-15T13:21:35.414Z] GC before operation: completed in 238.435 ms, heap usage 293.285 MB -> 88.215 MB. [2025-07-15T13:21:39.000Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:21:43.043Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:21:47.096Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:21:50.201Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:21:52.464Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:21:54.710Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:21:56.945Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:21:58.385Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:21:59.078Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-07-15T13:21:59.078Z] The best model improves the baseline by 14.34%. [2025-07-15T13:21:59.078Z] Top recommended movies for user id 72: [2025-07-15T13:21:59.078Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:21:59.078Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:21:59.078Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:21:59.078Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:21:59.078Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:21:59.078Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (23992.567 ms) ====== [2025-07-15T13:21:59.078Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-07-15T13:21:59.078Z] GC before operation: completed in 224.226 ms, heap usage 146.962 MB -> 87.914 MB. [2025-07-15T13:22:03.157Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:22:06.681Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:22:10.762Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:22:13.889Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:22:16.970Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:22:18.628Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:22:20.834Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:22:23.058Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:22:23.058Z] 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. [2025-07-15T13:22:23.058Z] The best model improves the baseline by 14.34%. [2025-07-15T13:22:23.778Z] Top recommended movies for user id 72: [2025-07-15T13:22:23.778Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:22:23.778Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:22:23.778Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:22:23.778Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:22:23.778Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:22:23.778Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (24122.074 ms) ====== [2025-07-15T13:22:23.778Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-07-15T13:22:23.778Z] GC before operation: completed in 235.656 ms, heap usage 169.649 MB -> 87.987 MB. [2025-07-15T13:22:26.847Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-15T13:22:30.930Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-15T13:22:34.960Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-15T13:22:38.980Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-15T13:22:41.193Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-15T13:22:42.604Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-15T13:22:44.806Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-15T13:22:47.088Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-15T13:22:47.088Z] 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. [2025-07-15T13:22:47.088Z] The best model improves the baseline by 14.34%. [2025-07-15T13:22:47.088Z] Top recommended movies for user id 72: [2025-07-15T13:22:47.088Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-07-15T13:22:47.088Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-07-15T13:22:47.088Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-07-15T13:22:47.088Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-07-15T13:22:47.088Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-07-15T13:22:47.088Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (23488.887 ms) ====== [2025-07-15T13:22:47.765Z] ----------------------------------- [2025-07-15T13:22:47.765Z] renaissance-movie-lens_0_PASSED [2025-07-15T13:22:47.765Z] ----------------------------------- [2025-07-15T13:22:47.765Z] [2025-07-15T13:22:47.765Z] TEST TEARDOWN: [2025-07-15T13:22:47.765Z] Nothing to be done for teardown. [2025-07-15T13:22:47.765Z] renaissance-movie-lens_0 Finish Time: Tue Jul 15 13:22:47 2025 Epoch Time (ms): 1752585767213