[2025-12-11T01:11:10.976Z] Running test renaissance-movie-lens_0 ... [2025-12-11T01:11:10.976Z] =============================================== [2025-12-11T01:11:10.976Z] renaissance-movie-lens_0 Start Time: Thu Dec 11 01:11:10 2025 Epoch Time (ms): 1765415470903 [2025-12-11T01:11:11.313Z] variation: NoOptions [2025-12-11T01:11:11.313Z] JVM_OPTIONS: [2025-12-11T01:11:11.313Z] { \ [2025-12-11T01:11:11.313Z] echo ""; echo "TEST SETUP:"; \ [2025-12-11T01:11:11.313Z] echo "Nothing to be done for setup."; \ [2025-12-11T01:11:11.313Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17654126173741\\renaissance-movie-lens_0"; \ [2025-12-11T01:11:11.313Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17654126173741\\renaissance-movie-lens_0"; \ [2025-12-11T01:11:11.313Z] echo ""; echo "TESTING:"; \ [2025-12-11T01:11:11.313Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/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 "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17654126173741\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-12-11T01:11:11.313Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17654126173741\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-11T01:11:11.313Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-11T01:11:11.313Z] echo "Nothing to be done for teardown."; \ [2025-12-11T01:11:11.313Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17654126173741\\TestTargetResult"; [2025-12-11T01:11:11.313Z] [2025-12-11T01:11:11.313Z] TEST SETUP: [2025-12-11T01:11:11.313Z] Nothing to be done for setup. [2025-12-11T01:11:11.313Z] [2025-12-11T01:11:11.313Z] TESTING: [2025-12-11T01:11:30.441Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-11T01:11:41.191Z] 01:11:40.389 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. [2025-12-11T01:11:44.444Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-11T01:11:46.038Z] Training: 60056, validation: 20285, test: 19854 [2025-12-11T01:11:46.038Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-11T01:11:46.039Z] GC before operation: completed in 239.473 ms, heap usage 300.891 MB -> 75.055 MB. [2025-12-11T01:12:03.567Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:12:12.942Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:12:24.033Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:12:33.390Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:12:39.452Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:12:45.899Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:12:50.967Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:12:55.939Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:12:55.939Z] 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. [2025-12-11T01:12:55.939Z] The best model improves the baseline by 14.34%. [2025-12-11T01:12:56.325Z] Top recommended movies for user id 72: [2025-12-11T01:12:56.325Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:12:56.325Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:12:56.325Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:12:56.325Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:12:56.325Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:12:56.325Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (70138.427 ms) ====== [2025-12-11T01:12:56.325Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-11T01:12:56.671Z] GC before operation: completed in 258.888 ms, heap usage 132.536 MB -> 88.680 MB. [2025-12-11T01:13:05.877Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:13:13.470Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:13:22.775Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:13:31.866Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:13:36.697Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:13:41.559Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:13:46.479Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:13:51.596Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:13:51.937Z] 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. [2025-12-11T01:13:52.391Z] The best model improves the baseline by 14.34%. [2025-12-11T01:13:52.778Z] Top recommended movies for user id 72: [2025-12-11T01:13:52.778Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:13:52.778Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:13:52.778Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:13:52.778Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:13:52.778Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:13:52.778Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (56129.844 ms) ====== [2025-12-11T01:13:52.778Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-11T01:13:52.778Z] GC before operation: completed in 242.673 ms, heap usage 150.487 MB -> 86.786 MB. [2025-12-11T01:14:02.486Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:14:11.608Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:14:19.500Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:14:28.737Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:14:32.551Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:14:38.786Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:14:44.098Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:14:49.328Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:14:49.701Z] 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. [2025-12-11T01:14:50.253Z] The best model improves the baseline by 14.34%. [2025-12-11T01:14:50.253Z] Top recommended movies for user id 72: [2025-12-11T01:14:50.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:14:50.253Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:14:50.253Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:14:50.253Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:14:50.253Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:14:50.253Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (57319.733 ms) ====== [2025-12-11T01:14:50.253Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-11T01:14:50.715Z] GC before operation: completed in 254.406 ms, heap usage 193.009 MB -> 87.366 MB. [2025-12-11T01:15:00.067Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:15:07.427Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:15:16.497Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:15:24.575Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:15:29.558Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:15:34.733Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:15:39.776Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:15:46.021Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:15:46.021Z] 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. [2025-12-11T01:15:46.021Z] The best model improves the baseline by 14.34%. [2025-12-11T01:15:46.497Z] Top recommended movies for user id 72: [2025-12-11T01:15:46.498Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:15:46.498Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:15:46.498Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:15:46.498Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:15:46.498Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:15:46.498Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (55910.942 ms) ====== [2025-12-11T01:15:46.498Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-11T01:15:46.918Z] GC before operation: completed in 268.269 ms, heap usage 169.035 MB -> 87.634 MB. [2025-12-11T01:15:56.614Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:16:04.178Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:16:11.734Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:16:20.918Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:16:25.062Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:16:29.836Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:16:34.628Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:16:38.476Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:16:39.416Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T01:16:39.416Z] The best model improves the baseline by 14.34%. [2025-12-11T01:16:39.416Z] Top recommended movies for user id 72: [2025-12-11T01:16:39.417Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:16:39.417Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:16:39.417Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:16:39.417Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:16:39.417Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:16:39.417Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (52733.154 ms) ====== [2025-12-11T01:16:39.417Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-11T01:16:39.905Z] GC before operation: completed in 253.378 ms, heap usage 125.472 MB -> 87.783 MB. [2025-12-11T01:16:49.093Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:16:58.235Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:17:06.386Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:17:13.920Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:17:19.929Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:17:23.833Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:17:29.084Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:17:33.978Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:17:34.378Z] 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. [2025-12-11T01:17:34.378Z] The best model improves the baseline by 14.34%. [2025-12-11T01:17:34.849Z] Top recommended movies for user id 72: [2025-12-11T01:17:34.849Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:17:34.849Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:17:34.849Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:17:34.849Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:17:34.849Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:17:34.849Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (55182.834 ms) ====== [2025-12-11T01:17:34.849Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-11T01:17:35.313Z] GC before operation: completed in 242.717 ms, heap usage 174.116 MB -> 87.910 MB. [2025-12-11T01:17:43.207Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:17:51.105Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:18:00.816Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:18:10.430Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:18:15.396Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:18:19.287Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:18:25.432Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:18:30.241Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:18:30.241Z] 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. [2025-12-11T01:18:30.241Z] The best model improves the baseline by 14.34%. [2025-12-11T01:18:30.640Z] Top recommended movies for user id 72: [2025-12-11T01:18:30.640Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:18:30.640Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:18:30.640Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:18:30.640Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:18:30.640Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:18:30.640Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55385.686 ms) ====== [2025-12-11T01:18:30.640Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-11T01:18:30.640Z] GC before operation: completed in 222.073 ms, heap usage 247.795 MB -> 87.968 MB. [2025-12-11T01:18:39.681Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:18:47.922Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:18:57.545Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:19:05.889Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:19:10.364Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:19:15.728Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:19:21.049Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:19:25.968Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:19:25.968Z] 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. [2025-12-11T01:19:25.968Z] The best model improves the baseline by 14.34%. [2025-12-11T01:19:26.708Z] Top recommended movies for user id 72: [2025-12-11T01:19:26.709Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:19:26.709Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:19:26.709Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:19:26.709Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:19:26.709Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:19:26.709Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55854.423 ms) ====== [2025-12-11T01:19:26.709Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-11T01:19:27.227Z] GC before operation: completed in 231.415 ms, heap usage 182.539 MB -> 88.073 MB. [2025-12-11T01:19:35.208Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:19:43.382Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:19:52.641Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:20:00.316Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:20:04.630Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:20:10.706Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:20:16.358Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:20:20.907Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:20:22.241Z] 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. [2025-12-11T01:20:22.241Z] The best model improves the baseline by 14.34%. [2025-12-11T01:20:22.241Z] Top recommended movies for user id 72: [2025-12-11T01:20:22.241Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:20:22.241Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:20:22.242Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:20:22.242Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:20:22.242Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:20:22.242Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55433.146 ms) ====== [2025-12-11T01:20:22.242Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-11T01:20:23.109Z] GC before operation: completed in 237.461 ms, heap usage 206.279 MB -> 87.959 MB. [2025-12-11T01:20:30.975Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:20:39.086Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:20:46.911Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:20:55.271Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:21:00.466Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:21:04.807Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:21:10.248Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:21:15.286Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:21:15.286Z] 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. [2025-12-11T01:21:15.286Z] The best model improves the baseline by 14.34%. [2025-12-11T01:21:15.627Z] Top recommended movies for user id 72: [2025-12-11T01:21:15.627Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:21:15.627Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:21:15.627Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:21:15.627Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:21:15.627Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:21:15.627Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (53117.729 ms) ====== [2025-12-11T01:21:15.627Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-11T01:21:15.627Z] GC before operation: completed in 230.274 ms, heap usage 199.874 MB -> 88.164 MB. [2025-12-11T01:21:25.675Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:21:34.001Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:21:43.044Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:21:50.845Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:21:55.620Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:21:59.784Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:22:05.075Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:22:10.279Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:22:11.034Z] 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. [2025-12-11T01:22:11.034Z] The best model improves the baseline by 14.34%. [2025-12-11T01:22:11.350Z] Top recommended movies for user id 72: [2025-12-11T01:22:11.350Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:22:11.350Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:22:11.350Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:22:11.350Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:22:11.350Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:22:11.350Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (55487.332 ms) ====== [2025-12-11T01:22:11.351Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-11T01:22:11.351Z] GC before operation: completed in 232.078 ms, heap usage 183.626 MB -> 87.891 MB. [2025-12-11T01:22:19.053Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:22:26.404Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:22:34.065Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:22:43.146Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:22:47.205Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:22:51.241Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:22:56.188Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:23:00.159Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:23:00.942Z] 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. [2025-12-11T01:23:00.942Z] The best model improves the baseline by 14.34%. [2025-12-11T01:23:01.330Z] Top recommended movies for user id 72: [2025-12-11T01:23:01.330Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:23:01.330Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:23:01.330Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:23:01.330Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:23:01.330Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:23:01.330Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (49781.782 ms) ====== [2025-12-11T01:23:01.330Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-11T01:23:01.740Z] GC before operation: completed in 241.395 ms, heap usage 292.555 MB -> 88.253 MB. [2025-12-11T01:23:10.907Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:23:18.187Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:23:27.243Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:23:34.906Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:23:39.167Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:23:44.764Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:23:49.691Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:23:54.835Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:23:55.245Z] 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. [2025-12-11T01:23:55.245Z] The best model improves the baseline by 14.34%. [2025-12-11T01:23:55.617Z] Top recommended movies for user id 72: [2025-12-11T01:23:55.617Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:23:55.617Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:23:55.617Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:23:55.617Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:23:55.617Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:23:55.617Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (53990.200 ms) ====== [2025-12-11T01:23:55.617Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-11T01:23:55.617Z] GC before operation: completed in 247.519 ms, heap usage 175.710 MB -> 88.213 MB. [2025-12-11T01:24:05.265Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:24:12.665Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:24:19.883Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:24:28.964Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:24:32.188Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:24:36.122Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:24:40.986Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:24:44.750Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:24:45.633Z] 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. [2025-12-11T01:24:45.633Z] The best model improves the baseline by 14.34%. [2025-12-11T01:24:45.633Z] Top recommended movies for user id 72: [2025-12-11T01:24:45.633Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:24:45.633Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:24:45.633Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:24:45.633Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:24:45.633Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:24:45.633Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (49841.753 ms) ====== [2025-12-11T01:24:45.633Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-11T01:24:46.132Z] GC before operation: completed in 241.321 ms, heap usage 127.277 MB -> 87.934 MB. [2025-12-11T01:24:55.386Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:25:03.167Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:25:10.605Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:25:19.851Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:25:24.886Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:25:29.797Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:25:34.765Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:25:39.882Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:25:40.294Z] 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. [2025-12-11T01:25:40.294Z] The best model improves the baseline by 14.34%. [2025-12-11T01:25:40.649Z] Top recommended movies for user id 72: [2025-12-11T01:25:40.649Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:25:40.649Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:25:40.649Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:25:40.649Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:25:40.649Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:25:40.649Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54663.455 ms) ====== [2025-12-11T01:25:40.649Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-11T01:25:40.649Z] GC before operation: completed in 234.976 ms, heap usage 182.528 MB -> 88.229 MB. [2025-12-11T01:25:48.254Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:25:57.110Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:26:04.592Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:26:11.972Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:26:15.174Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:26:20.150Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:26:25.150Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:26:30.461Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:26:30.461Z] 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. [2025-12-11T01:26:30.461Z] The best model improves the baseline by 14.34%. [2025-12-11T01:26:30.461Z] Top recommended movies for user id 72: [2025-12-11T01:26:30.461Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:26:30.461Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:26:30.461Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:26:30.461Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:26:30.461Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:26:30.461Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (49688.648 ms) ====== [2025-12-11T01:26:30.461Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-11T01:26:30.889Z] GC before operation: completed in 239.487 ms, heap usage 183.237 MB -> 88.080 MB. [2025-12-11T01:26:40.009Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:26:46.234Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:26:55.262Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:27:03.102Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:27:08.044Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:27:13.133Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:27:18.037Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:27:25.146Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:27:25.552Z] 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. [2025-12-11T01:27:25.552Z] The best model improves the baseline by 14.34%. [2025-12-11T01:27:25.958Z] Top recommended movies for user id 72: [2025-12-11T01:27:25.958Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:27:25.958Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:27:25.958Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:27:25.958Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:27:25.958Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:27:25.958Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (55109.515 ms) ====== [2025-12-11T01:27:25.958Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-11T01:27:25.958Z] GC before operation: completed in 236.989 ms, heap usage 205.123 MB -> 88.195 MB. [2025-12-11T01:27:34.510Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:27:42.453Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:27:52.129Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:28:00.406Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:28:07.130Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:28:09.493Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:28:15.106Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:28:19.252Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:28:20.073Z] 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. [2025-12-11T01:28:20.073Z] The best model improves the baseline by 14.34%. [2025-12-11T01:28:20.073Z] Top recommended movies for user id 72: [2025-12-11T01:28:20.073Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:28:20.073Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:28:20.073Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:28:20.073Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:28:20.073Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:28:20.073Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54022.456 ms) ====== [2025-12-11T01:28:20.073Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-11T01:28:20.925Z] GC before operation: completed in 231.243 ms, heap usage 227.700 MB -> 88.129 MB. [2025-12-11T01:28:28.382Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:28:35.801Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:28:43.433Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:28:51.064Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:28:54.889Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:28:58.783Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:29:04.015Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:29:08.788Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:29:09.346Z] 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. [2025-12-11T01:29:09.346Z] The best model improves the baseline by 14.34%. [2025-12-11T01:29:09.346Z] Top recommended movies for user id 72: [2025-12-11T01:29:09.346Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:29:09.346Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:29:09.346Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:29:09.346Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:29:09.346Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:29:09.346Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (49043.695 ms) ====== [2025-12-11T01:29:09.346Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-11T01:29:09.732Z] GC before operation: completed in 236.915 ms, heap usage 288.200 MB -> 88.271 MB. [2025-12-11T01:29:19.324Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T01:29:26.583Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T01:29:35.880Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T01:29:43.691Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T01:29:47.730Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T01:29:52.948Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T01:29:57.915Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T01:30:02.864Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T01:30:03.577Z] 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. [2025-12-11T01:30:03.577Z] The best model improves the baseline by 14.34%. [2025-12-11T01:30:04.054Z] Top recommended movies for user id 72: [2025-12-11T01:30:04.054Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T01:30:04.055Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T01:30:04.055Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T01:30:04.055Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T01:30:04.055Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T01:30:04.055Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (54564.059 ms) ====== [2025-12-11T01:30:04.756Z] [2025-12-11T01:30:04.358+0000] org.renaissance.core (org.renaissance.core.DirUtils lambda$createScratchDirectory$1) [2025-12-11T01:30:04.756Z] WARNING: Error deleting scratch directory C:\jenkins\workspace\Test_openjdk11_hs_extended.perf_x86-64_windows\aqa-tests\TKG\output_17654126173741\renaissance-movie-lens_0\harness-011112-16227610432440948606: harness-011112-16227610432440948606\apache-spark\lib\activation-1.1.1.jar: The process cannot access the file because it is being used by another process. [2025-12-11T01:30:04.756Z] [2025-12-11T01:30:04.756Z] ----------------------------------- [2025-12-11T01:30:04.756Z] renaissance-movie-lens_0_PASSED [2025-12-11T01:30:04.756Z] ----------------------------------- [2025-12-11T01:30:05.087Z] [2025-12-11T01:30:05.087Z] TEST TEARDOWN: [2025-12-11T01:30:05.087Z] Nothing to be done for teardown. [2025-12-11T01:30:05.087Z] renaissance-movie-lens_0 Finish Time: Thu Dec 11 01:30:05 2025 Epoch Time (ms): 1765416605048