[2025-11-26T23:09:54.801Z] Running test renaissance-movie-lens_0 ... [2025-11-26T23:09:54.801Z] =============================================== [2025-11-26T23:09:54.801Z] renaissance-movie-lens_0 Start Time: Wed Nov 26 23:09:53 2025 Epoch Time (ms): 1764198593399 [2025-11-26T23:09:54.801Z] variation: NoOptions [2025-11-26T23:09:54.801Z] JVM_OPTIONS: [2025-11-26T23:09:54.801Z] { \ [2025-11-26T23:09:54.801Z] echo ""; echo "TEST SETUP:"; \ [2025-11-26T23:09:54.801Z] echo "Nothing to be done for setup."; \ [2025-11-26T23:09:54.801Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17641968171826/renaissance-movie-lens_0"; \ [2025-11-26T23:09:54.801Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17641968171826/renaissance-movie-lens_0"; \ [2025-11-26T23:09:54.801Z] echo ""; echo "TESTING:"; \ [2025-11-26T23:09:54.801Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17641968171826/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-26T23:09:54.801Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17641968171826/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-26T23:09:54.801Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-26T23:09:54.801Z] echo "Nothing to be done for teardown."; \ [2025-11-26T23:09:54.801Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17641968171826/TestTargetResult"; [2025-11-26T23:09:54.801Z] [2025-11-26T23:09:54.801Z] TEST SETUP: [2025-11-26T23:09:54.801Z] Nothing to be done for setup. [2025-11-26T23:09:54.801Z] [2025-11-26T23:09:54.801Z] TESTING: [2025-11-26T23:10:00.968Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-26T23:10:12.182Z] 23:10:10.333 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-11-26T23:10:14.022Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-26T23:10:14.383Z] Training: 60056, validation: 20285, test: 19854 [2025-11-26T23:10:14.383Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-26T23:10:14.383Z] GC before operation: completed in 135.380 ms, heap usage 278.798 MB -> 76.087 MB. [2025-11-26T23:10:23.767Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:10:28.859Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:10:34.009Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:10:37.188Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:10:39.650Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:10:42.079Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:10:47.106Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:10:47.106Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:10:47.106Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:10:47.583Z] The best model improves the baseline by 14.52%. [2025-11-26T23:10:47.583Z] Top recommended movies for user id 72: [2025-11-26T23:10:47.583Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:10:47.583Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:10:47.583Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:10:47.583Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:10:47.583Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:10:47.583Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33107.551 ms) ====== [2025-11-26T23:10:47.583Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-26T23:10:47.960Z] GC before operation: completed in 165.003 ms, heap usage 380.637 MB -> 86.944 MB. [2025-11-26T23:10:52.000Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:10:55.204Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:11:01.670Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:11:02.495Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:11:04.343Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:11:06.889Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:11:09.388Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:11:11.281Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:11:11.281Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:11:11.638Z] The best model improves the baseline by 14.52%. [2025-11-26T23:11:11.638Z] Top recommended movies for user id 72: [2025-11-26T23:11:11.638Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:11:11.638Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:11:11.638Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:11:11.638Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:11:11.638Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:11:11.638Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23861.724 ms) ====== [2025-11-26T23:11:11.638Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-26T23:11:11.997Z] GC before operation: completed in 137.237 ms, heap usage 375.487 MB -> 89.077 MB. [2025-11-26T23:11:15.145Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:11:19.175Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:11:22.362Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:11:25.533Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:11:27.949Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:11:29.756Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:11:31.722Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:11:34.148Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:11:34.148Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:11:34.148Z] The best model improves the baseline by 14.52%. [2025-11-26T23:11:34.506Z] Top recommended movies for user id 72: [2025-11-26T23:11:34.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:11:34.506Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:11:34.506Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:11:34.506Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:11:34.506Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:11:34.506Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22716.288 ms) ====== [2025-11-26T23:11:34.506Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-26T23:11:34.863Z] GC before operation: completed in 142.674 ms, heap usage 293.926 MB -> 89.661 MB. [2025-11-26T23:11:38.011Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:11:41.185Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:11:44.399Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:11:47.580Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:11:49.349Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:11:51.772Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:11:53.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:11:55.363Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:11:56.133Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:11:56.133Z] The best model improves the baseline by 14.52%. [2025-11-26T23:11:56.133Z] Top recommended movies for user id 72: [2025-11-26T23:11:56.133Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:11:56.133Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:11:56.133Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:11:56.133Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:11:56.133Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:11:56.133Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21485.740 ms) ====== [2025-11-26T23:11:56.133Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-26T23:11:56.503Z] GC before operation: completed in 150.693 ms, heap usage 109.026 MB -> 89.721 MB. [2025-11-26T23:11:59.772Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:12:02.253Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:12:06.369Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:12:08.785Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:12:11.256Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:12:13.066Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:12:14.946Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:12:16.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:12:16.752Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:12:16.752Z] The best model improves the baseline by 14.52%. [2025-11-26T23:12:17.106Z] Top recommended movies for user id 72: [2025-11-26T23:12:17.106Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:12:17.106Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:12:17.106Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:12:17.106Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:12:17.106Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:12:17.106Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20784.879 ms) ====== [2025-11-26T23:12:17.106Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-26T23:12:17.106Z] GC before operation: completed in 151.858 ms, heap usage 213.201 MB -> 89.752 MB. [2025-11-26T23:12:21.080Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:12:23.499Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:12:26.773Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:12:29.951Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:12:31.715Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:12:34.143Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:12:35.980Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:12:37.782Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:12:38.139Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:12:38.139Z] The best model improves the baseline by 14.52%. [2025-11-26T23:12:38.139Z] Top recommended movies for user id 72: [2025-11-26T23:12:38.139Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:12:38.139Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:12:38.139Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:12:38.139Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:12:38.139Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:12:38.139Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20944.494 ms) ====== [2025-11-26T23:12:38.139Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-26T23:12:38.498Z] GC before operation: completed in 146.035 ms, heap usage 104.868 MB -> 93.608 MB. [2025-11-26T23:12:41.635Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:12:44.049Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:12:47.212Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:12:49.616Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:12:51.399Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:12:53.372Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:12:55.159Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:12:56.978Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:12:56.978Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:12:57.348Z] The best model improves the baseline by 14.52%. [2025-11-26T23:12:57.349Z] Top recommended movies for user id 72: [2025-11-26T23:12:57.349Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:12:57.349Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:12:57.349Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:12:57.349Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:12:57.349Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:12:57.349Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19020.998 ms) ====== [2025-11-26T23:12:57.349Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-26T23:12:57.349Z] GC before operation: completed in 140.415 ms, heap usage 140.826 MB -> 93.095 MB. [2025-11-26T23:13:00.492Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:13:06.473Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:13:06.888Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:13:10.057Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:13:11.857Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:13:13.667Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:13:16.113Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:13:17.364Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:13:18.124Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:13:18.124Z] The best model improves the baseline by 14.52%. [2025-11-26T23:13:18.124Z] Top recommended movies for user id 72: [2025-11-26T23:13:18.124Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:13:18.124Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:13:18.124Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:13:18.124Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:13:18.124Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:13:18.124Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20652.738 ms) ====== [2025-11-26T23:13:18.124Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-26T23:13:18.479Z] GC before operation: completed in 151.879 ms, heap usage 118.713 MB -> 90.086 MB. [2025-11-26T23:13:21.758Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:13:24.173Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:13:27.344Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:13:30.482Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:13:32.282Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:13:34.078Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:13:35.877Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:13:37.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:13:38.089Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:13:38.089Z] The best model improves the baseline by 14.52%. [2025-11-26T23:13:38.456Z] Top recommended movies for user id 72: [2025-11-26T23:13:38.456Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:13:38.456Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:13:38.456Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:13:38.456Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:13:38.456Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:13:38.456Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20033.211 ms) ====== [2025-11-26T23:13:38.456Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-26T23:13:38.456Z] GC before operation: completed in 140.520 ms, heap usage 477.858 MB -> 90.491 MB. [2025-11-26T23:13:41.629Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:13:44.776Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:13:48.031Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:13:50.584Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:13:55.206Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:13:55.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:13:56.494Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:13:57.743Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:13:58.095Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:13:58.095Z] The best model improves the baseline by 14.52%. [2025-11-26T23:13:58.449Z] Top recommended movies for user id 72: [2025-11-26T23:13:58.449Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:13:58.449Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:13:58.449Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:13:58.449Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:13:58.449Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:13:58.449Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19929.031 ms) ====== [2025-11-26T23:13:58.449Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-26T23:13:58.449Z] GC before operation: completed in 155.180 ms, heap usage 753.317 MB -> 94.264 MB. [2025-11-26T23:14:01.598Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:14:06.601Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:14:06.973Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:14:10.086Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:14:11.343Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:14:13.142Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:14:14.958Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:14:16.980Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:14:16.980Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:14:16.980Z] The best model improves the baseline by 14.52%. [2025-11-26T23:14:17.344Z] Top recommended movies for user id 72: [2025-11-26T23:14:17.344Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:14:17.344Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:14:17.344Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:14:17.344Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:14:17.344Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:14:17.344Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18711.516 ms) ====== [2025-11-26T23:14:17.344Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-26T23:14:17.344Z] GC before operation: completed in 141.364 ms, heap usage 238.882 MB -> 90.043 MB. [2025-11-26T23:14:20.542Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:14:22.980Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:14:26.158Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:14:28.650Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:14:30.462Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:14:32.267Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:14:34.091Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:14:35.882Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:14:35.882Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:14:35.882Z] The best model improves the baseline by 14.52%. [2025-11-26T23:14:36.259Z] Top recommended movies for user id 72: [2025-11-26T23:14:36.259Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:14:36.259Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:14:36.259Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:14:36.259Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:14:36.259Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:14:36.259Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18650.342 ms) ====== [2025-11-26T23:14:36.259Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-26T23:14:36.259Z] GC before operation: completed in 142.402 ms, heap usage 215.532 MB -> 90.246 MB. [2025-11-26T23:14:39.484Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:14:42.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:14:45.225Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:14:48.428Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:14:49.701Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:14:52.101Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:14:55.255Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:14:55.628Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:14:55.985Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:14:55.985Z] The best model improves the baseline by 14.52%. [2025-11-26T23:14:56.344Z] Top recommended movies for user id 72: [2025-11-26T23:14:56.344Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:14:56.344Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:14:56.344Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:14:56.344Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:14:56.344Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:14:56.344Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20169.986 ms) ====== [2025-11-26T23:14:56.344Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-26T23:14:56.708Z] GC before operation: completed in 142.656 ms, heap usage 375.090 MB -> 90.645 MB. [2025-11-26T23:14:59.924Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:15:05.578Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:15:05.936Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:15:09.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:15:12.302Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:15:15.518Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:15:15.518Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:15:18.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:15:18.691Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:15:18.691Z] The best model improves the baseline by 14.52%. [2025-11-26T23:15:18.691Z] Top recommended movies for user id 72: [2025-11-26T23:15:18.691Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:15:18.691Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:15:18.691Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:15:18.691Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:15:18.691Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:15:18.691Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20431.977 ms) ====== [2025-11-26T23:15:18.691Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-26T23:15:18.691Z] GC before operation: completed in 152.857 ms, heap usage 433.004 MB -> 90.509 MB. [2025-11-26T23:15:20.640Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:15:25.267Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:15:26.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:15:29.165Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:15:32.688Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:15:32.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:15:34.546Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:15:36.318Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:15:36.679Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:15:36.679Z] The best model improves the baseline by 14.52%. [2025-11-26T23:15:37.045Z] Top recommended movies for user id 72: [2025-11-26T23:15:37.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:15:37.045Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:15:37.045Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:15:37.045Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:15:37.045Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:15:37.045Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19915.488 ms) ====== [2025-11-26T23:15:37.045Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-26T23:15:37.045Z] GC before operation: completed in 148.457 ms, heap usage 295.917 MB -> 90.650 MB. [2025-11-26T23:15:40.192Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:15:43.374Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:15:45.808Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:15:48.607Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:15:50.447Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:15:51.721Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:15:53.648Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:15:55.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:15:55.437Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:15:55.437Z] The best model improves the baseline by 14.52%. [2025-11-26T23:15:55.794Z] Top recommended movies for user id 72: [2025-11-26T23:15:55.794Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:15:55.794Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:15:55.795Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:15:55.795Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:15:55.795Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:15:55.795Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18607.124 ms) ====== [2025-11-26T23:15:55.795Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-26T23:15:55.795Z] GC before operation: completed in 146.018 ms, heap usage 198.110 MB -> 90.252 MB. [2025-11-26T23:15:59.015Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:16:02.148Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:16:04.602Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:16:07.744Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:16:09.571Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:16:11.406Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:16:13.204Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:16:15.024Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:16:15.411Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:16:15.411Z] The best model improves the baseline by 14.52%. [2025-11-26T23:16:15.411Z] Top recommended movies for user id 72: [2025-11-26T23:16:15.411Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:16:15.411Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:16:15.411Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:16:15.411Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:16:15.411Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:16:15.411Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19626.331 ms) ====== [2025-11-26T23:16:15.411Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-26T23:16:15.868Z] GC before operation: completed in 143.808 ms, heap usage 374.194 MB -> 90.712 MB. [2025-11-26T23:16:19.075Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:16:21.493Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:16:24.642Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:16:27.788Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:16:29.607Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:16:31.385Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:16:33.175Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:16:34.936Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:16:35.797Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:16:35.797Z] The best model improves the baseline by 14.52%. [2025-11-26T23:16:35.797Z] Top recommended movies for user id 72: [2025-11-26T23:16:35.797Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:16:35.797Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:16:35.797Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:16:35.797Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:16:35.797Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:16:35.797Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19998.009 ms) ====== [2025-11-26T23:16:35.797Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-26T23:16:35.797Z] GC before operation: completed in 140.687 ms, heap usage 165.121 MB -> 90.217 MB. [2025-11-26T23:16:38.932Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:16:42.156Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:16:44.609Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:16:47.738Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:16:49.515Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:16:51.328Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:16:53.776Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:16:55.567Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:16:55.567Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:16:55.567Z] The best model improves the baseline by 14.52%. [2025-11-26T23:16:55.921Z] Top recommended movies for user id 72: [2025-11-26T23:16:55.921Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:16:55.921Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:16:55.921Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:16:55.921Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:16:55.921Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:16:55.921Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20033.548 ms) ====== [2025-11-26T23:16:55.921Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-26T23:16:55.921Z] GC before operation: completed in 143.527 ms, heap usage 119.897 MB -> 93.232 MB. [2025-11-26T23:16:59.049Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:17:01.479Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:17:04.713Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:17:07.861Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:17:09.107Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:17:10.894Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:17:13.372Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:17:14.668Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:17:15.025Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:17:15.025Z] The best model improves the baseline by 14.52%. [2025-11-26T23:17:15.377Z] Top recommended movies for user id 72: [2025-11-26T23:17:15.377Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:17:15.377Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:17:15.377Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:17:15.377Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:17:15.377Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:17:15.377Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19397.602 ms) ====== [2025-11-26T23:17:16.204Z] ----------------------------------- [2025-11-26T23:17:16.204Z] renaissance-movie-lens_0_PASSED [2025-11-26T23:17:16.204Z] ----------------------------------- [2025-11-26T23:17:16.204Z] [2025-11-26T23:17:16.204Z] TEST TEARDOWN: [2025-11-26T23:17:16.204Z] Nothing to be done for teardown. [2025-11-26T23:17:16.204Z] renaissance-movie-lens_0 Finish Time: Wed Nov 26 23:17:15 2025 Epoch Time (ms): 1764199035838