[2025-12-25T00:12:45.850Z] Running test renaissance-movie-lens_0 ... [2025-12-25T00:12:45.850Z] =============================================== [2025-12-25T00:12:45.850Z] renaissance-movie-lens_0 Start Time: Thu Dec 25 00:12:45 2025 Epoch Time (ms): 1766621565495 [2025-12-25T00:12:45.850Z] variation: NoOptions [2025-12-25T00:12:45.850Z] JVM_OPTIONS: [2025-12-25T00:12:45.850Z] { \ [2025-12-25T00:12:45.850Z] echo ""; echo "TEST SETUP:"; \ [2025-12-25T00:12:45.850Z] echo "Nothing to be done for setup."; \ [2025-12-25T00:12:45.850Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666196986535/renaissance-movie-lens_0"; \ [2025-12-25T00:12:45.850Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666196986535/renaissance-movie-lens_0"; \ [2025-12-25T00:12:45.850Z] echo ""; echo "TESTING:"; \ [2025-12-25T00:12:45.850Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666196986535/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-25T00:12:45.850Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666196986535/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-25T00:12:45.850Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-25T00:12:45.850Z] echo "Nothing to be done for teardown."; \ [2025-12-25T00:12:45.850Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666196986535/TestTargetResult"; [2025-12-25T00:12:45.850Z] [2025-12-25T00:12:45.850Z] TEST SETUP: [2025-12-25T00:12:45.850Z] Nothing to be done for setup. [2025-12-25T00:12:45.850Z] [2025-12-25T00:12:45.850Z] TESTING: [2025-12-25T00:12:56.094Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-25T00:13:09.697Z] 00:13:09.241 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-25T00:13:13.918Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-25T00:13:13.918Z] Training: 60056, validation: 20285, test: 19854 [2025-12-25T00:13:13.918Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-25T00:13:13.918Z] GC before operation: completed in 249.423 ms, heap usage 281.588 MB -> 75.816 MB. [2025-12-25T00:13:25.892Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:13:32.834Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:13:37.306Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:13:42.766Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:13:44.598Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:13:47.667Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:13:49.628Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:13:52.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:13:52.659Z] 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. [2025-12-25T00:13:52.659Z] The best model improves the baseline by 14.52%. [2025-12-25T00:13:52.659Z] Top recommended movies for user id 72: [2025-12-25T00:13:52.659Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:13:52.659Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:13:52.659Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:13:52.659Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:13:52.659Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:13:52.659Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (38565.924 ms) ====== [2025-12-25T00:13:52.659Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-25T00:13:52.659Z] GC before operation: completed in 162.516 ms, heap usage 350.232 MB -> 90.254 MB. [2025-12-25T00:13:58.287Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:14:01.602Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:14:04.632Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:14:08.964Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:14:10.931Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:14:12.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:14:16.103Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:14:18.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:14:18.078Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-25T00:14:18.078Z] The best model improves the baseline by 14.52%. [2025-12-25T00:14:18.078Z] Top recommended movies for user id 72: [2025-12-25T00:14:18.078Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:14:18.078Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:14:18.078Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:14:18.078Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:14:18.078Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:14:18.078Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25271.330 ms) ====== [2025-12-25T00:14:18.078Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-25T00:14:18.078Z] GC before operation: completed in 157.409 ms, heap usage 733.212 MB -> 92.583 MB. [2025-12-25T00:14:23.675Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:14:26.799Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:14:30.979Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:14:34.014Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:14:36.037Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:14:38.005Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:14:40.145Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:14:42.212Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:14:42.212Z] 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. [2025-12-25T00:14:42.212Z] The best model improves the baseline by 14.52%. [2025-12-25T00:14:43.167Z] Top recommended movies for user id 72: [2025-12-25T00:14:43.167Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:14:43.167Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:14:43.167Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:14:43.167Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:14:43.167Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:14:43.167Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24218.786 ms) ====== [2025-12-25T00:14:43.167Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-25T00:14:43.167Z] GC before operation: completed in 167.927 ms, heap usage 247.308 MB -> 94.952 MB. [2025-12-25T00:14:46.204Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:14:50.377Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:14:53.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:14:56.885Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:14:58.945Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:15:01.053Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:15:03.022Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:15:04.995Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:15:04.995Z] 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. [2025-12-25T00:15:04.995Z] The best model improves the baseline by 14.52%. [2025-12-25T00:15:04.995Z] Top recommended movies for user id 72: [2025-12-25T00:15:04.995Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:15:04.995Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:15:04.995Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:15:04.995Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:15:04.995Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:15:04.995Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22207.459 ms) ====== [2025-12-25T00:15:04.995Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-25T00:15:04.995Z] GC before operation: completed in 163.420 ms, heap usage 649.416 MB -> 93.205 MB. [2025-12-25T00:15:09.240Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:15:12.286Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:15:15.320Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:15:18.525Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:15:20.496Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:15:22.466Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:15:23.425Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:15:25.399Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:15:26.363Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-25T00:15:26.363Z] The best model improves the baseline by 14.52%. [2025-12-25T00:15:26.363Z] Top recommended movies for user id 72: [2025-12-25T00:15:26.364Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:15:26.364Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:15:26.364Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:15:26.364Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:15:26.364Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:15:26.364Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20860.130 ms) ====== [2025-12-25T00:15:26.364Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-25T00:15:26.364Z] GC before operation: completed in 161.853 ms, heap usage 370.127 MB -> 93.162 MB. [2025-12-25T00:15:29.404Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:15:32.443Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:15:35.481Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:15:38.514Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:15:40.480Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:15:41.442Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:15:43.409Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:15:45.393Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:15:45.393Z] 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. [2025-12-25T00:15:45.393Z] The best model improves the baseline by 14.52%. [2025-12-25T00:15:46.352Z] Top recommended movies for user id 72: [2025-12-25T00:15:46.352Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:15:46.352Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:15:46.352Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:15:46.352Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:15:46.352Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:15:46.353Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19711.753 ms) ====== [2025-12-25T00:15:46.353Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-25T00:15:46.353Z] GC before operation: completed in 169.808 ms, heap usage 151.814 MB -> 95.453 MB. [2025-12-25T00:15:49.452Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:15:52.489Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:15:55.546Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:15:57.517Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:15:59.485Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:16:01.454Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:16:02.416Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:16:04.825Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:16:04.825Z] 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. [2025-12-25T00:16:04.825Z] The best model improves the baseline by 14.52%. [2025-12-25T00:16:04.825Z] Top recommended movies for user id 72: [2025-12-25T00:16:04.825Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:16:04.825Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:16:04.825Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:16:04.825Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:16:04.825Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:16:04.825Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18508.215 ms) ====== [2025-12-25T00:16:04.825Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-25T00:16:04.825Z] GC before operation: completed in 158.513 ms, heap usage 300.206 MB -> 91.701 MB. [2025-12-25T00:16:07.857Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:16:10.892Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:16:13.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:16:16.959Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:16:17.916Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:16:19.880Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:16:21.843Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:16:22.802Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:16:23.761Z] 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. [2025-12-25T00:16:23.761Z] The best model improves the baseline by 14.52%. [2025-12-25T00:16:23.761Z] Top recommended movies for user id 72: [2025-12-25T00:16:23.761Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:16:23.761Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:16:23.761Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:16:23.761Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:16:23.761Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:16:23.761Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18812.175 ms) ====== [2025-12-25T00:16:23.761Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-25T00:16:23.761Z] GC before operation: completed in 147.944 ms, heap usage 319.152 MB -> 91.928 MB. [2025-12-25T00:16:27.962Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:16:29.929Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:16:32.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:16:35.993Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:16:37.956Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:16:38.909Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:16:40.871Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:16:41.831Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:16:42.783Z] 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. [2025-12-25T00:16:42.784Z] The best model improves the baseline by 14.52%. [2025-12-25T00:16:42.784Z] Top recommended movies for user id 72: [2025-12-25T00:16:42.784Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:16:42.784Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:16:42.784Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:16:42.784Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:16:42.784Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:16:42.784Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18889.364 ms) ====== [2025-12-25T00:16:42.784Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-25T00:16:42.784Z] GC before operation: completed in 153.210 ms, heap usage 259.428 MB -> 93.303 MB. [2025-12-25T00:16:45.989Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:16:47.955Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:16:50.985Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:16:54.018Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:16:54.973Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:16:56.935Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:16:57.892Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:16:59.856Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:16:59.856Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-25T00:16:59.856Z] The best model improves the baseline by 14.52%. [2025-12-25T00:16:59.856Z] Top recommended movies for user id 72: [2025-12-25T00:16:59.856Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:16:59.856Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:16:59.856Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:16:59.856Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:16:59.856Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:16:59.856Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17335.458 ms) ====== [2025-12-25T00:16:59.856Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-25T00:17:00.813Z] GC before operation: completed in 153.147 ms, heap usage 247.866 MB -> 90.121 MB. [2025-12-25T00:17:02.781Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:17:05.811Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:17:08.842Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:17:10.803Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:17:12.466Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:17:14.437Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:17:16.408Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:17:17.373Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:17:18.325Z] 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. [2025-12-25T00:17:18.325Z] The best model improves the baseline by 14.52%. [2025-12-25T00:17:18.325Z] Top recommended movies for user id 72: [2025-12-25T00:17:18.325Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:17:18.325Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:17:18.325Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:17:18.325Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:17:18.325Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:17:18.325Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17829.247 ms) ====== [2025-12-25T00:17:18.325Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-25T00:17:18.325Z] GC before operation: completed in 159.500 ms, heap usage 276.447 MB -> 95.656 MB. [2025-12-25T00:17:21.364Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:17:24.400Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:17:27.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:17:30.454Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:17:31.466Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:17:33.437Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:17:35.401Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:17:37.367Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:17:37.367Z] 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. [2025-12-25T00:17:37.367Z] The best model improves the baseline by 14.52%. [2025-12-25T00:17:37.367Z] Top recommended movies for user id 72: [2025-12-25T00:17:37.367Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:17:37.367Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:17:37.367Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:17:37.367Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:17:37.367Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:17:37.367Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18905.543 ms) ====== [2025-12-25T00:17:37.367Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-25T00:17:37.367Z] GC before operation: completed in 216.053 ms, heap usage 491.694 MB -> 93.791 MB. [2025-12-25T00:17:41.545Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:17:43.511Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:17:46.546Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:17:49.575Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:17:50.533Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:17:52.504Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:17:54.470Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:17:55.425Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:17:55.425Z] 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. [2025-12-25T00:17:56.385Z] The best model improves the baseline by 14.52%. [2025-12-25T00:17:56.385Z] Top recommended movies for user id 72: [2025-12-25T00:17:56.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:17:56.385Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:17:56.385Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:17:56.385Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:17:56.386Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:17:56.386Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18630.693 ms) ====== [2025-12-25T00:17:56.386Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-25T00:17:56.386Z] GC before operation: completed in 158.617 ms, heap usage 380.056 MB -> 94.038 MB. [2025-12-25T00:17:59.419Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:18:02.457Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:18:05.490Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:18:07.449Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:18:09.409Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:18:10.368Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:18:12.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:18:14.301Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:18:14.301Z] 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. [2025-12-25T00:18:14.301Z] The best model improves the baseline by 14.52%. [2025-12-25T00:18:14.301Z] Top recommended movies for user id 72: [2025-12-25T00:18:14.301Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:18:14.301Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:18:14.301Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:18:14.301Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:18:14.301Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:18:14.301Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18171.123 ms) ====== [2025-12-25T00:18:14.301Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-25T00:18:14.302Z] GC before operation: completed in 167.724 ms, heap usage 286.266 MB -> 95.606 MB. [2025-12-25T00:18:18.196Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:18:20.175Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:18:22.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:18:25.161Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:18:26.120Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:18:28.089Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:18:30.052Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:18:31.016Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:18:31.016Z] 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. [2025-12-25T00:18:31.016Z] The best model improves the baseline by 14.52%. [2025-12-25T00:18:31.975Z] Top recommended movies for user id 72: [2025-12-25T00:18:31.975Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:18:31.975Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:18:31.975Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:18:31.975Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:18:31.975Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:18:31.976Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16959.321 ms) ====== [2025-12-25T00:18:31.976Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-25T00:18:31.976Z] GC before operation: completed in 143.486 ms, heap usage 205.969 MB -> 95.791 MB. [2025-12-25T00:18:33.939Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:18:36.973Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:18:39.996Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:18:41.961Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:18:43.921Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:18:44.880Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:18:46.854Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:18:47.812Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:18:48.767Z] 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. [2025-12-25T00:18:48.767Z] The best model improves the baseline by 14.52%. [2025-12-25T00:18:48.767Z] Top recommended movies for user id 72: [2025-12-25T00:18:48.767Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:18:48.767Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:18:48.767Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:18:48.767Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:18:48.767Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:18:48.767Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16944.035 ms) ====== [2025-12-25T00:18:48.767Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-25T00:18:48.767Z] GC before operation: completed in 205.471 ms, heap usage 546.705 MB -> 96.198 MB. [2025-12-25T00:18:51.801Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:18:53.766Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:18:56.800Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:18:58.765Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:19:00.728Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:19:01.689Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:19:03.654Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:19:05.618Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:19:05.618Z] 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. [2025-12-25T00:19:05.618Z] The best model improves the baseline by 14.52%. [2025-12-25T00:19:05.618Z] Top recommended movies for user id 72: [2025-12-25T00:19:05.618Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:19:05.618Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:19:05.618Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:19:05.618Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:19:05.618Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:19:05.618Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16839.463 ms) ====== [2025-12-25T00:19:05.618Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-25T00:19:05.618Z] GC before operation: completed in 161.269 ms, heap usage 374.204 MB -> 92.725 MB. [2025-12-25T00:19:09.794Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:19:11.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:19:14.795Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:19:16.778Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:19:18.784Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:19:20.761Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:19:21.721Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:19:23.683Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:19:23.683Z] 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. [2025-12-25T00:19:23.683Z] The best model improves the baseline by 14.52%. [2025-12-25T00:19:23.683Z] Top recommended movies for user id 72: [2025-12-25T00:19:23.683Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:19:23.683Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:19:23.683Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:19:23.683Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:19:23.683Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:19:23.683Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17825.358 ms) ====== [2025-12-25T00:19:23.683Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-25T00:19:23.683Z] GC before operation: completed in 196.724 ms, heap usage 541.626 MB -> 99.362 MB. [2025-12-25T00:19:27.144Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:19:29.105Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:19:32.140Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:19:34.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:19:36.065Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:19:37.027Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:19:38.993Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:19:39.950Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:19:40.909Z] 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. [2025-12-25T00:19:40.909Z] The best model improves the baseline by 14.52%. [2025-12-25T00:19:40.909Z] Top recommended movies for user id 72: [2025-12-25T00:19:40.909Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:19:40.909Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:19:40.909Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:19:40.909Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:19:40.909Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:19:40.909Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16951.201 ms) ====== [2025-12-25T00:19:40.909Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-25T00:19:40.909Z] GC before operation: completed in 163.036 ms, heap usage 507.740 MB -> 95.129 MB. [2025-12-25T00:19:43.938Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:19:45.902Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:19:48.933Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:19:50.894Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:19:52.858Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:19:54.820Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:19:55.779Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:19:57.743Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:19:57.743Z] 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. [2025-12-25T00:19:57.743Z] The best model improves the baseline by 14.52%. [2025-12-25T00:19:57.743Z] Top recommended movies for user id 72: [2025-12-25T00:19:57.743Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:19:57.743Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:19:57.743Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:19:57.743Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:19:57.743Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:19:57.743Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16751.654 ms) ====== [2025-12-25T00:19:58.698Z] ----------------------------------- [2025-12-25T00:19:58.698Z] renaissance-movie-lens_0_PASSED [2025-12-25T00:19:58.698Z] ----------------------------------- [2025-12-25T00:19:58.698Z] [2025-12-25T00:19:58.698Z] TEST TEARDOWN: [2025-12-25T00:19:58.698Z] Nothing to be done for teardown. [2025-12-25T00:19:58.698Z] renaissance-movie-lens_0 Finish Time: Thu Dec 25 00:19:58 2025 Epoch Time (ms): 1766621998391