[2025-11-19T22:54:30.733Z] Running test renaissance-movie-lens_0 ... [2025-11-19T22:54:30.733Z] =============================================== [2025-11-19T22:54:30.733Z] renaissance-movie-lens_0 Start Time: Wed Nov 19 22:54:30 2025 Epoch Time (ms): 1763592870272 [2025-11-19T22:54:30.733Z] variation: NoOptions [2025-11-19T22:54:30.733Z] JVM_OPTIONS: [2025-11-19T22:54:30.733Z] { \ [2025-11-19T22:54:30.733Z] echo ""; echo "TEST SETUP:"; \ [2025-11-19T22:54:30.733Z] echo "Nothing to be done for setup."; \ [2025-11-19T22:54:30.733Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17635915335639/renaissance-movie-lens_0"; \ [2025-11-19T22:54:30.733Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17635915335639/renaissance-movie-lens_0"; \ [2025-11-19T22:54:30.733Z] echo ""; echo "TESTING:"; \ [2025-11-19T22:54:30.733Z] "/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_17635915335639/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-19T22:54:30.733Z] 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_17635915335639/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-19T22:54:30.733Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-19T22:54:30.733Z] echo "Nothing to be done for teardown."; \ [2025-11-19T22:54:30.733Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17635915335639/TestTargetResult"; [2025-11-19T22:54:30.733Z] [2025-11-19T22:54:30.733Z] TEST SETUP: [2025-11-19T22:54:30.733Z] Nothing to be done for setup. [2025-11-19T22:54:30.733Z] [2025-11-19T22:54:30.733Z] TESTING: [2025-11-19T22:54:38.848Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-19T22:54:52.335Z] 22:54:50.846 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. [2025-11-19T22:54:55.352Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-19T22:54:56.303Z] Training: 60056, validation: 20285, test: 19854 [2025-11-19T22:54:56.303Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-19T22:54:56.303Z] GC before operation: completed in 207.485 ms, heap usage 273.301 MB -> 76.136 MB. [2025-11-19T22:55:07.823Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:55:15.973Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:55:22.060Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:55:27.440Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:55:30.447Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:55:33.454Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:55:36.469Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:55:39.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:55:39.517Z] 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. [2025-11-19T22:55:39.517Z] The best model improves the baseline by 14.52%. [2025-11-19T22:55:40.481Z] Top recommended movies for user id 72: [2025-11-19T22:55:40.481Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:55:40.481Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:55:40.481Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:55:40.481Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:55:40.481Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:55:40.481Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (43892.050 ms) ====== [2025-11-19T22:55:40.481Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-19T22:55:40.481Z] GC before operation: completed in 301.538 ms, heap usage 120.947 MB -> 94.689 MB. [2025-11-19T22:55:45.858Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:55:51.265Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:55:55.410Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:55:59.551Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:56:02.585Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:56:05.685Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:56:08.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:56:11.729Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:56:12.684Z] 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. [2025-11-19T22:56:12.684Z] The best model improves the baseline by 14.52%. [2025-11-19T22:56:12.684Z] Top recommended movies for user id 72: [2025-11-19T22:56:12.684Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:56:12.684Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:56:12.684Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:56:12.684Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:56:12.684Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:56:12.684Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (32084.648 ms) ====== [2025-11-19T22:56:12.684Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-19T22:56:12.684Z] GC before operation: completed in 206.219 ms, heap usage 170.992 MB -> 88.830 MB. [2025-11-19T22:56:18.043Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:56:23.000Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:56:27.213Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:56:31.360Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:56:34.380Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:56:37.400Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:56:39.359Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:56:42.373Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:56:42.373Z] 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. [2025-11-19T22:56:42.373Z] The best model improves the baseline by 14.52%. [2025-11-19T22:56:43.329Z] Top recommended movies for user id 72: [2025-11-19T22:56:43.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:56:43.329Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:56:43.329Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:56:43.329Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:56:43.329Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:56:43.329Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (30074.246 ms) ====== [2025-11-19T22:56:43.329Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-19T22:56:43.329Z] GC before operation: completed in 255.097 ms, heap usage 391.954 MB -> 89.826 MB. [2025-11-19T22:56:48.688Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:56:51.697Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:56:55.834Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:56:59.964Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:57:02.981Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:57:04.935Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:57:07.943Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:57:09.892Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:57:09.892Z] 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. [2025-11-19T22:57:09.892Z] The best model improves the baseline by 14.52%. [2025-11-19T22:57:10.841Z] Top recommended movies for user id 72: [2025-11-19T22:57:10.841Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:57:10.841Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:57:10.841Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:57:10.841Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:57:10.841Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:57:10.841Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (27194.971 ms) ====== [2025-11-19T22:57:10.841Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-19T22:57:10.841Z] GC before operation: completed in 238.599 ms, heap usage 119.220 MB -> 92.824 MB. [2025-11-19T22:57:14.979Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:57:19.321Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:57:22.465Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:57:24.404Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:57:26.349Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:57:27.291Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:57:29.243Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:57:30.893Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:57:31.875Z] 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. [2025-11-19T22:57:31.875Z] The best model improves the baseline by 14.52%. [2025-11-19T22:57:31.875Z] Top recommended movies for user id 72: [2025-11-19T22:57:31.875Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:57:31.875Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:57:31.875Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:57:31.875Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:57:31.875Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:57:31.875Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20366.891 ms) ====== [2025-11-19T22:57:31.875Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-19T22:57:31.875Z] GC before operation: completed in 121.766 ms, heap usage 244.298 MB -> 89.811 MB. [2025-11-19T22:57:33.824Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:57:36.821Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:57:39.819Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:57:42.814Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:57:44.751Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:57:46.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:57:48.623Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:57:50.558Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:57:50.558Z] 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. [2025-11-19T22:57:50.558Z] The best model improves the baseline by 14.52%. [2025-11-19T22:57:50.558Z] Top recommended movies for user id 72: [2025-11-19T22:57:50.558Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:57:50.558Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:57:50.558Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:57:50.558Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:57:50.558Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:57:50.558Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19602.333 ms) ====== [2025-11-19T22:57:50.558Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-19T22:57:50.558Z] GC before operation: completed in 145.700 ms, heap usage 422.227 MB -> 90.410 MB. [2025-11-19T22:57:53.551Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:57:56.543Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:57:59.535Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:58:02.527Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:58:04.507Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:58:06.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:58:08.422Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:58:11.449Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:58:11.449Z] 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. [2025-11-19T22:58:11.449Z] The best model improves the baseline by 14.52%. [2025-11-19T22:58:12.414Z] Top recommended movies for user id 72: [2025-11-19T22:58:12.414Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:58:12.414Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:58:12.414Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:58:12.414Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:58:12.414Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:58:12.414Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20983.305 ms) ====== [2025-11-19T22:58:12.414Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-19T22:58:12.414Z] GC before operation: completed in 214.280 ms, heap usage 95.230 MB -> 90.364 MB. [2025-11-19T22:58:15.401Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:58:18.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:58:22.754Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:58:25.753Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:58:27.696Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:58:29.630Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:58:31.580Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:58:33.555Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:58:34.499Z] 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. [2025-11-19T22:58:34.499Z] The best model improves the baseline by 14.52%. [2025-11-19T22:58:34.499Z] Top recommended movies for user id 72: [2025-11-19T22:58:34.499Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:58:34.499Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:58:34.499Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:58:34.499Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:58:34.499Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:58:34.499Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22626.429 ms) ====== [2025-11-19T22:58:34.499Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-19T22:58:35.464Z] GC before operation: completed in 208.465 ms, heap usage 166.018 MB -> 90.197 MB. [2025-11-19T22:58:38.155Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:58:41.162Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:58:45.338Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:58:48.415Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:58:50.386Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:58:53.417Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:58:55.356Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:58:57.303Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:58:58.366Z] 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. [2025-11-19T22:58:58.366Z] The best model improves the baseline by 14.52%. [2025-11-19T22:58:58.366Z] Top recommended movies for user id 72: [2025-11-19T22:58:58.366Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:58:58.366Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:58:58.366Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:58:58.366Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:58:58.366Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:58:58.366Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (23095.308 ms) ====== [2025-11-19T22:58:58.366Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-19T22:58:58.366Z] GC before operation: completed in 168.156 ms, heap usage 157.258 MB -> 90.083 MB. [2025-11-19T22:59:01.382Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:59:04.394Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:59:08.566Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:59:11.618Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:59:14.712Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:59:17.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:59:19.728Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:59:21.730Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:59:21.730Z] 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. [2025-11-19T22:59:21.730Z] The best model improves the baseline by 14.52%. [2025-11-19T22:59:21.730Z] Top recommended movies for user id 72: [2025-11-19T22:59:21.730Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:59:21.730Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:59:21.730Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:59:21.730Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:59:21.730Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:59:21.730Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (23526.981 ms) ====== [2025-11-19T22:59:21.730Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-19T22:59:21.730Z] GC before operation: completed in 171.492 ms, heap usage 163.293 MB -> 90.325 MB. [2025-11-19T22:59:25.999Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:59:30.208Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:59:34.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:59:38.633Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:59:40.620Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:59:43.643Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:59:46.326Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:59:49.396Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:59:49.396Z] 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. [2025-11-19T22:59:49.396Z] The best model improves the baseline by 14.52%. [2025-11-19T22:59:49.396Z] Top recommended movies for user id 72: [2025-11-19T22:59:49.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T22:59:49.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T22:59:49.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T22:59:49.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T22:59:49.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T22:59:49.396Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27585.931 ms) ====== [2025-11-19T22:59:49.396Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-19T22:59:49.396Z] GC before operation: completed in 267.938 ms, heap usage 496.426 MB -> 90.512 MB. [2025-11-19T22:59:54.851Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:59:59.088Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:00:02.330Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:00:07.829Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:00:08.830Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:00:11.108Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:00:13.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:00:15.778Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:00:15.778Z] 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. [2025-11-19T23:00:15.778Z] The best model improves the baseline by 14.52%. [2025-11-19T23:00:15.778Z] Top recommended movies for user id 72: [2025-11-19T23:00:15.778Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:00:15.778Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:00:15.778Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:00:15.778Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:00:15.778Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:00:15.778Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (25860.249 ms) ====== [2025-11-19T23:00:15.778Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-19T23:00:15.778Z] GC before operation: completed in 218.182 ms, heap usage 596.127 MB -> 94.094 MB. [2025-11-19T23:00:20.911Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:00:24.719Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:00:27.743Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:00:30.261Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:00:33.399Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:00:35.879Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:00:38.135Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:00:41.275Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:00:41.275Z] 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. [2025-11-19T23:00:41.275Z] The best model improves the baseline by 14.52%. [2025-11-19T23:00:41.275Z] Top recommended movies for user id 72: [2025-11-19T23:00:41.275Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:00:41.275Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:00:41.275Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:00:41.275Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:00:41.275Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:00:41.275Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (25643.153 ms) ====== [2025-11-19T23:00:41.275Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-19T23:00:42.319Z] GC before operation: completed in 231.442 ms, heap usage 615.290 MB -> 94.214 MB. [2025-11-19T23:00:46.088Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:00:50.731Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:00:54.162Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:00:58.497Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:01:00.561Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:01:03.937Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:01:06.333Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:01:07.457Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:01:08.559Z] 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. [2025-11-19T23:01:08.559Z] The best model improves the baseline by 14.52%. [2025-11-19T23:01:08.559Z] Top recommended movies for user id 72: [2025-11-19T23:01:08.559Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:01:08.559Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:01:08.559Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:01:08.559Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:01:08.559Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:01:08.559Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (26704.991 ms) ====== [2025-11-19T23:01:08.559Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-19T23:01:08.559Z] GC before operation: completed in 216.384 ms, heap usage 200.515 MB -> 90.289 MB. [2025-11-19T23:01:11.648Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:01:15.871Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:01:20.280Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:01:24.550Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:01:27.604Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:01:31.099Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:01:33.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:01:36.417Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:01:36.417Z] 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. [2025-11-19T23:01:36.417Z] The best model improves the baseline by 14.52%. [2025-11-19T23:01:37.396Z] Top recommended movies for user id 72: [2025-11-19T23:01:37.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:01:37.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:01:37.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:01:37.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:01:37.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:01:37.396Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (28609.137 ms) ====== [2025-11-19T23:01:37.396Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-19T23:01:37.396Z] GC before operation: completed in 194.905 ms, heap usage 264.279 MB -> 90.566 MB. [2025-11-19T23:01:41.676Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:01:46.000Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:01:49.122Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:01:53.581Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:01:55.585Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:01:57.548Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:02:01.792Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:02:03.817Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:02:04.767Z] 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. [2025-11-19T23:02:04.767Z] The best model improves the baseline by 14.52%. [2025-11-19T23:02:04.767Z] Top recommended movies for user id 72: [2025-11-19T23:02:04.767Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:02:04.767Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:02:04.767Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:02:04.767Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:02:04.767Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:02:04.767Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (27172.562 ms) ====== [2025-11-19T23:02:04.767Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-19T23:02:04.767Z] GC before operation: completed in 227.051 ms, heap usage 424.658 MB -> 90.674 MB. [2025-11-19T23:02:10.408Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:02:14.583Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:02:18.531Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:02:23.986Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:02:27.102Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:02:30.268Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:02:32.566Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:02:35.696Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:02:36.773Z] 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. [2025-11-19T23:02:36.773Z] The best model improves the baseline by 14.52%. [2025-11-19T23:02:36.773Z] Top recommended movies for user id 72: [2025-11-19T23:02:36.773Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:02:36.773Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:02:36.773Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:02:36.773Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:02:36.773Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:02:36.773Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (31888.880 ms) ====== [2025-11-19T23:02:36.773Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-19T23:02:36.773Z] GC before operation: completed in 244.080 ms, heap usage 520.133 MB -> 90.866 MB. [2025-11-19T23:02:42.316Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:02:46.558Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:02:52.056Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:02:57.485Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:02:59.669Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:03:02.822Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:03:07.022Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:03:10.100Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:03:11.077Z] 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. [2025-11-19T23:03:11.077Z] The best model improves the baseline by 14.52%. [2025-11-19T23:03:12.062Z] Top recommended movies for user id 72: [2025-11-19T23:03:12.062Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:03:12.062Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:03:12.062Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:03:12.062Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:03:12.062Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:03:12.062Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (34636.040 ms) ====== [2025-11-19T23:03:12.062Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-19T23:03:12.062Z] GC before operation: completed in 278.005 ms, heap usage 377.928 MB -> 90.529 MB. [2025-11-19T23:03:16.369Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:03:20.700Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:03:25.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:03:30.393Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:03:33.505Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:03:36.740Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:03:39.798Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:03:42.928Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:03:43.891Z] 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. [2025-11-19T23:03:43.891Z] The best model improves the baseline by 14.52%. [2025-11-19T23:03:44.858Z] Top recommended movies for user id 72: [2025-11-19T23:03:44.858Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:03:44.858Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:03:44.858Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:03:44.858Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:03:44.858Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:03:44.858Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (32440.762 ms) ====== [2025-11-19T23:03:44.858Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-19T23:03:44.858Z] GC before operation: completed in 271.992 ms, heap usage 106.461 MB -> 90.268 MB. [2025-11-19T23:03:51.697Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T23:03:57.162Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T23:04:03.915Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T23:04:09.315Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T23:04:13.476Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T23:04:15.445Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T23:04:18.466Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T23:04:21.474Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T23:04:21.474Z] 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. [2025-11-19T23:04:21.474Z] The best model improves the baseline by 14.52%. [2025-11-19T23:04:22.430Z] Top recommended movies for user id 72: [2025-11-19T23:04:22.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-19T23:04:22.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-19T23:04:22.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-19T23:04:22.430Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-19T23:04:22.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-19T23:04:22.430Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (37429.119 ms) ====== [2025-11-19T23:04:23.377Z] ----------------------------------- [2025-11-19T23:04:23.377Z] renaissance-movie-lens_0_PASSED [2025-11-19T23:04:23.377Z] ----------------------------------- [2025-11-19T23:04:23.377Z] [2025-11-19T23:04:23.377Z] TEST TEARDOWN: [2025-11-19T23:04:23.377Z] Nothing to be done for teardown. [2025-11-19T23:04:23.377Z] renaissance-movie-lens_0 Finish Time: Wed Nov 19 23:04:22 2025 Epoch Time (ms): 1763593462931