[2025-11-06T04:05:00.027Z] Running test renaissance-movie-lens_0 ... [2025-11-06T04:05:00.027Z] =============================================== [2025-11-06T04:05:00.027Z] renaissance-movie-lens_0 Start Time: Thu Nov 6 04:04:59 2025 Epoch Time (ms): 1762401899235 [2025-11-06T04:05:00.027Z] variation: NoOptions [2025-11-06T04:05:00.027Z] JVM_OPTIONS: [2025-11-06T04:05:00.027Z] { \ [2025-11-06T04:05:00.027Z] echo ""; echo "TEST SETUP:"; \ [2025-11-06T04:05:00.027Z] echo "Nothing to be done for setup."; \ [2025-11-06T04:05:00.027Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17623986436024/renaissance-movie-lens_0"; \ [2025-11-06T04:05:00.027Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17623986436024/renaissance-movie-lens_0"; \ [2025-11-06T04:05:00.027Z] echo ""; echo "TESTING:"; \ [2025-11-06T04:05:00.027Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17623986436024/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-06T04:05:00.027Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17623986436024/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-06T04:05:00.027Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-06T04:05:00.027Z] echo "Nothing to be done for teardown."; \ [2025-11-06T04:05:00.027Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17623986436024/TestTargetResult"; [2025-11-06T04:05:00.027Z] [2025-11-06T04:05:00.027Z] TEST SETUP: [2025-11-06T04:05:00.027Z] Nothing to be done for setup. [2025-11-06T04:05:00.027Z] [2025-11-06T04:05:00.027Z] TESTING: [2025-11-06T04:05:11.741Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-06T04:05:30.477Z] 04:05:28.833 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. [2025-11-06T04:05:34.334Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-06T04:05:36.335Z] Training: 60056, validation: 20285, test: 19854 [2025-11-06T04:05:36.335Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-06T04:05:36.335Z] GC before operation: completed in 292.774 ms, heap usage 275.577 MB -> 74.667 MB. [2025-11-06T04:05:58.259Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:06:10.081Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:06:18.382Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:06:26.697Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:06:29.763Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:06:34.015Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:06:38.253Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:06:42.551Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:06:42.551Z] 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. [2025-11-06T04:06:43.517Z] The best model improves the baseline by 14.52%. [2025-11-06T04:06:43.517Z] Top recommended movies for user id 72: [2025-11-06T04:06:43.517Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:06:43.517Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:06:43.517Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:06:43.517Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:06:43.517Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:06:43.517Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (67036.721 ms) ====== [2025-11-06T04:06:43.517Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-06T04:06:43.517Z] GC before operation: completed in 380.399 ms, heap usage 129.140 MB -> 85.352 MB. [2025-11-06T04:06:51.743Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:06:57.928Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:07:03.402Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:07:10.154Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:07:14.339Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:07:18.537Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:07:22.744Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:07:26.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:07:27.886Z] 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. [2025-11-06T04:07:27.886Z] The best model improves the baseline by 14.52%. [2025-11-06T04:07:27.886Z] Top recommended movies for user id 72: [2025-11-06T04:07:27.886Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:07:27.886Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:07:27.886Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:07:27.886Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:07:27.886Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:07:27.886Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44284.591 ms) ====== [2025-11-06T04:07:27.886Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-06T04:07:28.844Z] GC before operation: completed in 405.183 ms, heap usage 375.792 MB -> 87.736 MB. [2025-11-06T04:07:35.607Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:07:42.379Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:07:47.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:07:54.599Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:07:57.662Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:08:00.703Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:08:04.909Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:08:07.965Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:08:07.965Z] 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. [2025-11-06T04:08:08.927Z] The best model improves the baseline by 14.52%. [2025-11-06T04:08:08.927Z] Top recommended movies for user id 72: [2025-11-06T04:08:08.927Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:08:08.927Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:08:08.927Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:08:08.927Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:08:08.927Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:08:08.927Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (40101.269 ms) ====== [2025-11-06T04:08:08.927Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-06T04:08:08.927Z] GC before operation: completed in 314.854 ms, heap usage 300.598 MB -> 88.367 MB. [2025-11-06T04:08:15.110Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:08:20.546Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:08:27.326Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:08:32.770Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:08:36.962Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:08:41.187Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:08:45.392Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:08:48.441Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:08:48.441Z] 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. [2025-11-06T04:08:48.441Z] The best model improves the baseline by 14.52%. [2025-11-06T04:08:48.441Z] Top recommended movies for user id 72: [2025-11-06T04:08:48.441Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:08:48.441Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:08:48.441Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:08:48.441Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:08:48.441Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:08:48.441Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (39587.900 ms) ====== [2025-11-06T04:08:48.441Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-06T04:08:49.400Z] GC before operation: completed in 370.605 ms, heap usage 463.257 MB -> 88.740 MB. [2025-11-06T04:08:54.841Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:09:00.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:09:07.211Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:09:12.677Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:09:15.737Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:09:19.925Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:09:23.013Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:09:26.597Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:09:26.597Z] 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. [2025-11-06T04:09:27.766Z] The best model improves the baseline by 14.52%. [2025-11-06T04:09:27.766Z] Top recommended movies for user id 72: [2025-11-06T04:09:27.766Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:09:27.766Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:09:27.766Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:09:27.766Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:09:27.766Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:09:27.766Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (37845.038 ms) ====== [2025-11-06T04:09:27.766Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-06T04:09:27.766Z] GC before operation: completed in 256.711 ms, heap usage 364.213 MB -> 88.626 MB. [2025-11-06T04:09:33.242Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:09:38.658Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:09:42.877Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:09:48.301Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:09:51.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:09:55.558Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:09:58.592Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:10:01.636Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:10:01.636Z] 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. [2025-11-06T04:10:01.636Z] The best model improves the baseline by 14.52%. [2025-11-06T04:10:02.595Z] Top recommended movies for user id 72: [2025-11-06T04:10:02.595Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:10:02.595Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:10:02.595Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:10:02.595Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:10:02.595Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:10:02.595Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (35181.719 ms) ====== [2025-11-06T04:10:02.595Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-06T04:10:02.595Z] GC before operation: completed in 335.535 ms, heap usage 343.106 MB -> 88.938 MB. [2025-11-06T04:10:08.176Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:10:13.600Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:10:19.021Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:10:23.207Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:10:27.397Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:10:30.443Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:10:33.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:10:36.551Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:10:37.514Z] 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. [2025-11-06T04:10:37.514Z] The best model improves the baseline by 14.52%. [2025-11-06T04:10:37.514Z] Top recommended movies for user id 72: [2025-11-06T04:10:37.514Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:10:37.514Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:10:37.514Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:10:37.514Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:10:37.514Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:10:37.514Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (35185.423 ms) ====== [2025-11-06T04:10:37.514Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-06T04:10:38.476Z] GC before operation: completed in 302.309 ms, heap usage 182.838 MB -> 88.728 MB. [2025-11-06T04:10:43.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:10:48.616Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:10:54.063Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:10:58.429Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:11:01.470Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:11:04.538Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:11:07.595Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:11:10.641Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:11:11.600Z] 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. [2025-11-06T04:11:11.600Z] The best model improves the baseline by 14.52%. [2025-11-06T04:11:11.600Z] Top recommended movies for user id 72: [2025-11-06T04:11:11.600Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:11:11.600Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:11:11.600Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:11:11.600Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:11:11.600Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:11:11.600Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (33485.275 ms) ====== [2025-11-06T04:11:11.600Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-06T04:11:11.600Z] GC before operation: completed in 333.355 ms, heap usage 234.594 MB -> 88.919 MB. [2025-11-06T04:11:17.013Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:11:22.457Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:11:27.893Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:11:32.089Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:11:35.145Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:11:38.185Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:11:41.220Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:11:44.263Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:11:45.222Z] 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. [2025-11-06T04:11:45.222Z] The best model improves the baseline by 14.52%. [2025-11-06T04:11:45.222Z] Top recommended movies for user id 72: [2025-11-06T04:11:45.222Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:11:45.222Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:11:45.222Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:11:45.222Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:11:45.222Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:11:45.222Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (33288.824 ms) ====== [2025-11-06T04:11:45.222Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-06T04:11:45.222Z] GC before operation: completed in 322.869 ms, heap usage 103.427 MB -> 88.653 MB. [2025-11-06T04:11:50.636Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:11:55.561Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:12:00.985Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:12:05.186Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:12:08.252Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:12:11.308Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:12:15.495Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:12:18.546Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:12:19.504Z] 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. [2025-11-06T04:12:19.504Z] The best model improves the baseline by 14.52%. [2025-11-06T04:12:19.504Z] Top recommended movies for user id 72: [2025-11-06T04:12:19.504Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:12:19.504Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:12:19.504Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:12:19.504Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:12:19.504Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:12:19.504Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (33990.760 ms) ====== [2025-11-06T04:12:19.504Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-06T04:12:19.504Z] GC before operation: completed in 358.689 ms, heap usage 181.169 MB -> 89.015 MB. [2025-11-06T04:12:26.312Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:12:30.517Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:12:35.936Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:12:41.345Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:12:44.391Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:12:47.440Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:12:50.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:12:53.524Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:12:53.524Z] 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. [2025-11-06T04:12:53.524Z] The best model improves the baseline by 14.52%. [2025-11-06T04:12:54.486Z] Top recommended movies for user id 72: [2025-11-06T04:12:54.486Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:12:54.486Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:12:54.486Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:12:54.486Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:12:54.486Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:12:54.486Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (34130.164 ms) ====== [2025-11-06T04:12:54.486Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-06T04:12:54.486Z] GC before operation: completed in 268.157 ms, heap usage 161.247 MB -> 88.624 MB. [2025-11-06T04:12:58.674Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:13:04.094Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:13:08.782Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:13:14.207Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:13:17.256Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:13:20.310Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:13:24.503Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:13:27.549Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:13:27.549Z] 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. [2025-11-06T04:13:28.513Z] The best model improves the baseline by 14.52%. [2025-11-06T04:13:28.513Z] Top recommended movies for user id 72: [2025-11-06T04:13:28.513Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:13:28.513Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:13:28.513Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:13:28.513Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:13:28.513Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:13:28.513Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (33982.954 ms) ====== [2025-11-06T04:13:28.513Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-06T04:13:28.513Z] GC before operation: completed in 325.109 ms, heap usage 315.025 MB -> 89.111 MB. [2025-11-06T04:13:33.939Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:13:39.388Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:13:44.817Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:13:50.236Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:13:52.204Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:13:55.252Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:13:59.447Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:14:02.541Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:14:02.541Z] 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. [2025-11-06T04:14:02.541Z] The best model improves the baseline by 14.52%. [2025-11-06T04:14:02.541Z] Top recommended movies for user id 72: [2025-11-06T04:14:02.541Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:14:02.541Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:14:02.541Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:14:02.541Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:14:02.541Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:14:02.541Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (34122.749 ms) ====== [2025-11-06T04:14:02.541Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-06T04:14:03.510Z] GC before operation: completed in 400.779 ms, heap usage 402.264 MB -> 89.297 MB. [2025-11-06T04:14:07.722Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:14:13.145Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:14:18.761Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:14:24.254Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:14:27.301Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:14:30.331Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:14:33.378Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:14:36.429Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:14:36.429Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T04:14:36.429Z] The best model improves the baseline by 14.52%. [2025-11-06T04:14:37.389Z] Top recommended movies for user id 72: [2025-11-06T04:14:37.389Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:14:37.389Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:14:37.389Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:14:37.389Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:14:37.389Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:14:37.389Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (33954.831 ms) ====== [2025-11-06T04:14:37.389Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-06T04:14:37.389Z] GC before operation: completed in 346.191 ms, heap usage 373.450 MB -> 89.035 MB. [2025-11-06T04:14:44.161Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:14:48.386Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:14:53.792Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:14:57.977Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:15:01.032Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:15:04.084Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:15:07.136Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:15:10.178Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:15:10.178Z] 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. [2025-11-06T04:15:10.178Z] The best model improves the baseline by 14.52%. [2025-11-06T04:15:11.142Z] Top recommended movies for user id 72: [2025-11-06T04:15:11.142Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:15:11.142Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:15:11.142Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:15:11.142Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:15:11.142Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:15:11.142Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (33221.174 ms) ====== [2025-11-06T04:15:11.142Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-06T04:15:11.142Z] GC before operation: completed in 406.135 ms, heap usage 444.580 MB -> 89.373 MB. [2025-11-06T04:15:16.568Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:15:20.767Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:15:26.202Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:15:30.394Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:15:33.068Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:15:36.121Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:15:39.221Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:15:42.284Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:15:43.251Z] 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. [2025-11-06T04:15:43.251Z] The best model improves the baseline by 14.52%. [2025-11-06T04:15:43.251Z] Top recommended movies for user id 72: [2025-11-06T04:15:43.251Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:15:43.251Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:15:43.251Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:15:43.251Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:15:43.251Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:15:43.251Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (32415.505 ms) ====== [2025-11-06T04:15:43.251Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-06T04:15:44.211Z] GC before operation: completed in 352.652 ms, heap usage 206.925 MB -> 88.952 MB. [2025-11-06T04:15:49.672Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:15:55.107Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:16:00.695Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:16:04.895Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:16:09.119Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:16:12.154Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:16:15.211Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:16:18.347Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:16:18.347Z] 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. [2025-11-06T04:16:19.305Z] The best model improves the baseline by 14.52%. [2025-11-06T04:16:19.305Z] Top recommended movies for user id 72: [2025-11-06T04:16:19.305Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:16:19.305Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:16:19.305Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:16:19.305Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:16:19.305Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:16:19.305Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (35306.355 ms) ====== [2025-11-06T04:16:19.305Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-06T04:16:19.305Z] GC before operation: completed in 328.233 ms, heap usage 174.525 MB -> 89.042 MB. [2025-11-06T04:16:24.740Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:16:30.173Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:16:34.372Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:16:39.897Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:16:42.955Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:16:45.716Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:16:49.961Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:16:51.967Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:16:52.941Z] 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. [2025-11-06T04:16:52.941Z] The best model improves the baseline by 14.52%. [2025-11-06T04:16:52.941Z] Top recommended movies for user id 72: [2025-11-06T04:16:52.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:16:52.941Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:16:52.941Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:16:52.941Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:16:52.941Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:16:52.941Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (33793.037 ms) ====== [2025-11-06T04:16:52.941Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-06T04:16:53.912Z] GC before operation: completed in 275.849 ms, heap usage 344.873 MB -> 89.028 MB. [2025-11-06T04:16:59.393Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:17:04.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:17:10.367Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:17:15.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:17:18.917Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:17:21.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:17:25.089Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:17:28.151Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:17:28.151Z] 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. [2025-11-06T04:17:28.151Z] The best model improves the baseline by 14.52%. [2025-11-06T04:17:29.124Z] Top recommended movies for user id 72: [2025-11-06T04:17:29.124Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:17:29.124Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:17:29.124Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:17:29.124Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:17:29.124Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:17:29.124Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (35200.609 ms) ====== [2025-11-06T04:17:29.124Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-06T04:17:29.124Z] GC before operation: completed in 323.100 ms, heap usage 260.704 MB -> 89.063 MB. [2025-11-06T04:17:33.363Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T04:17:38.839Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T04:17:43.066Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T04:17:48.540Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T04:17:51.625Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T04:17:53.622Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T04:17:56.700Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T04:18:00.264Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T04:18:00.264Z] 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. [2025-11-06T04:18:00.264Z] The best model improves the baseline by 14.52%. [2025-11-06T04:18:01.239Z] Top recommended movies for user id 72: [2025-11-06T04:18:01.239Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T04:18:01.239Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T04:18:01.239Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T04:18:01.239Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T04:18:01.239Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T04:18:01.239Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (31782.342 ms) ====== [2025-11-06T04:18:02.207Z] ----------------------------------- [2025-11-06T04:18:02.207Z] renaissance-movie-lens_0_PASSED [2025-11-06T04:18:02.207Z] ----------------------------------- [2025-11-06T04:18:02.207Z] [2025-11-06T04:18:02.207Z] TEST TEARDOWN: [2025-11-06T04:18:02.207Z] Nothing to be done for teardown. [2025-11-06T04:18:02.207Z] renaissance-movie-lens_0 Finish Time: Thu Nov 6 04:18:01 2025 Epoch Time (ms): 1762402681525