[2025-11-06T02:56:09.404Z] Running test renaissance-movie-lens_0 ... [2025-11-06T02:56:09.404Z] =============================================== [2025-11-06T02:56:09.404Z] renaissance-movie-lens_0 Start Time: Thu Nov 6 02:56:08 2025 Epoch Time (ms): 1762397768843 [2025-11-06T02:56:09.404Z] variation: NoOptions [2025-11-06T02:56:09.404Z] JVM_OPTIONS: [2025-11-06T02:56:09.404Z] { \ [2025-11-06T02:56:09.404Z] echo ""; echo "TEST SETUP:"; \ [2025-11-06T02:56:09.404Z] echo "Nothing to be done for setup."; \ [2025-11-06T02:56:09.404Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623963763701/renaissance-movie-lens_0"; \ [2025-11-06T02:56:09.404Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623963763701/renaissance-movie-lens_0"; \ [2025-11-06T02:56:09.404Z] echo ""; echo "TESTING:"; \ [2025-11-06T02:56:09.404Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623963763701/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-06T02:56:09.405Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623963763701/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-06T02:56:09.405Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-06T02:56:09.405Z] echo "Nothing to be done for teardown."; \ [2025-11-06T02:56:09.405Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623963763701/TestTargetResult"; [2025-11-06T02:56:09.405Z] [2025-11-06T02:56:09.405Z] TEST SETUP: [2025-11-06T02:56:09.405Z] Nothing to be done for setup. [2025-11-06T02:56:09.405Z] [2025-11-06T02:56:09.405Z] TESTING: [2025-11-06T02:56:14.739Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-06T02:56:21.385Z] 02:56:20.047 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. [2025-11-06T02:56:22.328Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-06T02:56:23.276Z] Training: 60056, validation: 20285, test: 19854 [2025-11-06T02:56:23.276Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-06T02:56:23.276Z] GC before operation: completed in 155.321 ms, heap usage 588.531 MB -> 75.936 MB. [2025-11-06T02:56:28.647Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:56:31.642Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:56:34.635Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:56:37.632Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:56:39.581Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:56:40.533Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:56:42.487Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:56:44.444Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:56:44.444Z] 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. [2025-11-06T02:56:44.444Z] The best model improves the baseline by 14.52%. [2025-11-06T02:56:44.444Z] Top recommended movies for user id 72: [2025-11-06T02:56:44.444Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:56:44.444Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:56:44.444Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:56:44.444Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:56:44.444Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:56:44.444Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21313.376 ms) ====== [2025-11-06T02:56:44.444Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-06T02:56:44.444Z] GC before operation: completed in 133.113 ms, heap usage 359.653 MB -> 88.897 MB. [2025-11-06T02:56:47.486Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:56:50.156Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:56:52.110Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:56:55.127Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:56:56.080Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:56:58.034Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:56:58.986Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:57:00.938Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:57:00.938Z] 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. [2025-11-06T02:57:00.938Z] The best model improves the baseline by 14.52%. [2025-11-06T02:57:01.888Z] Top recommended movies for user id 72: [2025-11-06T02:57:01.888Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:57:01.888Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:57:01.888Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:57:01.888Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:57:01.888Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:57:01.888Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16790.302 ms) ====== [2025-11-06T02:57:01.888Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-06T02:57:01.888Z] GC before operation: completed in 133.296 ms, heap usage 243.794 MB -> 88.576 MB. [2025-11-06T02:57:03.853Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:57:06.865Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:57:08.817Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:57:10.769Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:57:12.723Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:57:13.679Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:57:15.632Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:57:16.586Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:57:16.586Z] 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. [2025-11-06T02:57:16.586Z] The best model improves the baseline by 14.52%. [2025-11-06T02:57:17.552Z] Top recommended movies for user id 72: [2025-11-06T02:57:17.552Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:57:17.552Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:57:17.552Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:57:17.552Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:57:17.552Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:57:17.552Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15624.481 ms) ====== [2025-11-06T02:57:17.552Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-06T02:57:17.552Z] GC before operation: completed in 108.662 ms, heap usage 163.338 MB -> 89.233 MB. [2025-11-06T02:57:19.503Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:57:22.514Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:57:24.469Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:57:27.484Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:57:28.435Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:57:30.388Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:57:31.346Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:57:33.298Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:57:33.298Z] 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. [2025-11-06T02:57:33.298Z] The best model improves the baseline by 14.52%. [2025-11-06T02:57:33.298Z] Top recommended movies for user id 72: [2025-11-06T02:57:33.298Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:57:33.298Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:57:33.298Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:57:33.298Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:57:33.298Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:57:33.298Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16016.537 ms) ====== [2025-11-06T02:57:33.298Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-06T02:57:33.298Z] GC before operation: completed in 0.396 ms, heap usage 115.460 MB -> 115.468 MB. [2025-11-06T02:57:35.252Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:57:38.270Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:57:40.222Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:57:42.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:57:44.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:57:45.075Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:57:47.025Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:57:47.976Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:57:47.976Z] 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. [2025-11-06T02:57:47.976Z] The best model improves the baseline by 14.52%. [2025-11-06T02:57:47.976Z] Top recommended movies for user id 72: [2025-11-06T02:57:47.976Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:57:47.976Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:57:47.977Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:57:47.977Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:57:47.977Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:57:47.977Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15077.510 ms) ====== [2025-11-06T02:57:47.977Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-06T02:57:49.630Z] GC before operation: completed in 112.774 ms, heap usage 439.552 MB -> 89.796 MB. [2025-11-06T02:57:51.582Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:57:53.532Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:57:55.483Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:57:57.438Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:57:58.389Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:58:00.516Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:58:01.510Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:58:02.460Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:58:02.460Z] 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. [2025-11-06T02:58:02.460Z] The best model improves the baseline by 14.52%. [2025-11-06T02:58:02.460Z] Top recommended movies for user id 72: [2025-11-06T02:58:02.460Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:58:02.460Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:58:02.460Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:58:02.460Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:58:02.460Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:58:02.460Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14306.623 ms) ====== [2025-11-06T02:58:02.460Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-06T02:58:03.410Z] GC before operation: completed in 113.413 ms, heap usage 427.277 MB -> 90.208 MB. [2025-11-06T02:58:05.458Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:58:08.470Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:58:10.419Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:58:12.368Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:58:13.319Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:58:14.270Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:58:16.223Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:58:17.173Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:58:17.173Z] 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. [2025-11-06T02:58:17.173Z] The best model improves the baseline by 14.52%. [2025-11-06T02:58:18.124Z] Top recommended movies for user id 72: [2025-11-06T02:58:18.124Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:58:18.124Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:58:18.124Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:58:18.124Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:58:18.124Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:58:18.124Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14715.473 ms) ====== [2025-11-06T02:58:18.124Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-06T02:58:18.124Z] GC before operation: completed in 130.628 ms, heap usage 542.142 MB -> 97.631 MB. [2025-11-06T02:58:20.075Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:58:22.035Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:58:23.986Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:58:25.939Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:58:27.894Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:58:28.846Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:58:29.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:58:31.757Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:58:31.757Z] 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. [2025-11-06T02:58:31.757Z] The best model improves the baseline by 14.52%. [2025-11-06T02:58:31.757Z] Top recommended movies for user id 72: [2025-11-06T02:58:31.757Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:58:31.757Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:58:31.757Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:58:31.757Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:58:31.757Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:58:31.757Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13929.696 ms) ====== [2025-11-06T02:58:31.757Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-06T02:58:31.757Z] GC before operation: completed in 114.115 ms, heap usage 792.089 MB -> 96.649 MB. [2025-11-06T02:58:33.714Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:58:36.725Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:58:38.676Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:58:40.631Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:58:41.584Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:58:42.536Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:58:44.489Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:58:45.515Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:58:45.515Z] 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. [2025-11-06T02:58:45.515Z] The best model improves the baseline by 14.52%. [2025-11-06T02:58:45.515Z] Top recommended movies for user id 72: [2025-11-06T02:58:45.515Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:58:45.515Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:58:45.516Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:58:45.516Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:58:45.516Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:58:45.516Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13990.270 ms) ====== [2025-11-06T02:58:45.516Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-06T02:58:45.516Z] GC before operation: completed in 119.352 ms, heap usage 232.771 MB -> 92.330 MB. [2025-11-06T02:58:48.165Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:58:50.122Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:58:52.074Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:58:54.025Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:58:54.976Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:58:56.927Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:58:57.880Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:58:58.830Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:58:58.830Z] 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. [2025-11-06T02:58:58.830Z] The best model improves the baseline by 14.52%. [2025-11-06T02:58:59.782Z] Top recommended movies for user id 72: [2025-11-06T02:58:59.782Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:58:59.782Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:58:59.782Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:58:59.782Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:58:59.782Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:58:59.782Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13445.860 ms) ====== [2025-11-06T02:58:59.782Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-06T02:58:59.782Z] GC before operation: completed in 114.387 ms, heap usage 507.120 MB -> 92.840 MB. [2025-11-06T02:59:01.736Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:59:03.688Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:59:05.642Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:59:07.637Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:59:08.596Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:59:09.550Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:59:11.501Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:59:12.452Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:59:13.402Z] 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. [2025-11-06T02:59:13.402Z] The best model improves the baseline by 14.52%. [2025-11-06T02:59:13.402Z] Top recommended movies for user id 72: [2025-11-06T02:59:13.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:59:13.402Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:59:13.402Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:59:13.402Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:59:13.402Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:59:13.402Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13771.984 ms) ====== [2025-11-06T02:59:13.402Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-06T02:59:13.402Z] GC before operation: completed in 118.917 ms, heap usage 474.006 MB -> 93.471 MB. [2025-11-06T02:59:15.364Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:59:17.320Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:59:20.334Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:59:22.285Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:59:23.236Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:59:24.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:59:26.153Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:59:27.105Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:59:27.105Z] 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. [2025-11-06T02:59:27.105Z] The best model improves the baseline by 14.52%. [2025-11-06T02:59:27.105Z] Top recommended movies for user id 72: [2025-11-06T02:59:27.105Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:59:27.105Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:59:27.105Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:59:27.105Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:59:27.105Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:59:27.105Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14170.600 ms) ====== [2025-11-06T02:59:27.105Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-06T02:59:28.105Z] GC before operation: completed in 112.614 ms, heap usage 490.467 MB -> 94.444 MB. [2025-11-06T02:59:30.060Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:59:32.013Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:59:33.968Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:59:35.918Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:59:36.871Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:59:38.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:59:39.774Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:59:40.725Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:59:41.675Z] 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. [2025-11-06T02:59:41.675Z] The best model improves the baseline by 14.52%. [2025-11-06T02:59:41.675Z] Top recommended movies for user id 72: [2025-11-06T02:59:41.675Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:59:41.675Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:59:41.675Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:59:41.675Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:59:41.675Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:59:41.675Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13740.949 ms) ====== [2025-11-06T02:59:41.675Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-06T02:59:41.675Z] GC before operation: completed in 115.046 ms, heap usage 373.356 MB -> 94.106 MB. [2025-11-06T02:59:43.631Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:59:46.030Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:59:48.007Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:59:49.958Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:59:50.914Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:59:52.866Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:59:53.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:59:55.767Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:59:55.767Z] 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. [2025-11-06T02:59:55.767Z] The best model improves the baseline by 14.52%. [2025-11-06T02:59:55.767Z] Top recommended movies for user id 72: [2025-11-06T02:59:55.767Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T02:59:55.767Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T02:59:55.767Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T02:59:55.767Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T02:59:55.767Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T02:59:55.767Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14186.249 ms) ====== [2025-11-06T02:59:55.767Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-06T02:59:55.767Z] GC before operation: completed in 165.143 ms, heap usage 213.735 MB -> 91.237 MB. [2025-11-06T02:59:58.787Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:00:00.747Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:00:03.815Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:00:05.765Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:00:06.778Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:00:08.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:00:09.682Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:00:10.635Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:00:10.635Z] 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. [2025-11-06T03:00:10.635Z] The best model improves the baseline by 14.52%. [2025-11-06T03:00:11.585Z] Top recommended movies for user id 72: [2025-11-06T03:00:11.585Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T03:00:11.585Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T03:00:11.585Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T03:00:11.585Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T03:00:11.585Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T03:00:11.585Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15313.315 ms) ====== [2025-11-06T03:00:11.585Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-06T03:00:11.585Z] GC before operation: completed in 134.887 ms, heap usage 507.645 MB -> 96.409 MB. [2025-11-06T03:00:13.536Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:00:15.496Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:00:18.578Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:00:20.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:00:21.478Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:00:22.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:00:24.380Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:00:25.330Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:00:25.330Z] 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. [2025-11-06T03:00:25.330Z] The best model improves the baseline by 14.52%. [2025-11-06T03:00:26.284Z] Top recommended movies for user id 72: [2025-11-06T03:00:26.284Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T03:00:26.284Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T03:00:26.284Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T03:00:26.284Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T03:00:26.284Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T03:00:26.284Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14535.814 ms) ====== [2025-11-06T03:00:26.284Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-06T03:00:26.284Z] GC before operation: completed in 167.527 ms, heap usage 384.114 MB -> 93.923 MB. [2025-11-06T03:00:28.236Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:00:30.188Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:00:33.200Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:00:35.151Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:00:36.103Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:00:38.055Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:00:39.004Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:00:39.954Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:00:40.907Z] 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. [2025-11-06T03:00:40.907Z] The best model improves the baseline by 14.52%. [2025-11-06T03:00:40.907Z] Top recommended movies for user id 72: [2025-11-06T03:00:40.907Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T03:00:40.907Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T03:00:40.907Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T03:00:40.907Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T03:00:40.907Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T03:00:40.907Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14705.620 ms) ====== [2025-11-06T03:00:40.907Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-06T03:00:40.907Z] GC before operation: completed in 169.388 ms, heap usage 459.662 MB -> 91.661 MB. [2025-11-06T03:00:43.558Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:00:46.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:00:48.528Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:00:50.481Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:00:51.430Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:00:53.383Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:00:54.337Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:00:55.290Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:00:56.242Z] 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. [2025-11-06T03:00:56.242Z] The best model improves the baseline by 14.52%. [2025-11-06T03:00:56.242Z] Top recommended movies for user id 72: [2025-11-06T03:00:56.242Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T03:00:56.242Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T03:00:56.242Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T03:00:56.242Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T03:00:56.242Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T03:00:56.242Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15208.304 ms) ====== [2025-11-06T03:00:56.242Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-06T03:00:56.242Z] GC before operation: completed in 116.878 ms, heap usage 135.978 MB -> 95.684 MB. [2025-11-06T03:00:58.194Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:01:00.148Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:01:03.195Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:01:05.268Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:01:06.218Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:01:07.168Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:01:09.120Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:01:10.072Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:01:10.072Z] 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. [2025-11-06T03:01:10.072Z] The best model improves the baseline by 14.52%. [2025-11-06T03:01:10.072Z] Top recommended movies for user id 72: [2025-11-06T03:01:10.072Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T03:01:10.072Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T03:01:10.072Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T03:01:10.072Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T03:01:10.072Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T03:01:10.072Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14230.916 ms) ====== [2025-11-06T03:01:10.072Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-06T03:01:11.024Z] GC before operation: completed in 144.006 ms, heap usage 233.500 MB -> 91.915 MB. [2025-11-06T03:01:12.976Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:01:14.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:01:16.887Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:01:19.902Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:01:20.853Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:01:21.804Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:01:23.755Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:01:24.707Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:01:24.707Z] 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. [2025-11-06T03:01:24.707Z] The best model improves the baseline by 14.52%. [2025-11-06T03:01:24.707Z] Top recommended movies for user id 72: [2025-11-06T03:01:24.707Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T03:01:24.707Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T03:01:24.707Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T03:01:24.707Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T03:01:24.707Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T03:01:24.707Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14458.420 ms) ====== [2025-11-06T03:01:25.657Z] ----------------------------------- [2025-11-06T03:01:25.657Z] renaissance-movie-lens_0_PASSED [2025-11-06T03:01:25.657Z] ----------------------------------- [2025-11-06T03:01:25.657Z] [2025-11-06T03:01:25.657Z] TEST TEARDOWN: [2025-11-06T03:01:25.657Z] Nothing to be done for teardown. [2025-11-06T03:01:25.657Z] renaissance-movie-lens_0 Finish Time: Thu Nov 6 03:01:25 2025 Epoch Time (ms): 1762398085059