[2025-11-27T14:19:51.932Z] Running test renaissance-movie-lens_0 ... [2025-11-27T14:19:51.932Z] =============================================== [2025-11-27T14:19:51.932Z] renaissance-movie-lens_0 Start Time: Thu Nov 27 14:19:51 2025 Epoch Time (ms): 1764253191081 [2025-11-27T14:19:51.932Z] variation: NoOptions [2025-11-27T14:19:51.932Z] JVM_OPTIONS: [2025-11-27T14:19:51.932Z] { \ [2025-11-27T14:19:51.932Z] echo ""; echo "TEST SETUP:"; \ [2025-11-27T14:19:51.932Z] echo "Nothing to be done for setup."; \ [2025-11-27T14:19:51.932Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642520084958/renaissance-movie-lens_0"; \ [2025-11-27T14:19:51.932Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642520084958/renaissance-movie-lens_0"; \ [2025-11-27T14:19:51.932Z] echo ""; echo "TESTING:"; \ [2025-11-27T14:19:51.932Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/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_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642520084958/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-27T14:19:51.932Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642520084958/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-27T14:19:51.932Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-27T14:19:51.932Z] echo "Nothing to be done for teardown."; \ [2025-11-27T14:19:51.932Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642520084958/TestTargetResult"; [2025-11-27T14:19:51.932Z] [2025-11-27T14:19:51.932Z] TEST SETUP: [2025-11-27T14:19:51.932Z] Nothing to be done for setup. [2025-11-27T14:19:51.932Z] [2025-11-27T14:19:51.932Z] TESTING: [2025-11-27T14:19:56.233Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-27T14:20:06.422Z] 14:20:05.571 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. [2025-11-27T14:20:07.965Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-27T14:20:08.705Z] Training: 60056, validation: 20285, test: 19854 [2025-11-27T14:20:08.705Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-27T14:20:08.705Z] GC before operation: completed in 118.841 ms, heap usage 366.263 MB -> 75.838 MB. [2025-11-27T14:20:16.902Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:20:21.227Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:20:24.533Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:20:27.854Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:20:29.391Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:20:31.769Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:20:33.353Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:20:34.894Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:20:35.641Z] 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. [2025-11-27T14:20:35.641Z] The best model improves the baseline by 14.52%. [2025-11-27T14:20:35.642Z] Top recommended movies for user id 72: [2025-11-27T14:20:35.642Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:20:35.642Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:20:35.642Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:20:35.642Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:20:35.642Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:20:35.642Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26699.437 ms) ====== [2025-11-27T14:20:35.642Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-27T14:20:35.642Z] GC before operation: completed in 122.852 ms, heap usage 503.856 MB -> 100.119 MB. [2025-11-27T14:20:38.976Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:20:42.300Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:20:44.689Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:20:47.583Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:20:49.120Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:20:50.681Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:20:54.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:20:56.396Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:20:56.396Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T14:20:56.396Z] The best model improves the baseline by 14.52%. [2025-11-27T14:20:56.396Z] Top recommended movies for user id 72: [2025-11-27T14:20:56.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:20:56.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:20:56.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:20:56.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:20:56.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:20:56.396Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20782.423 ms) ====== [2025-11-27T14:20:56.396Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-27T14:20:56.396Z] GC before operation: completed in 109.903 ms, heap usage 140.795 MB -> 91.600 MB. [2025-11-27T14:21:01.827Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:21:10.486Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:21:12.878Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:21:15.259Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:21:16.801Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:21:18.338Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:21:19.875Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:21:21.422Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:21:21.422Z] 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. [2025-11-27T14:21:21.422Z] The best model improves the baseline by 14.52%. [2025-11-27T14:21:21.422Z] Top recommended movies for user id 72: [2025-11-27T14:21:21.422Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:21:21.422Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:21:21.422Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:21:21.422Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:21:21.422Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:21:21.422Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24848.427 ms) ====== [2025-11-27T14:21:21.422Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-27T14:21:21.422Z] GC before operation: completed in 113.869 ms, heap usage 683.076 MB -> 96.674 MB. [2025-11-27T14:21:24.717Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:21:27.092Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:21:29.478Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:21:31.857Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:21:33.400Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:21:34.930Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:21:36.498Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:21:38.026Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:21:38.026Z] 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. [2025-11-27T14:21:38.027Z] The best model improves the baseline by 14.52%. [2025-11-27T14:21:38.027Z] Top recommended movies for user id 72: [2025-11-27T14:21:38.027Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:21:38.027Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:21:38.027Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:21:38.027Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:21:38.027Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:21:38.027Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16719.776 ms) ====== [2025-11-27T14:21:38.027Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-27T14:21:38.762Z] GC before operation: completed in 111.260 ms, heap usage 183.025 MB -> 91.189 MB. [2025-11-27T14:21:40.775Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:21:43.151Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:21:46.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:21:48.842Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:21:50.372Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:21:51.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:21:53.462Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:21:54.996Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:21:54.996Z] 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. [2025-11-27T14:21:54.996Z] The best model improves the baseline by 14.52%. [2025-11-27T14:21:54.996Z] Top recommended movies for user id 72: [2025-11-27T14:21:54.996Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:21:54.996Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:21:54.996Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:21:54.996Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:21:54.996Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:21:54.996Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16524.745 ms) ====== [2025-11-27T14:21:54.996Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-27T14:21:54.996Z] GC before operation: completed in 109.956 ms, heap usage 492.450 MB -> 89.761 MB. [2025-11-27T14:21:57.380Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:22:00.696Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:22:03.082Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:22:05.466Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:22:06.207Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:22:07.741Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:22:09.277Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:22:10.814Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:22:10.814Z] 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. [2025-11-27T14:22:10.814Z] The best model improves the baseline by 14.52%. [2025-11-27T14:22:10.814Z] Top recommended movies for user id 72: [2025-11-27T14:22:10.814Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:22:10.814Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:22:10.814Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:22:10.814Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:22:10.814Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:22:10.814Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16055.056 ms) ====== [2025-11-27T14:22:10.814Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-27T14:22:11.549Z] GC before operation: completed in 109.934 ms, heap usage 510.017 MB -> 90.265 MB. [2025-11-27T14:22:13.941Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:22:16.354Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:22:18.732Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:22:21.605Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:22:22.346Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:22:23.888Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:22:24.624Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:22:26.151Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:22:26.151Z] 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. [2025-11-27T14:22:26.151Z] The best model improves the baseline by 14.52%. [2025-11-27T14:22:26.891Z] Top recommended movies for user id 72: [2025-11-27T14:22:26.891Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:22:26.891Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:22:26.891Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:22:26.891Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:22:26.891Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:22:26.891Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15317.279 ms) ====== [2025-11-27T14:22:26.891Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-27T14:22:26.891Z] GC before operation: completed in 111.319 ms, heap usage 532.430 MB -> 93.444 MB. [2025-11-27T14:22:29.277Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:22:31.656Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:22:34.035Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:22:35.597Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:22:37.120Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:22:38.650Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:22:40.191Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:22:41.722Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:22:41.722Z] 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. [2025-11-27T14:22:41.722Z] The best model improves the baseline by 14.52%. [2025-11-27T14:22:41.722Z] Top recommended movies for user id 72: [2025-11-27T14:22:41.722Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:22:41.722Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:22:41.722Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:22:41.722Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:22:41.722Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:22:41.722Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15091.464 ms) ====== [2025-11-27T14:22:41.722Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-27T14:22:41.722Z] GC before operation: completed in 113.141 ms, heap usage 435.663 MB -> 90.330 MB. [2025-11-27T14:22:44.110Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:22:46.486Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:22:48.878Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:22:51.263Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:22:52.803Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:22:53.544Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:22:55.080Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:22:56.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:22:56.614Z] 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. [2025-11-27T14:22:56.614Z] The best model improves the baseline by 14.52%. [2025-11-27T14:22:56.614Z] Top recommended movies for user id 72: [2025-11-27T14:22:56.614Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:22:56.614Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:22:56.614Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:22:56.614Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:22:56.614Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:22:57.350Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15079.151 ms) ====== [2025-11-27T14:22:57.350Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-27T14:22:57.350Z] GC before operation: completed in 115.393 ms, heap usage 239.444 MB -> 89.828 MB. [2025-11-27T14:22:59.733Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:23:01.760Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:23:04.151Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:23:06.529Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:23:08.146Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:23:09.683Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:23:10.423Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:23:11.954Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:23:12.700Z] 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. [2025-11-27T14:23:12.700Z] The best model improves the baseline by 14.52%. [2025-11-27T14:23:12.700Z] Top recommended movies for user id 72: [2025-11-27T14:23:12.700Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:23:12.700Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:23:12.700Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:23:12.700Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:23:12.700Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:23:12.700Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15402.008 ms) ====== [2025-11-27T14:23:12.700Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-27T14:23:12.700Z] GC before operation: completed in 107.265 ms, heap usage 211.515 MB -> 90.065 MB. [2025-11-27T14:23:15.082Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:23:17.461Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:23:19.845Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:23:22.244Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:23:23.774Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:23:24.515Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:23:26.043Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:23:27.574Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:23:28.310Z] 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. [2025-11-27T14:23:28.310Z] The best model improves the baseline by 14.52%. [2025-11-27T14:23:28.310Z] Top recommended movies for user id 72: [2025-11-27T14:23:28.310Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:23:28.310Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:23:28.310Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:23:28.310Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:23:28.310Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:23:28.310Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15484.749 ms) ====== [2025-11-27T14:23:28.310Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-27T14:23:28.310Z] GC before operation: completed in 113.493 ms, heap usage 475.852 MB -> 90.166 MB. [2025-11-27T14:23:30.695Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:23:33.076Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:23:35.455Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:23:36.978Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:23:38.505Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:23:40.037Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:23:41.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:23:43.114Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:23:43.114Z] 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. [2025-11-27T14:23:43.114Z] The best model improves the baseline by 14.52%. [2025-11-27T14:23:43.114Z] Top recommended movies for user id 72: [2025-11-27T14:23:43.114Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:23:43.114Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:23:43.114Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:23:43.114Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:23:43.114Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:23:43.114Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14858.452 ms) ====== [2025-11-27T14:23:43.114Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-27T14:23:43.114Z] GC before operation: completed in 110.364 ms, heap usage 125.483 MB -> 90.702 MB. [2025-11-27T14:23:45.952Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:23:48.343Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:23:50.720Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:23:53.096Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:23:55.469Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:23:56.209Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:23:57.752Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:23:59.287Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:23:59.287Z] 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. [2025-11-27T14:24:00.028Z] The best model improves the baseline by 14.52%. [2025-11-27T14:24:00.028Z] Top recommended movies for user id 72: [2025-11-27T14:24:00.028Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:24:00.028Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:24:00.028Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:24:00.028Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:24:00.028Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:24:00.028Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16611.993 ms) ====== [2025-11-27T14:24:00.028Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-27T14:24:00.028Z] GC before operation: completed in 100.354 ms, heap usage 510.228 MB -> 92.782 MB. [2025-11-27T14:24:02.408Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:24:04.848Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:24:08.181Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:24:10.561Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:24:12.103Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:24:12.845Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:24:14.410Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:24:15.935Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:24:15.935Z] 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. [2025-11-27T14:24:15.935Z] The best model improves the baseline by 14.52%. [2025-11-27T14:24:16.671Z] Top recommended movies for user id 72: [2025-11-27T14:24:16.672Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:24:16.672Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:24:16.672Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:24:16.672Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:24:16.672Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:24:16.672Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16487.892 ms) ====== [2025-11-27T14:24:16.672Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-27T14:24:16.672Z] GC before operation: completed in 109.215 ms, heap usage 485.689 MB -> 93.751 MB. [2025-11-27T14:24:19.092Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:24:21.467Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:24:23.933Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:24:26.394Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:24:27.929Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:24:28.669Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:24:30.676Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:24:31.418Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:24:32.182Z] 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. [2025-11-27T14:24:32.182Z] The best model improves the baseline by 14.52%. [2025-11-27T14:24:32.182Z] Top recommended movies for user id 72: [2025-11-27T14:24:32.182Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:24:32.182Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:24:32.182Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:24:32.182Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:24:32.182Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:24:32.182Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15615.356 ms) ====== [2025-11-27T14:24:32.182Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-27T14:24:32.182Z] GC before operation: completed in 114.591 ms, heap usage 543.072 MB -> 96.079 MB. [2025-11-27T14:24:34.557Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:24:36.987Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:24:39.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:24:41.730Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:24:43.255Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:24:43.993Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:24:46.377Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:24:47.118Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:24:47.857Z] 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. [2025-11-27T14:24:47.857Z] The best model improves the baseline by 14.52%. [2025-11-27T14:24:47.857Z] Top recommended movies for user id 72: [2025-11-27T14:24:47.857Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:24:47.857Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:24:47.857Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:24:47.857Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:24:47.857Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:24:47.857Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15574.942 ms) ====== [2025-11-27T14:24:47.857Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-27T14:24:47.857Z] GC before operation: completed in 105.404 ms, heap usage 139.999 MB -> 93.038 MB. [2025-11-27T14:24:51.165Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:24:53.537Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:24:55.914Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:24:58.281Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:24:59.813Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:25:01.349Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:25:02.087Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:25:03.693Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:25:03.693Z] 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. [2025-11-27T14:25:03.693Z] The best model improves the baseline by 14.52%. [2025-11-27T14:25:04.432Z] Top recommended movies for user id 72: [2025-11-27T14:25:04.432Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:25:04.432Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:25:04.432Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:25:04.432Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:25:04.432Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:25:04.432Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16259.928 ms) ====== [2025-11-27T14:25:04.432Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-27T14:25:04.432Z] GC before operation: completed in 107.995 ms, heap usage 126.628 MB -> 95.603 MB. [2025-11-27T14:25:06.817Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:25:09.197Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:25:10.850Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:25:13.724Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:25:14.460Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:25:15.987Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:25:17.514Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:25:20.145Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:25:20.884Z] 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. [2025-11-27T14:25:20.884Z] The best model improves the baseline by 14.52%. [2025-11-27T14:25:20.884Z] Top recommended movies for user id 72: [2025-11-27T14:25:20.884Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:25:20.884Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:25:20.884Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:25:20.884Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:25:20.884Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:25:20.884Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16467.461 ms) ====== [2025-11-27T14:25:20.884Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-27T14:25:20.884Z] GC before operation: completed in 106.527 ms, heap usage 529.500 MB -> 92.678 MB. [2025-11-27T14:25:30.456Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:25:31.982Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:25:34.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:25:36.758Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:25:38.307Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:25:39.046Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:25:40.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:25:42.109Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:25:42.109Z] 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. [2025-11-27T14:25:42.109Z] The best model improves the baseline by 14.52%. [2025-11-27T14:25:42.109Z] Top recommended movies for user id 72: [2025-11-27T14:25:42.109Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:25:42.109Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:25:42.109Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:25:42.109Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:25:42.109Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:25:42.109Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (21473.482 ms) ====== [2025-11-27T14:25:42.109Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-27T14:25:42.109Z] GC before operation: completed in 110.529 ms, heap usage 208.812 MB -> 92.540 MB. [2025-11-27T14:25:45.415Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T14:25:47.790Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T14:25:49.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T14:25:51.702Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T14:25:54.994Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T14:25:56.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T14:25:58.058Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T14:25:59.284Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T14:25:59.284Z] 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. [2025-11-27T14:25:59.284Z] The best model improves the baseline by 14.52%. [2025-11-27T14:25:59.284Z] Top recommended movies for user id 72: [2025-11-27T14:25:59.284Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T14:25:59.285Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T14:25:59.285Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T14:25:59.285Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T14:25:59.285Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T14:25:59.285Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16909.046 ms) ====== [2025-11-27T14:26:00.022Z] ----------------------------------- [2025-11-27T14:26:00.022Z] renaissance-movie-lens_0_PASSED [2025-11-27T14:26:00.022Z] ----------------------------------- [2025-11-27T14:26:00.022Z] [2025-11-27T14:26:00.022Z] TEST TEARDOWN: [2025-11-27T14:26:00.022Z] Nothing to be done for teardown. [2025-11-27T14:26:00.022Z] renaissance-movie-lens_0 Finish Time: Thu Nov 27 14:25:59 2025 Epoch Time (ms): 1764253559321