[2025-12-04T18:42:50.225Z] Running test renaissance-movie-lens_0 ... [2025-12-04T18:42:50.225Z] =============================================== [2025-12-04T18:42:50.225Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 18:42:49 2025 Epoch Time (ms): 1764873769599 [2025-12-04T18:42:50.225Z] variation: NoOptions [2025-12-04T18:42:50.225Z] JVM_OPTIONS: [2025-12-04T18:42:50.225Z] { \ [2025-12-04T18:42:50.225Z] echo ""; echo "TEST SETUP:"; \ [2025-12-04T18:42:50.225Z] echo "Nothing to be done for setup."; \ [2025-12-04T18:42:50.226Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_1764872091822/renaissance-movie-lens_0"; \ [2025-12-04T18:42:50.226Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_1764872091822/renaissance-movie-lens_0"; \ [2025-12-04T18:42:50.226Z] echo ""; echo "TESTING:"; \ [2025-12-04T18:42:50.226Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_1764872091822/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-04T18:42:50.226Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_1764872091822/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-04T18:42:50.226Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-04T18:42:50.226Z] echo "Nothing to be done for teardown."; \ [2025-12-04T18:42:50.226Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_1764872091822/TestTargetResult"; [2025-12-04T18:42:50.226Z] [2025-12-04T18:42:50.226Z] TEST SETUP: [2025-12-04T18:42:50.226Z] Nothing to be done for setup. [2025-12-04T18:42:50.226Z] [2025-12-04T18:42:50.226Z] TESTING: [2025-12-04T18:42:55.735Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-04T18:43:03.919Z] 18:43:02.705 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-04T18:43:05.492Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-04T18:43:06.255Z] Training: 60056, validation: 20285, test: 19854 [2025-12-04T18:43:06.255Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-04T18:43:06.255Z] GC before operation: completed in 139.937 ms, heap usage 174.778 MB -> 74.459 MB. [2025-12-04T18:43:14.468Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:43:20.074Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:43:24.483Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:43:27.865Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:43:30.298Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:43:32.773Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:43:35.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:43:37.656Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:43:37.656Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:43:37.656Z] The best model improves the baseline by 14.52%. [2025-12-04T18:43:38.411Z] Top recommended movies for user id 72: [2025-12-04T18:43:38.411Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:43:38.411Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:43:38.411Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:43:38.411Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:43:38.411Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:43:38.411Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (31703.076 ms) ====== [2025-12-04T18:43:38.411Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-04T18:43:38.411Z] GC before operation: completed in 167.113 ms, heap usage 195.715 MB -> 88.925 MB. [2025-12-04T18:43:41.793Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:43:46.192Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:43:50.927Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:43:53.621Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:43:56.052Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:43:58.482Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:44:00.913Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:44:02.483Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:44:02.483Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:44:03.242Z] The best model improves the baseline by 14.52%. [2025-12-04T18:44:03.242Z] Top recommended movies for user id 72: [2025-12-04T18:44:03.242Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:44:03.242Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:44:03.242Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:44:03.242Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:44:03.242Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:44:03.242Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24715.653 ms) ====== [2025-12-04T18:44:03.242Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-04T18:44:03.242Z] GC before operation: completed in 182.488 ms, heap usage 167.818 MB -> 87.428 MB. [2025-12-04T18:44:06.606Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:44:09.980Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:44:14.380Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:44:16.850Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:44:19.324Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:44:21.751Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:44:24.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:44:25.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:44:25.752Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:44:25.752Z] The best model improves the baseline by 14.52%. [2025-12-04T18:44:26.511Z] Top recommended movies for user id 72: [2025-12-04T18:44:26.511Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:44:26.511Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:44:26.511Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:44:26.511Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:44:26.511Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:44:26.511Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23041.303 ms) ====== [2025-12-04T18:44:26.511Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-04T18:44:26.511Z] GC before operation: completed in 150.379 ms, heap usage 297.668 MB -> 88.209 MB. [2025-12-04T18:44:29.886Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:44:33.272Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:44:36.707Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:44:40.095Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:44:42.525Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:44:44.961Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:44:46.544Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:44:48.984Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:44:48.984Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:44:48.984Z] The best model improves the baseline by 14.52%. [2025-12-04T18:44:48.984Z] Top recommended movies for user id 72: [2025-12-04T18:44:48.984Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:44:48.984Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:44:48.984Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:44:48.984Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:44:48.984Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:44:48.984Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22754.544 ms) ====== [2025-12-04T18:44:48.984Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-04T18:44:48.984Z] GC before operation: completed in 152.156 ms, heap usage 264.959 MB -> 88.455 MB. [2025-12-04T18:44:52.360Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:44:55.852Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:44:59.778Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:45:03.153Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:45:04.709Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:45:07.203Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:45:09.626Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:45:11.191Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:45:11.191Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:45:11.191Z] The best model improves the baseline by 14.52%. [2025-12-04T18:45:11.944Z] Top recommended movies for user id 72: [2025-12-04T18:45:11.945Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:45:11.945Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:45:11.945Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:45:11.945Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:45:11.945Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:45:11.945Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22350.377 ms) ====== [2025-12-04T18:45:11.945Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-04T18:45:11.945Z] GC before operation: completed in 152.743 ms, heap usage 178.724 MB -> 88.281 MB. [2025-12-04T18:45:15.317Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:45:18.711Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:45:22.079Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:45:25.446Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:45:27.014Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:45:29.446Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:45:31.886Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:45:33.449Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:45:33.449Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:45:33.449Z] The best model improves the baseline by 14.52%. [2025-12-04T18:45:34.207Z] Top recommended movies for user id 72: [2025-12-04T18:45:34.207Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:45:34.207Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:45:34.207Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:45:34.207Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:45:34.207Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:45:34.207Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (22090.062 ms) ====== [2025-12-04T18:45:34.207Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-04T18:45:34.207Z] GC before operation: completed in 161.420 ms, heap usage 238.688 MB -> 88.644 MB. [2025-12-04T18:45:37.589Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:45:40.978Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:45:44.378Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:45:46.816Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:45:49.262Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:45:50.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:45:53.345Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:45:54.911Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:45:55.675Z] 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. [2025-12-04T18:45:55.675Z] The best model improves the baseline by 14.52%. [2025-12-04T18:45:55.675Z] Top recommended movies for user id 72: [2025-12-04T18:45:55.675Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:45:55.675Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:45:55.675Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:45:55.675Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:45:55.675Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:45:55.675Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21427.662 ms) ====== [2025-12-04T18:45:55.675Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-04T18:45:55.675Z] GC before operation: completed in 151.833 ms, heap usage 279.114 MB -> 88.645 MB. [2025-12-04T18:45:59.057Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:46:02.433Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:46:05.382Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:46:08.781Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:46:10.356Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:46:12.847Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:46:14.429Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:46:17.005Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:46:17.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:46:17.005Z] The best model improves the baseline by 14.52%. [2025-12-04T18:46:17.005Z] Top recommended movies for user id 72: [2025-12-04T18:46:17.005Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:46:17.005Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:46:17.005Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:46:17.005Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:46:17.005Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:46:17.005Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21308.065 ms) ====== [2025-12-04T18:46:17.005Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-04T18:46:17.005Z] GC before operation: completed in 144.113 ms, heap usage 230.209 MB -> 88.765 MB. [2025-12-04T18:46:20.390Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:46:23.784Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:46:26.227Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:46:29.602Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:46:31.180Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:46:32.749Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:46:35.191Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:46:36.766Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:46:37.532Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:46:37.532Z] The best model improves the baseline by 14.52%. [2025-12-04T18:46:37.532Z] Top recommended movies for user id 72: [2025-12-04T18:46:37.532Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:46:37.532Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:46:37.532Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:46:37.532Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:46:37.532Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:46:37.532Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20268.874 ms) ====== [2025-12-04T18:46:37.532Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-04T18:46:37.532Z] GC before operation: completed in 150.889 ms, heap usage 214.019 MB -> 88.620 MB. [2025-12-04T18:46:40.926Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:46:44.320Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:46:46.764Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:46:50.147Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:46:52.582Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:46:54.153Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:46:56.594Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:46:58.167Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:46:58.928Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:46:58.928Z] The best model improves the baseline by 14.52%. [2025-12-04T18:46:58.928Z] Top recommended movies for user id 72: [2025-12-04T18:46:58.928Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:46:58.928Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:46:58.928Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:46:58.928Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:46:58.928Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:46:58.928Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21281.401 ms) ====== [2025-12-04T18:46:58.928Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-04T18:46:58.928Z] GC before operation: completed in 144.326 ms, heap usage 257.367 MB -> 88.939 MB. [2025-12-04T18:47:02.356Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:47:05.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:47:09.130Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:47:11.586Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:47:13.679Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:47:15.250Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:47:17.688Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:47:19.266Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:47:20.027Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:47:20.027Z] The best model improves the baseline by 14.52%. [2025-12-04T18:47:20.027Z] Top recommended movies for user id 72: [2025-12-04T18:47:20.027Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:47:20.027Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:47:20.027Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:47:20.027Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:47:20.027Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:47:20.027Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20995.406 ms) ====== [2025-12-04T18:47:20.027Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-04T18:47:20.027Z] GC before operation: completed in 143.196 ms, heap usage 279.304 MB -> 88.672 MB. [2025-12-04T18:47:23.409Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:47:26.790Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:47:30.186Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:47:33.576Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:47:35.166Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:47:36.855Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:47:39.303Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:47:40.875Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:47:40.875Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:47:40.875Z] The best model improves the baseline by 14.52%. [2025-12-04T18:47:41.633Z] Top recommended movies for user id 72: [2025-12-04T18:47:41.633Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:47:41.633Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:47:41.633Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:47:41.633Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:47:41.633Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:47:41.633Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (21283.873 ms) ====== [2025-12-04T18:47:41.633Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-04T18:47:41.633Z] GC before operation: completed in 151.374 ms, heap usage 239.623 MB -> 88.803 MB. [2025-12-04T18:47:45.016Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:47:47.474Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:47:50.867Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:47:54.385Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:47:55.950Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:47:57.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:47:59.970Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:48:01.670Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:48:01.670Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:48:01.670Z] The best model improves the baseline by 14.52%. [2025-12-04T18:48:01.670Z] Top recommended movies for user id 72: [2025-12-04T18:48:01.670Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:48:01.670Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:48:01.670Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:48:01.670Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:48:01.670Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:48:01.670Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20437.338 ms) ====== [2025-12-04T18:48:01.670Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-04T18:48:02.427Z] GC before operation: completed in 146.777 ms, heap usage 340.001 MB -> 89.053 MB. [2025-12-04T18:48:08.688Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:48:08.688Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:48:12.076Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:48:15.469Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:48:17.041Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:48:18.617Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:48:21.069Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:48:22.639Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:48:22.639Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:48:23.398Z] The best model improves the baseline by 14.52%. [2025-12-04T18:48:23.398Z] Top recommended movies for user id 72: [2025-12-04T18:48:23.398Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:48:23.398Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:48:23.398Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:48:23.398Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:48:23.398Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:48:23.398Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (21040.544 ms) ====== [2025-12-04T18:48:23.398Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-04T18:48:23.398Z] GC before operation: completed in 144.874 ms, heap usage 178.035 MB -> 88.725 MB. [2025-12-04T18:48:26.792Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:48:29.236Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:48:32.613Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:48:36.011Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:48:37.579Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:48:40.021Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:48:41.598Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:48:43.170Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:48:43.966Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:48:43.966Z] The best model improves the baseline by 14.52%. [2025-12-04T18:48:43.966Z] Top recommended movies for user id 72: [2025-12-04T18:48:43.966Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:48:43.966Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:48:43.966Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:48:43.966Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:48:43.966Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:48:43.966Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20464.600 ms) ====== [2025-12-04T18:48:43.966Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-04T18:48:43.966Z] GC before operation: completed in 137.360 ms, heap usage 124.671 MB -> 88.862 MB. [2025-12-04T18:48:47.347Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:48:50.301Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:48:53.692Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:48:56.145Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:48:58.613Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:49:00.187Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:49:01.768Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:49:04.218Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:49:04.218Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:49:04.218Z] The best model improves the baseline by 14.52%. [2025-12-04T18:49:04.218Z] Top recommended movies for user id 72: [2025-12-04T18:49:04.218Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:49:04.218Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:49:04.218Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:49:04.218Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:49:04.218Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:49:04.218Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20419.282 ms) ====== [2025-12-04T18:49:04.218Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-04T18:49:04.218Z] GC before operation: completed in 148.081 ms, heap usage 120.438 MB -> 88.715 MB. [2025-12-04T18:49:07.639Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:49:11.026Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:49:14.442Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:49:17.056Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:49:19.655Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:49:21.300Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:49:22.953Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:49:24.599Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:49:25.396Z] 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. [2025-12-04T18:49:25.396Z] The best model improves the baseline by 14.52%. [2025-12-04T18:49:25.396Z] Top recommended movies for user id 72: [2025-12-04T18:49:25.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:49:25.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:49:25.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:49:25.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:49:25.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:49:25.396Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20767.236 ms) ====== [2025-12-04T18:49:25.396Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-04T18:49:25.396Z] GC before operation: completed in 138.442 ms, heap usage 278.765 MB -> 88.957 MB. [2025-12-04T18:49:28.943Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:49:31.502Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:49:35.159Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:49:38.701Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:49:40.347Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:49:41.995Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:49:43.640Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:49:46.208Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:49:46.208Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:49:46.208Z] The best model improves the baseline by 14.52%. [2025-12-04T18:49:46.208Z] Top recommended movies for user id 72: [2025-12-04T18:49:46.208Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:49:46.208Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:49:46.208Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:49:46.208Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:49:46.208Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:49:46.208Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20738.018 ms) ====== [2025-12-04T18:49:46.208Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-04T18:49:46.208Z] GC before operation: completed in 141.657 ms, heap usage 213.807 MB -> 88.685 MB. [2025-12-04T18:49:49.752Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:49:52.313Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:49:55.982Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:49:59.529Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:50:01.181Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:50:02.840Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:50:05.393Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:50:07.046Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:50:07.046Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:50:07.046Z] The best model improves the baseline by 14.52%. [2025-12-04T18:50:07.046Z] Top recommended movies for user id 72: [2025-12-04T18:50:07.046Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:50:07.046Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:50:07.046Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:50:07.046Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:50:07.046Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:50:07.046Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (21025.079 ms) ====== [2025-12-04T18:50:07.046Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-04T18:50:07.841Z] GC before operation: completed in 141.260 ms, heap usage 370.363 MB -> 89.052 MB. [2025-12-04T18:50:10.397Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T18:50:13.940Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T18:50:17.592Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T18:50:20.153Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T18:50:22.719Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T18:50:24.905Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T18:50:26.550Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T18:50:28.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T18:50:28.203Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T18:50:28.203Z] The best model improves the baseline by 14.52%. [2025-12-04T18:50:29.041Z] Top recommended movies for user id 72: [2025-12-04T18:50:29.041Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T18:50:29.041Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T18:50:29.041Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T18:50:29.041Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T18:50:29.041Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T18:50:29.041Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (21129.854 ms) ====== [2025-12-04T18:50:29.041Z] ----------------------------------- [2025-12-04T18:50:29.041Z] renaissance-movie-lens_0_PASSED [2025-12-04T18:50:29.041Z] ----------------------------------- [2025-12-04T18:50:29.041Z] [2025-12-04T18:50:29.041Z] TEST TEARDOWN: [2025-12-04T18:50:29.041Z] Nothing to be done for teardown. [2025-12-04T18:50:29.041Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 18:50:28 2025 Epoch Time (ms): 1764874228679