[2025-09-25T00:49:30.500Z] Running test renaissance-movie-lens_0 ... [2025-09-25T00:49:30.500Z] =============================================== [2025-09-25T00:49:30.500Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 00:49:29 2025 Epoch Time (ms): 1758761369954 [2025-09-25T00:49:30.500Z] variation: NoOptions [2025-09-25T00:49:30.500Z] JVM_OPTIONS: [2025-09-25T00:49:30.500Z] { \ [2025-09-25T00:49:30.500Z] echo ""; echo "TEST SETUP:"; \ [2025-09-25T00:49:30.500Z] echo "Nothing to be done for setup."; \ [2025-09-25T00:49:30.500Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17587599761548/renaissance-movie-lens_0"; \ [2025-09-25T00:49:30.500Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17587599761548/renaissance-movie-lens_0"; \ [2025-09-25T00:49:30.500Z] echo ""; echo "TESTING:"; \ [2025-09-25T00:49:30.500Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17587599761548/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-25T00:49:30.500Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17587599761548/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-25T00:49:30.500Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-25T00:49:30.500Z] echo "Nothing to be done for teardown."; \ [2025-09-25T00:49:30.500Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17587599761548/TestTargetResult"; [2025-09-25T00:49:30.500Z] [2025-09-25T00:49:30.500Z] TEST SETUP: [2025-09-25T00:49:30.500Z] Nothing to be done for setup. [2025-09-25T00:49:30.500Z] [2025-09-25T00:49:30.500Z] TESTING: [2025-09-25T00:49:37.092Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-25T00:49:45.159Z] 00:49:44.090 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. [2025-09-25T00:49:47.127Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-25T00:49:47.127Z] Training: 60056, validation: 20285, test: 19854 [2025-09-25T00:49:47.127Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-25T00:49:47.127Z] GC before operation: completed in 105.775 ms, heap usage 381.617 MB -> 75.949 MB. [2025-09-25T00:49:53.741Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:49:57.830Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:50:01.939Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:50:05.351Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:50:07.279Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:50:09.214Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:50:11.136Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:50:13.062Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:50:13.062Z] 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. [2025-09-25T00:50:13.062Z] The best model improves the baseline by 14.52%. [2025-09-25T00:50:13.062Z] Top recommended movies for user id 72: [2025-09-25T00:50:13.062Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:50:13.062Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:50:13.062Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:50:13.062Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:50:13.062Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:50:13.062Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25677.154 ms) ====== [2025-09-25T00:50:13.062Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-25T00:50:13.062Z] GC before operation: completed in 165.926 ms, heap usage 390.890 MB -> 93.565 MB. [2025-09-25T00:50:16.025Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:50:19.001Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:50:21.967Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:50:24.938Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:50:25.873Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:50:27.793Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:50:28.734Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:50:30.655Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:50:30.655Z] 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. [2025-09-25T00:50:30.655Z] The best model improves the baseline by 14.52%. [2025-09-25T00:50:30.655Z] Top recommended movies for user id 72: [2025-09-25T00:50:30.655Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:50:30.655Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:50:30.655Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:50:30.655Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:50:30.655Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:50:30.655Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17460.176 ms) ====== [2025-09-25T00:50:30.655Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-25T00:50:30.655Z] GC before operation: completed in 154.418 ms, heap usage 515.157 MB -> 89.071 MB. [2025-09-25T00:50:33.618Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:50:36.626Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:50:38.547Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:50:41.518Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:50:42.454Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:50:44.376Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:50:45.313Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:50:47.232Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:50:47.232Z] 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. [2025-09-25T00:50:47.232Z] The best model improves the baseline by 14.52%. [2025-09-25T00:50:47.232Z] Top recommended movies for user id 72: [2025-09-25T00:50:47.232Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:50:47.232Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:50:47.232Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:50:47.232Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:50:47.232Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:50:47.232Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16464.113 ms) ====== [2025-09-25T00:50:47.232Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-25T00:50:47.232Z] GC before operation: completed in 158.713 ms, heap usage 100.321 MB -> 91.787 MB. [2025-09-25T00:50:50.659Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:50:52.582Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:50:55.550Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:50:57.469Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:50:59.388Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:51:01.310Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:51:02.250Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:51:04.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:51:04.176Z] 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. [2025-09-25T00:51:04.176Z] The best model improves the baseline by 14.52%. [2025-09-25T00:51:04.176Z] Top recommended movies for user id 72: [2025-09-25T00:51:04.176Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:51:04.176Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:51:04.176Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:51:04.176Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:51:04.176Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:51:04.176Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16529.856 ms) ====== [2025-09-25T00:51:04.176Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-25T00:51:04.176Z] GC before operation: completed in 136.462 ms, heap usage 253.519 MB -> 89.753 MB. [2025-09-25T00:51:07.260Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:51:09.183Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:51:12.152Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:51:14.069Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:51:15.996Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:51:16.932Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:51:18.854Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:51:20.949Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:51:20.949Z] 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. [2025-09-25T00:51:20.949Z] The best model improves the baseline by 14.52%. [2025-09-25T00:51:20.949Z] Top recommended movies for user id 72: [2025-09-25T00:51:20.949Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:51:20.949Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:51:20.949Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:51:20.949Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:51:20.949Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:51:20.949Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16915.283 ms) ====== [2025-09-25T00:51:20.949Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-25T00:51:20.949Z] GC before operation: completed in 154.319 ms, heap usage 264.196 MB -> 89.724 MB. [2025-09-25T00:51:25.035Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:51:28.017Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:51:30.983Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:51:35.855Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:51:36.789Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:51:38.717Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:51:41.005Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:51:42.946Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:51:42.946Z] 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. [2025-09-25T00:51:42.946Z] The best model improves the baseline by 14.52%. [2025-09-25T00:51:42.946Z] Top recommended movies for user id 72: [2025-09-25T00:51:42.946Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:51:42.946Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:51:42.946Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:51:42.946Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:51:42.946Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:51:42.946Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (21958.425 ms) ====== [2025-09-25T00:51:42.946Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-25T00:51:43.883Z] GC before operation: completed in 166.841 ms, heap usage 495.714 MB -> 90.382 MB. [2025-09-25T00:51:46.857Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:51:49.827Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:51:53.921Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:51:58.047Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:51:59.979Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:52:01.904Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:52:03.827Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:52:06.827Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:52:06.827Z] 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. [2025-09-25T00:52:06.827Z] The best model improves the baseline by 14.52%. [2025-09-25T00:52:06.827Z] Top recommended movies for user id 72: [2025-09-25T00:52:06.827Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:52:06.827Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:52:06.827Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:52:06.827Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:52:06.827Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:52:06.827Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23282.072 ms) ====== [2025-09-25T00:52:06.827Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-25T00:52:06.828Z] GC before operation: completed in 149.920 ms, heap usage 220.476 MB -> 90.007 MB. [2025-09-25T00:52:09.824Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:52:13.920Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:52:16.886Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:52:21.653Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:52:23.584Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:52:25.503Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:52:27.432Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:52:29.354Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:52:29.354Z] 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. [2025-09-25T00:52:29.354Z] The best model improves the baseline by 14.52%. [2025-09-25T00:52:29.354Z] Top recommended movies for user id 72: [2025-09-25T00:52:29.354Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:52:29.354Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:52:29.354Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:52:29.354Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:52:29.354Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:52:29.354Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22609.583 ms) ====== [2025-09-25T00:52:29.354Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-25T00:52:29.354Z] GC before operation: completed in 164.382 ms, heap usage 243.472 MB -> 90.139 MB. [2025-09-25T00:52:33.445Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:52:36.440Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:52:39.436Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:52:43.555Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:52:45.494Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:52:46.434Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:52:48.364Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:52:49.302Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:52:49.302Z] 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. [2025-09-25T00:52:49.302Z] The best model improves the baseline by 14.52%. [2025-09-25T00:52:49.302Z] Top recommended movies for user id 72: [2025-09-25T00:52:49.302Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:52:49.302Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:52:49.302Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:52:49.302Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:52:49.302Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:52:49.302Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19914.256 ms) ====== [2025-09-25T00:52:49.302Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-25T00:52:49.302Z] GC before operation: completed in 149.714 ms, heap usage 237.272 MB -> 90.060 MB. [2025-09-25T00:52:52.307Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:52:54.230Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:52:58.318Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:53:01.302Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:53:03.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:53:05.138Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:53:07.907Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:53:09.879Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:53:09.879Z] 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. [2025-09-25T00:53:09.879Z] The best model improves the baseline by 14.52%. [2025-09-25T00:53:10.818Z] Top recommended movies for user id 72: [2025-09-25T00:53:10.818Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:53:10.818Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:53:10.818Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:53:10.818Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:53:10.818Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:53:10.818Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20633.191 ms) ====== [2025-09-25T00:53:10.818Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-25T00:53:10.818Z] GC before operation: completed in 173.542 ms, heap usage 186.248 MB -> 90.242 MB. [2025-09-25T00:53:13.781Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:53:16.750Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:53:20.866Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:53:23.833Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:53:26.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:53:28.740Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:53:30.668Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:53:32.595Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:53:32.595Z] 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. [2025-09-25T00:53:32.595Z] The best model improves the baseline by 14.52%. [2025-09-25T00:53:32.595Z] Top recommended movies for user id 72: [2025-09-25T00:53:32.595Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:53:32.595Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:53:32.595Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:53:32.595Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:53:32.595Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:53:32.595Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (22345.497 ms) ====== [2025-09-25T00:53:32.595Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-25T00:53:32.595Z] GC before operation: completed in 153.926 ms, heap usage 182.305 MB -> 90.018 MB. [2025-09-25T00:53:36.743Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:53:39.716Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:53:43.805Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:53:46.786Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:53:48.719Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:53:50.650Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:53:52.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:53:54.495Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:53:55.431Z] 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. [2025-09-25T00:53:55.431Z] The best model improves the baseline by 14.52%. [2025-09-25T00:53:55.431Z] Top recommended movies for user id 72: [2025-09-25T00:53:55.431Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:53:55.431Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:53:55.431Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:53:55.431Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:53:55.431Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:53:55.431Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22325.100 ms) ====== [2025-09-25T00:53:55.431Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-25T00:53:55.431Z] GC before operation: completed in 175.217 ms, heap usage 312.450 MB -> 90.341 MB. [2025-09-25T00:54:00.231Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:54:02.151Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:54:06.249Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:54:09.319Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:54:11.243Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:54:13.170Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:54:15.088Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:54:17.011Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:54:17.011Z] 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. [2025-09-25T00:54:17.011Z] The best model improves the baseline by 14.52%. [2025-09-25T00:54:17.011Z] Top recommended movies for user id 72: [2025-09-25T00:54:17.011Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:54:17.011Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:54:17.011Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:54:17.011Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:54:17.011Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:54:17.011Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (21820.393 ms) ====== [2025-09-25T00:54:17.011Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-25T00:54:17.945Z] GC before operation: completed in 154.710 ms, heap usage 138.898 MB -> 90.291 MB. [2025-09-25T00:54:20.921Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:54:23.893Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:54:26.962Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:54:31.063Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:54:33.003Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:54:35.976Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:54:37.901Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:54:40.947Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:54:40.947Z] 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. [2025-09-25T00:54:40.947Z] The best model improves the baseline by 14.52%. [2025-09-25T00:54:40.947Z] Top recommended movies for user id 72: [2025-09-25T00:54:40.947Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:54:40.947Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:54:40.947Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:54:40.947Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:54:40.947Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:54:40.947Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (23803.262 ms) ====== [2025-09-25T00:54:40.947Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-25T00:54:41.986Z] GC before operation: completed in 204.569 ms, heap usage 123.279 MB -> 90.002 MB. [2025-09-25T00:54:46.609Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:54:49.571Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:54:53.660Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:54:57.761Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:54:59.691Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:55:01.618Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:55:04.585Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:55:06.505Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:55:06.505Z] 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. [2025-09-25T00:55:06.505Z] The best model improves the baseline by 14.52%. [2025-09-25T00:55:06.505Z] Top recommended movies for user id 72: [2025-09-25T00:55:06.505Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:55:06.505Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:55:06.505Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:55:06.505Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:55:06.505Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:55:06.505Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (25326.696 ms) ====== [2025-09-25T00:55:06.505Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-25T00:55:07.610Z] GC before operation: completed in 160.127 ms, heap usage 166.350 MB -> 90.438 MB. [2025-09-25T00:55:10.578Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:55:13.544Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:55:16.514Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:55:20.591Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:55:22.509Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:55:24.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:55:27.409Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:55:29.339Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:55:29.339Z] 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. [2025-09-25T00:55:29.339Z] The best model improves the baseline by 14.52%. [2025-09-25T00:55:29.339Z] Top recommended movies for user id 72: [2025-09-25T00:55:29.339Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:55:29.339Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:55:29.339Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:55:29.339Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:55:29.339Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:55:29.339Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (22486.880 ms) ====== [2025-09-25T00:55:29.339Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-25T00:55:29.339Z] GC before operation: completed in 213.866 ms, heap usage 181.056 MB -> 90.143 MB. [2025-09-25T00:55:32.984Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:55:37.067Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:55:40.032Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:55:43.008Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:55:44.931Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:55:47.896Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:55:49.817Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:55:51.758Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:55:51.758Z] 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. [2025-09-25T00:55:51.758Z] The best model improves the baseline by 14.52%. [2025-09-25T00:55:51.758Z] Top recommended movies for user id 72: [2025-09-25T00:55:51.758Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:55:51.758Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:55:51.758Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:55:51.758Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:55:51.758Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:55:51.758Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (22237.479 ms) ====== [2025-09-25T00:55:51.758Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-25T00:55:51.758Z] GC before operation: completed in 193.463 ms, heap usage 377.290 MB -> 90.498 MB. [2025-09-25T00:55:55.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:55:58.801Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:56:02.896Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:56:05.881Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:56:08.850Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:56:10.820Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:56:12.742Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:56:14.660Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:56:14.660Z] 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. [2025-09-25T00:56:14.660Z] The best model improves the baseline by 14.52%. [2025-09-25T00:56:14.660Z] Top recommended movies for user id 72: [2025-09-25T00:56:14.660Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:56:14.660Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:56:14.660Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:56:14.660Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:56:14.660Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:56:14.660Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (22763.517 ms) ====== [2025-09-25T00:56:14.660Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-25T00:56:14.660Z] GC before operation: completed in 163.936 ms, heap usage 228.531 MB -> 90.131 MB. [2025-09-25T00:56:19.538Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:56:20.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:56:22.574Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:56:24.494Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:56:26.412Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:56:27.350Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:56:29.273Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:56:30.211Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:56:30.211Z] 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. [2025-09-25T00:56:31.149Z] The best model improves the baseline by 14.52%. [2025-09-25T00:56:31.149Z] Top recommended movies for user id 72: [2025-09-25T00:56:31.149Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:56:31.149Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:56:31.149Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:56:31.149Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:56:31.149Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:56:31.149Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15703.952 ms) ====== [2025-09-25T00:56:31.149Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-25T00:56:31.149Z] GC before operation: completed in 122.427 ms, heap usage 414.415 MB -> 90.566 MB. [2025-09-25T00:56:33.075Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:56:36.045Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:56:37.968Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:56:40.953Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:56:41.886Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:56:42.821Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:56:44.742Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:56:46.668Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:56:46.668Z] 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. [2025-09-25T00:56:46.668Z] The best model improves the baseline by 14.52%. [2025-09-25T00:56:46.668Z] Top recommended movies for user id 72: [2025-09-25T00:56:46.668Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:56:46.668Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:56:46.668Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:56:46.668Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:56:46.668Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:56:46.668Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15658.554 ms) ====== [2025-09-25T00:56:47.602Z] ----------------------------------- [2025-09-25T00:56:47.602Z] renaissance-movie-lens_0_PASSED [2025-09-25T00:56:47.602Z] ----------------------------------- [2025-09-25T00:56:47.602Z] [2025-09-25T00:56:47.602Z] TEST TEARDOWN: [2025-09-25T00:56:47.602Z] Nothing to be done for teardown. [2025-09-25T00:56:47.602Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 00:56:46 2025 Epoch Time (ms): 1758761806776