[2025-12-17T22:32:37.499Z] Running test renaissance-movie-lens_0 ... [2025-12-17T22:32:37.499Z] =============================================== [2025-12-17T22:32:37.499Z] renaissance-movie-lens_0 Start Time: Wed Dec 17 22:32:36 2025 Epoch Time (ms): 1766010756708 [2025-12-17T22:32:37.499Z] variation: NoOptions [2025-12-17T22:32:37.499Z] JVM_OPTIONS: [2025-12-17T22:32:37.499Z] { \ [2025-12-17T22:32:37.499Z] echo ""; echo "TEST SETUP:"; \ [2025-12-17T22:32:37.499Z] echo "Nothing to be done for setup."; \ [2025-12-17T22:32:37.499Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17660091562547/renaissance-movie-lens_0"; \ [2025-12-17T22:32:37.499Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17660091562547/renaissance-movie-lens_0"; \ [2025-12-17T22:32:37.499Z] echo ""; echo "TESTING:"; \ [2025-12-17T22:32:37.499Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_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_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17660091562547/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-17T22:32:37.499Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17660091562547/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-17T22:32:37.499Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-17T22:32:37.499Z] echo "Nothing to be done for teardown."; \ [2025-12-17T22:32:37.499Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17660091562547/TestTargetResult"; [2025-12-17T22:32:37.499Z] [2025-12-17T22:32:37.499Z] TEST SETUP: [2025-12-17T22:32:37.499Z] Nothing to be done for setup. [2025-12-17T22:32:37.499Z] [2025-12-17T22:32:37.499Z] TESTING: [2025-12-17T22:32:41.897Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-17T22:32:48.786Z] 22:32:48.468 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. [2025-12-17T22:32:51.227Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-17T22:32:51.993Z] Training: 60056, validation: 20285, test: 19854 [2025-12-17T22:32:51.993Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-17T22:32:51.993Z] GC before operation: completed in 119.982 ms, heap usage 163.397 MB -> 75.567 MB. [2025-12-17T22:32:58.079Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:33:02.503Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:33:06.918Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:33:09.371Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:33:11.815Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:33:13.384Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:33:14.962Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:33:16.541Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:33:16.541Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-17T22:33:16.541Z] The best model improves the baseline by 14.52%. [2025-12-17T22:33:16.541Z] Top recommended movies for user id 72: [2025-12-17T22:33:16.541Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:33:16.541Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:33:16.541Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:33:16.541Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:33:16.541Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:33:16.541Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24803.310 ms) ====== [2025-12-17T22:33:16.541Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-17T22:33:16.541Z] GC before operation: completed in 0.858 ms, heap usage 121.482 MB -> 121.634 MB. [2025-12-17T22:33:19.937Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:33:22.384Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:33:25.812Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:33:28.267Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:33:29.836Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:33:31.408Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:33:32.978Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:33:34.581Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:33:34.581Z] 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. [2025-12-17T22:33:34.581Z] The best model improves the baseline by 14.52%. [2025-12-17T22:33:34.581Z] Top recommended movies for user id 72: [2025-12-17T22:33:34.581Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:33:34.581Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:33:34.581Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:33:34.581Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:33:34.581Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:33:34.581Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17840.177 ms) ====== [2025-12-17T22:33:34.581Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-17T22:33:34.581Z] GC before operation: completed in 107.868 ms, heap usage 214.394 MB -> 94.052 MB. [2025-12-17T22:33:37.974Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:33:39.748Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:33:43.163Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:33:44.757Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:33:46.334Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:33:47.934Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:33:49.610Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:33:51.196Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:33:51.196Z] 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. [2025-12-17T22:33:51.196Z] The best model improves the baseline by 14.52%. [2025-12-17T22:33:51.196Z] Top recommended movies for user id 72: [2025-12-17T22:33:51.196Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:33:51.196Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:33:51.196Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:33:51.196Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:33:51.196Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:33:51.196Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16589.791 ms) ====== [2025-12-17T22:33:51.196Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-17T22:33:51.196Z] GC before operation: completed in 109.051 ms, heap usage 242.382 MB -> 89.073 MB. [2025-12-17T22:33:53.684Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:33:56.183Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:33:58.676Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:34:01.178Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:34:02.770Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:34:04.370Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:34:05.955Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:34:07.574Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:34:07.574Z] 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. [2025-12-17T22:34:07.574Z] The best model improves the baseline by 14.52%. [2025-12-17T22:34:07.574Z] Top recommended movies for user id 72: [2025-12-17T22:34:07.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:34:07.574Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:34:07.574Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:34:07.574Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:34:07.574Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:34:07.574Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16006.228 ms) ====== [2025-12-17T22:34:07.574Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-17T22:34:07.574Z] GC before operation: completed in 106.119 ms, heap usage 430.794 MB -> 89.751 MB. [2025-12-17T22:34:10.027Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:34:12.467Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:34:14.942Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:34:17.472Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:34:19.262Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:34:20.025Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:34:21.602Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:34:23.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:34:23.176Z] 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. [2025-12-17T22:34:23.176Z] The best model improves the baseline by 14.52%. [2025-12-17T22:34:23.176Z] Top recommended movies for user id 72: [2025-12-17T22:34:23.176Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:34:23.176Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:34:23.176Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:34:23.176Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:34:23.176Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:34:23.176Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15727.585 ms) ====== [2025-12-17T22:34:23.176Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-17T22:34:23.176Z] GC before operation: completed in 109.763 ms, heap usage 158.395 MB -> 89.378 MB. [2025-12-17T22:34:26.557Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:34:28.140Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:34:30.602Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:34:33.085Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:34:34.696Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:34:36.295Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:34:37.893Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:34:38.667Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:34:39.446Z] 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. [2025-12-17T22:34:39.446Z] The best model improves the baseline by 14.52%. [2025-12-17T22:34:39.446Z] Top recommended movies for user id 72: [2025-12-17T22:34:39.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:34:39.446Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:34:39.446Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:34:39.446Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:34:39.446Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:34:39.446Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15841.668 ms) ====== [2025-12-17T22:34:39.446Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-17T22:34:39.446Z] GC before operation: completed in 101.246 ms, heap usage 491.976 MB -> 90.194 MB. [2025-12-17T22:34:41.938Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:34:44.438Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:34:46.895Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:34:48.491Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:34:50.128Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:34:51.710Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:34:53.308Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:34:54.077Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:34:54.847Z] 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. [2025-12-17T22:34:54.847Z] The best model improves the baseline by 14.52%. [2025-12-17T22:34:54.847Z] Top recommended movies for user id 72: [2025-12-17T22:34:54.847Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:34:54.847Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:34:54.847Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:34:54.847Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:34:54.847Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:34:54.847Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15252.611 ms) ====== [2025-12-17T22:34:54.847Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-17T22:34:54.847Z] GC before operation: completed in 104.239 ms, heap usage 426.119 MB -> 90.118 MB. [2025-12-17T22:34:57.406Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:34:59.993Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:35:01.568Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:35:04.012Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:35:05.578Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:35:07.153Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:35:07.910Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:35:09.487Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:35:09.487Z] 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. [2025-12-17T22:35:09.487Z] The best model improves the baseline by 14.52%. [2025-12-17T22:35:09.487Z] Top recommended movies for user id 72: [2025-12-17T22:35:09.487Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:35:09.487Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:35:09.487Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:35:09.487Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:35:09.487Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:35:09.487Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15012.883 ms) ====== [2025-12-17T22:35:09.487Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-17T22:35:10.247Z] GC before operation: completed in 110.065 ms, heap usage 252.141 MB -> 90.125 MB. [2025-12-17T22:35:12.701Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:35:14.274Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:35:16.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:35:19.170Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:35:19.935Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:35:21.517Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:35:23.092Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:35:23.854Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:35:24.616Z] 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. [2025-12-17T22:35:24.616Z] The best model improves the baseline by 14.52%. [2025-12-17T22:35:24.616Z] Top recommended movies for user id 72: [2025-12-17T22:35:24.616Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:35:24.616Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:35:24.616Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:35:24.616Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:35:24.616Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:35:24.616Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14680.592 ms) ====== [2025-12-17T22:35:24.616Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-17T22:35:24.616Z] GC before operation: completed in 104.165 ms, heap usage 493.039 MB -> 90.189 MB. [2025-12-17T22:35:27.073Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:35:29.521Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:35:31.970Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:35:33.551Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:35:35.122Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:35:36.697Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:35:37.459Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:35:39.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:35:39.036Z] 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. [2025-12-17T22:35:39.036Z] The best model improves the baseline by 14.52%. [2025-12-17T22:35:39.794Z] Top recommended movies for user id 72: [2025-12-17T22:35:39.794Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:35:39.794Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:35:39.794Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:35:39.794Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:35:39.794Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:35:39.794Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14733.328 ms) ====== [2025-12-17T22:35:39.794Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-17T22:35:39.794Z] GC before operation: completed in 100.759 ms, heap usage 262.859 MB -> 90.113 MB. [2025-12-17T22:35:41.570Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:35:44.010Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:35:46.450Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:35:48.912Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:35:49.670Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:35:51.251Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:35:52.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:35:53.596Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:35:53.596Z] 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. [2025-12-17T22:35:54.359Z] The best model improves the baseline by 14.52%. [2025-12-17T22:35:54.359Z] Top recommended movies for user id 72: [2025-12-17T22:35:54.359Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:35:54.359Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:35:54.359Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:35:54.359Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:35:54.359Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:35:54.359Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14588.423 ms) ====== [2025-12-17T22:35:54.359Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-17T22:35:54.359Z] GC before operation: completed in 105.582 ms, heap usage 175.659 MB -> 89.723 MB. [2025-12-17T22:35:56.809Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:35:58.378Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:36:00.954Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:36:03.403Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:36:04.186Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:36:05.771Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:36:07.343Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:36:08.111Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:36:08.878Z] 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. [2025-12-17T22:36:08.878Z] The best model improves the baseline by 14.52%. [2025-12-17T22:36:08.878Z] Top recommended movies for user id 72: [2025-12-17T22:36:08.878Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:36:08.878Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:36:08.878Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:36:08.878Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:36:08.878Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:36:08.878Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14554.742 ms) ====== [2025-12-17T22:36:08.878Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-17T22:36:08.878Z] GC before operation: completed in 107.601 ms, heap usage 534.227 MB -> 93.764 MB. [2025-12-17T22:36:11.359Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:36:13.811Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:36:15.390Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:36:17.848Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:36:19.936Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:36:20.699Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:36:22.279Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:36:23.043Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:36:23.808Z] 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. [2025-12-17T22:36:23.808Z] The best model improves the baseline by 14.52%. [2025-12-17T22:36:23.808Z] Top recommended movies for user id 72: [2025-12-17T22:36:23.808Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:36:23.808Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:36:23.808Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:36:23.808Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:36:23.808Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:36:23.808Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14694.447 ms) ====== [2025-12-17T22:36:23.808Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-17T22:36:23.808Z] GC before operation: completed in 108.941 ms, heap usage 260.223 MB -> 90.261 MB. [2025-12-17T22:36:26.287Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:36:27.866Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:36:30.318Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:36:32.761Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:36:34.332Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:36:35.102Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:36:36.680Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:36:38.257Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:36:38.257Z] 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. [2025-12-17T22:36:38.257Z] The best model improves the baseline by 14.52%. [2025-12-17T22:36:38.257Z] Top recommended movies for user id 72: [2025-12-17T22:36:38.257Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:36:38.257Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:36:38.257Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:36:38.257Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:36:38.257Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:36:38.257Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14695.575 ms) ====== [2025-12-17T22:36:38.257Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-17T22:36:38.257Z] GC before operation: completed in 104.461 ms, heap usage 213.322 MB -> 91.776 MB. [2025-12-17T22:36:40.705Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:36:43.148Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:36:45.593Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:36:47.175Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:36:48.783Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:36:50.357Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:36:51.117Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:36:52.695Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:36:52.695Z] 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. [2025-12-17T22:36:52.695Z] The best model improves the baseline by 14.52%. [2025-12-17T22:36:52.695Z] Top recommended movies for user id 72: [2025-12-17T22:36:52.695Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:36:52.695Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:36:52.695Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:36:52.695Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:36:52.695Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:36:52.695Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14451.602 ms) ====== [2025-12-17T22:36:52.695Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-17T22:36:52.695Z] GC before operation: completed in 101.477 ms, heap usage 214.204 MB -> 90.109 MB. [2025-12-17T22:36:55.144Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:36:57.595Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:37:00.037Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:37:02.112Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:37:03.691Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:37:05.259Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:37:06.833Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:37:08.420Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:37:08.420Z] 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. [2025-12-17T22:37:08.420Z] The best model improves the baseline by 14.52%. [2025-12-17T22:37:08.420Z] Top recommended movies for user id 72: [2025-12-17T22:37:08.420Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:37:08.420Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:37:08.420Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:37:08.420Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:37:08.420Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:37:08.420Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15413.849 ms) ====== [2025-12-17T22:37:08.420Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-17T22:37:08.420Z] GC before operation: completed in 110.117 ms, heap usage 366.190 MB -> 90.265 MB. [2025-12-17T22:37:10.864Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:37:15.286Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:37:16.865Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:37:19.314Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:37:20.884Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:37:22.455Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:37:24.029Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:37:24.794Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:37:25.551Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-17T22:37:25.551Z] The best model improves the baseline by 14.52%. [2025-12-17T22:37:25.551Z] Top recommended movies for user id 72: [2025-12-17T22:37:25.551Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:37:25.551Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:37:25.551Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:37:25.551Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:37:25.551Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:37:25.551Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16836.201 ms) ====== [2025-12-17T22:37:25.551Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-17T22:37:25.551Z] GC before operation: completed in 105.441 ms, heap usage 271.033 MB -> 90.255 MB. [2025-12-17T22:37:27.995Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:37:30.444Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:37:32.907Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:37:34.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:37:36.099Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:37:37.670Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:37:39.242Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:37:40.815Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:37:40.815Z] 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. [2025-12-17T22:37:40.815Z] The best model improves the baseline by 14.52%. [2025-12-17T22:37:40.815Z] Top recommended movies for user id 72: [2025-12-17T22:37:40.815Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:37:40.815Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:37:40.815Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:37:40.815Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:37:40.815Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:37:40.815Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15253.555 ms) ====== [2025-12-17T22:37:40.815Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-17T22:37:40.815Z] GC before operation: completed in 109.407 ms, heap usage 247.132 MB -> 90.002 MB. [2025-12-17T22:37:43.269Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:37:45.344Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:37:47.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:37:50.239Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:37:51.817Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:37:54.257Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:37:55.827Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:37:57.444Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:37:57.444Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-17T22:37:57.444Z] The best model improves the baseline by 14.52%. [2025-12-17T22:37:58.200Z] Top recommended movies for user id 72: [2025-12-17T22:37:58.200Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:37:58.200Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:37:58.200Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:37:58.200Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:37:58.200Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:37:58.200Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16946.088 ms) ====== [2025-12-17T22:37:58.200Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-17T22:37:58.200Z] GC before operation: completed in 116.293 ms, heap usage 296.383 MB -> 90.289 MB. [2025-12-17T22:38:00.651Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T22:38:02.292Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T22:38:04.742Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T22:38:07.187Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T22:38:08.766Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T22:38:09.528Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T22:38:11.103Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T22:38:12.673Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T22:38:12.673Z] 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. [2025-12-17T22:38:12.673Z] The best model improves the baseline by 14.52%. [2025-12-17T22:38:12.673Z] Top recommended movies for user id 72: [2025-12-17T22:38:12.673Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T22:38:12.673Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T22:38:12.673Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T22:38:12.673Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T22:38:12.673Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T22:38:12.673Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14698.976 ms) ====== [2025-12-17T22:38:13.432Z] ----------------------------------- [2025-12-17T22:38:13.432Z] renaissance-movie-lens_0_PASSED [2025-12-17T22:38:13.432Z] ----------------------------------- [2025-12-17T22:38:13.432Z] [2025-12-17T22:38:13.432Z] TEST TEARDOWN: [2025-12-17T22:38:13.432Z] Nothing to be done for teardown. [2025-12-17T22:38:13.432Z] renaissance-movie-lens_0 Finish Time: Wed Dec 17 22:38:12 2025 Epoch Time (ms): 1766011092641