[2025-12-11T23:54:46.329Z] Running test renaissance-movie-lens_0 ... [2025-12-11T23:54:46.329Z] =============================================== [2025-12-11T23:54:46.329Z] renaissance-movie-lens_0 Start Time: Thu Dec 11 23:54:46 2025 Epoch Time (ms): 1765497286126 [2025-12-11T23:54:46.329Z] variation: NoOptions [2025-12-11T23:54:46.329Z] JVM_OPTIONS: [2025-12-11T23:54:46.329Z] { \ [2025-12-11T23:54:46.329Z] echo ""; echo "TEST SETUP:"; \ [2025-12-11T23:54:46.329Z] echo "Nothing to be done for setup."; \ [2025-12-11T23:54:46.329Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17654952482575/renaissance-movie-lens_0"; \ [2025-12-11T23:54:46.329Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17654952482575/renaissance-movie-lens_0"; \ [2025-12-11T23:54:46.329Z] echo ""; echo "TESTING:"; \ [2025-12-11T23:54:46.329Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_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_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17654952482575/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-11T23:54:46.329Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17654952482575/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-11T23:54:46.329Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-11T23:54:46.329Z] echo "Nothing to be done for teardown."; \ [2025-12-11T23:54:46.329Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17654952482575/TestTargetResult"; [2025-12-11T23:54:46.329Z] [2025-12-11T23:54:46.329Z] TEST SETUP: [2025-12-11T23:54:46.329Z] Nothing to be done for setup. [2025-12-11T23:54:46.329Z] [2025-12-11T23:54:46.329Z] TESTING: [2025-12-11T23:54:51.037Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-11T23:54:58.179Z] 23:54:57.991 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-12-11T23:55:01.873Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-11T23:55:01.873Z] Training: 60056, validation: 20285, test: 19854 [2025-12-11T23:55:01.873Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-11T23:55:02.190Z] GC before operation: completed in 139.197 ms, heap usage 356.979 MB -> 75.874 MB. [2025-12-11T23:55:09.404Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:55:14.055Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:55:18.702Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:55:22.377Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:55:24.554Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:55:26.733Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:55:28.332Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:55:30.523Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:55:30.523Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:55:30.523Z] The best model improves the baseline by 14.34%. [2025-12-11T23:55:30.836Z] Top recommended movies for user id 72: [2025-12-11T23:55:30.836Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:55:30.836Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:55:30.836Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:55:30.836Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:55:30.836Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:55:30.836Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28802.286 ms) ====== [2025-12-11T23:55:30.836Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-11T23:55:31.161Z] GC before operation: completed in 148.978 ms, heap usage 171.357 MB -> 95.820 MB. [2025-12-11T23:55:34.099Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:55:36.972Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:55:39.840Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:55:42.028Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:55:43.657Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:55:45.253Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:55:46.863Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:55:48.462Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:55:48.775Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:55:48.775Z] The best model improves the baseline by 14.34%. [2025-12-11T23:55:48.775Z] Top recommended movies for user id 72: [2025-12-11T23:55:48.775Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:55:48.775Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:55:48.775Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:55:48.775Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:55:48.775Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:55:48.775Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17798.851 ms) ====== [2025-12-11T23:55:48.775Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-11T23:55:49.093Z] GC before operation: completed in 131.357 ms, heap usage 354.611 MB -> 88.110 MB. [2025-12-11T23:55:52.038Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:55:54.222Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:55:57.170Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:55:59.351Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:56:00.949Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:56:02.553Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:56:04.151Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:56:05.750Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:56:06.068Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:56:06.068Z] The best model improves the baseline by 14.34%. [2025-12-11T23:56:06.068Z] Top recommended movies for user id 72: [2025-12-11T23:56:06.068Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:56:06.068Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:56:06.068Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:56:06.068Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:56:06.068Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:56:06.068Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17121.974 ms) ====== [2025-12-11T23:56:06.068Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-11T23:56:06.382Z] GC before operation: completed in 135.856 ms, heap usage 446.592 MB -> 92.073 MB. [2025-12-11T23:56:08.566Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:56:10.746Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:56:13.616Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:56:15.816Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:56:16.922Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:56:18.025Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:56:19.621Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:56:20.718Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:56:21.036Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:56:21.036Z] The best model improves the baseline by 14.34%. [2025-12-11T23:56:21.350Z] Top recommended movies for user id 72: [2025-12-11T23:56:21.350Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:56:21.350Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:56:21.350Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:56:21.350Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:56:21.350Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:56:21.350Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14949.526 ms) ====== [2025-12-11T23:56:21.350Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-11T23:56:21.350Z] GC before operation: completed in 136.162 ms, heap usage 236.916 MB -> 88.742 MB. [2025-12-11T23:56:24.215Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:56:25.817Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:56:28.687Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:56:30.283Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:56:31.879Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:56:32.982Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:56:34.581Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:56:35.748Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:56:36.064Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:56:36.064Z] The best model improves the baseline by 14.34%. [2025-12-11T23:56:36.064Z] Top recommended movies for user id 72: [2025-12-11T23:56:36.064Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:56:36.064Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:56:36.064Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:56:36.064Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:56:36.064Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:56:36.064Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14723.350 ms) ====== [2025-12-11T23:56:36.064Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-11T23:56:36.064Z] GC before operation: completed in 141.875 ms, heap usage 435.444 MB -> 89.099 MB. [2025-12-11T23:56:38.241Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:56:40.429Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:56:43.292Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:56:44.882Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:56:45.984Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:56:47.573Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:56:49.174Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:56:50.273Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:56:50.273Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:56:50.273Z] The best model improves the baseline by 14.34%. [2025-12-11T23:56:50.587Z] Top recommended movies for user id 72: [2025-12-11T23:56:50.587Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:56:50.587Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:56:50.587Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:56:50.587Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:56:50.587Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:56:50.587Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14297.559 ms) ====== [2025-12-11T23:56:50.587Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-11T23:56:50.587Z] GC before operation: completed in 136.146 ms, heap usage 115.530 MB -> 92.661 MB. [2025-12-11T23:56:52.766Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:56:54.945Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:56:57.190Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:56:59.377Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:57:00.976Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:57:02.079Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:57:03.180Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:57:04.282Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:57:04.597Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:57:04.597Z] The best model improves the baseline by 14.34%. [2025-12-11T23:57:04.910Z] Top recommended movies for user id 72: [2025-12-11T23:57:04.910Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:57:04.910Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:57:04.910Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:57:04.910Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:57:04.910Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:57:04.910Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14174.936 ms) ====== [2025-12-11T23:57:04.910Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-11T23:57:04.910Z] GC before operation: completed in 150.602 ms, heap usage 637.410 MB -> 93.005 MB. [2025-12-11T23:57:07.111Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:57:09.290Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:57:11.473Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:57:13.077Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:57:14.672Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:57:16.272Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:57:17.451Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:57:19.044Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:57:19.044Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:57:19.044Z] The best model improves the baseline by 14.34%. [2025-12-11T23:57:19.361Z] Top recommended movies for user id 72: [2025-12-11T23:57:19.361Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:57:19.361Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:57:19.361Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:57:19.361Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:57:19.361Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:57:19.361Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14265.747 ms) ====== [2025-12-11T23:57:19.361Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-11T23:57:19.361Z] GC before operation: completed in 145.474 ms, heap usage 503.790 MB -> 92.974 MB. [2025-12-11T23:57:21.551Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:57:23.734Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:57:25.914Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:57:28.101Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:57:28.774Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:57:30.370Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:57:31.472Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:57:32.573Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:57:32.573Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:57:32.886Z] The best model improves the baseline by 14.34%. [2025-12-11T23:57:32.886Z] Top recommended movies for user id 72: [2025-12-11T23:57:32.886Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:57:32.886Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:57:32.886Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:57:32.886Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:57:32.886Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:57:32.886Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13562.728 ms) ====== [2025-12-11T23:57:32.886Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-11T23:57:33.201Z] GC before operation: completed in 144.819 ms, heap usage 229.067 MB -> 89.092 MB. [2025-12-11T23:57:35.377Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:57:36.976Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:57:39.188Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:57:41.366Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:57:42.467Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:57:43.567Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:57:44.667Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:57:46.265Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:57:46.265Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:57:46.265Z] The best model improves the baseline by 14.34%. [2025-12-11T23:57:46.265Z] Top recommended movies for user id 72: [2025-12-11T23:57:46.265Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:57:46.265Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:57:46.265Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:57:46.265Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:57:46.265Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:57:46.265Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13305.451 ms) ====== [2025-12-11T23:57:46.265Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-11T23:57:46.583Z] GC before operation: completed in 134.105 ms, heap usage 115.217 MB -> 92.223 MB. [2025-12-11T23:57:48.763Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:57:51.001Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:57:53.184Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:57:54.785Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:57:55.889Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:57:57.498Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:57:58.604Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:57:59.714Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:58:00.028Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:58:00.028Z] The best model improves the baseline by 14.34%. [2025-12-11T23:58:00.028Z] Top recommended movies for user id 72: [2025-12-11T23:58:00.028Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:58:00.028Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:58:00.028Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:58:00.028Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:58:00.028Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:58:00.028Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13654.033 ms) ====== [2025-12-11T23:58:00.028Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-11T23:58:00.352Z] GC before operation: completed in 145.128 ms, heap usage 440.139 MB -> 89.570 MB. [2025-12-11T23:58:02.532Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:58:04.713Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:58:06.305Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:58:08.488Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:58:09.592Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:58:10.696Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:58:12.295Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:58:13.402Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:58:13.402Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:58:13.402Z] The best model improves the baseline by 14.34%. [2025-12-11T23:58:13.717Z] Top recommended movies for user id 72: [2025-12-11T23:58:13.717Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:58:13.717Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:58:13.717Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:58:13.717Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:58:13.717Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:58:13.717Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13248.900 ms) ====== [2025-12-11T23:58:13.717Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-11T23:58:13.717Z] GC before operation: completed in 135.053 ms, heap usage 169.990 MB -> 89.199 MB. [2025-12-11T23:58:15.901Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:58:17.502Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:58:19.702Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:58:21.884Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:58:22.985Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:58:24.084Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:58:25.183Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:58:26.783Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:58:26.783Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:58:26.783Z] The best model improves the baseline by 14.34%. [2025-12-11T23:58:26.783Z] Top recommended movies for user id 72: [2025-12-11T23:58:26.783Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:58:26.783Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:58:26.783Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:58:26.783Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:58:26.783Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:58:26.783Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13155.463 ms) ====== [2025-12-11T23:58:26.783Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-11T23:58:27.097Z] GC before operation: completed in 148.459 ms, heap usage 599.374 MB -> 93.189 MB. [2025-12-11T23:58:29.279Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:58:31.470Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:58:33.657Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:58:35.258Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:58:36.362Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:58:37.468Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:58:39.122Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:58:40.239Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:58:40.239Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:58:40.239Z] The best model improves the baseline by 14.34%. [2025-12-11T23:58:40.239Z] Top recommended movies for user id 72: [2025-12-11T23:58:40.239Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:58:40.239Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:58:40.239Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:58:40.239Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:58:40.239Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:58:40.239Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13349.199 ms) ====== [2025-12-11T23:58:40.239Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-11T23:58:40.554Z] GC before operation: completed in 141.202 ms, heap usage 307.984 MB -> 89.400 MB. [2025-12-11T23:58:42.738Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:58:44.336Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:58:46.562Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:58:48.748Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:58:49.849Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:58:50.952Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:58:52.058Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:58:53.162Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:58:53.476Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:58:53.476Z] The best model improves the baseline by 14.34%. [2025-12-11T23:58:53.476Z] Top recommended movies for user id 72: [2025-12-11T23:58:53.476Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:58:53.476Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:58:53.476Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:58:53.476Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:58:53.476Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:58:53.476Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13084.844 ms) ====== [2025-12-11T23:58:53.476Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-11T23:58:53.791Z] GC before operation: completed in 144.585 ms, heap usage 216.958 MB -> 89.365 MB. [2025-12-11T23:58:55.979Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:58:57.636Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:58:59.826Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:59:02.014Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:59:03.123Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:59:04.223Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:59:05.329Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:59:06.927Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:59:06.927Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:59:06.927Z] The best model improves the baseline by 14.34%. [2025-12-11T23:59:06.927Z] Top recommended movies for user id 72: [2025-12-11T23:59:06.927Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:59:06.927Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:59:06.927Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:59:06.927Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:59:06.927Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:59:06.927Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13282.909 ms) ====== [2025-12-11T23:59:06.927Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-11T23:59:07.243Z] GC before operation: completed in 146.782 ms, heap usage 217.887 MB -> 89.309 MB. [2025-12-11T23:59:09.425Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:59:11.023Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:59:13.209Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:59:14.811Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:59:16.412Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:59:17.515Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:59:18.665Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:59:19.767Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:59:20.081Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:59:20.081Z] The best model improves the baseline by 14.34%. [2025-12-11T23:59:20.081Z] Top recommended movies for user id 72: [2025-12-11T23:59:20.081Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:59:20.081Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:59:20.081Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:59:20.081Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:59:20.081Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:59:20.081Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12958.193 ms) ====== [2025-12-11T23:59:20.081Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-11T23:59:20.395Z] GC before operation: completed in 138.348 ms, heap usage 170.387 MB -> 89.373 MB. [2025-12-11T23:59:22.583Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:59:24.764Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:59:26.949Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:59:28.543Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:59:29.653Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:59:31.256Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:59:32.359Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:59:33.953Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:59:33.953Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:59:33.953Z] The best model improves the baseline by 14.34%. [2025-12-11T23:59:33.953Z] Top recommended movies for user id 72: [2025-12-11T23:59:33.953Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:59:33.953Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:59:33.953Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:59:33.953Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:59:33.953Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:59:33.953Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13692.392 ms) ====== [2025-12-11T23:59:33.953Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-11T23:59:33.953Z] GC before operation: completed in 148.672 ms, heap usage 689.470 MB -> 93.897 MB. [2025-12-11T23:59:36.144Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:59:38.327Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:59:40.601Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:59:42.198Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:59:43.304Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:59:44.409Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:59:46.011Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-11T23:59:47.116Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-11T23:59:47.116Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-11T23:59:47.116Z] The best model improves the baseline by 14.34%. [2025-12-11T23:59:47.436Z] Top recommended movies for user id 72: [2025-12-11T23:59:47.436Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-11T23:59:47.436Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-11T23:59:47.436Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-11T23:59:47.436Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-11T23:59:47.436Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-11T23:59:47.436Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13228.535 ms) ====== [2025-12-11T23:59:47.436Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-11T23:59:47.436Z] GC before operation: completed in 131.691 ms, heap usage 311.920 MB -> 89.490 MB. [2025-12-11T23:59:49.636Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-11T23:59:51.241Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-11T23:59:53.422Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-11T23:59:55.023Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-11T23:59:56.670Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-11T23:59:57.769Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-11T23:59:58.931Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-12T00:00:00.034Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-12T00:00:00.353Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-12T00:00:00.353Z] The best model improves the baseline by 14.34%. [2025-12-12T00:00:00.353Z] Top recommended movies for user id 72: [2025-12-12T00:00:00.353Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-12T00:00:00.353Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-12T00:00:00.353Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-12T00:00:00.353Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-12T00:00:00.353Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-12T00:00:00.353Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12929.652 ms) ====== [2025-12-12T00:00:01.028Z] ----------------------------------- [2025-12-12T00:00:01.029Z] renaissance-movie-lens_0_PASSED [2025-12-12T00:00:01.029Z] ----------------------------------- [2025-12-12T00:00:01.029Z] [2025-12-12T00:00:01.029Z] TEST TEARDOWN: [2025-12-12T00:00:01.029Z] Nothing to be done for teardown. [2025-12-12T00:00:01.029Z] renaissance-movie-lens_0 Finish Time: Fri Dec 12 00:00:00 2025 Epoch Time (ms): 1765497600729