[2025-09-25T02:27:20.687Z] Running test renaissance-movie-lens_0 ... [2025-09-25T02:27:20.687Z] =============================================== [2025-09-25T02:27:20.687Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 02:27:19 2025 Epoch Time (ms): 1758767239705 [2025-09-25T02:27:20.687Z] variation: NoOptions [2025-09-25T02:27:20.687Z] JVM_OPTIONS: [2025-09-25T02:27:20.687Z] { \ [2025-09-25T02:27:20.687Z] echo ""; echo "TEST SETUP:"; \ [2025-09-25T02:27:20.687Z] echo "Nothing to be done for setup."; \ [2025-09-25T02:27:20.687Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17587656834733/renaissance-movie-lens_0"; \ [2025-09-25T02:27:20.687Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17587656834733/renaissance-movie-lens_0"; \ [2025-09-25T02:27:20.687Z] echo ""; echo "TESTING:"; \ [2025-09-25T02:27:20.687Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_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_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17587656834733/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-25T02:27:20.687Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17587656834733/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-25T02:27:20.687Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-25T02:27:20.687Z] echo "Nothing to be done for teardown."; \ [2025-09-25T02:27:20.687Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17587656834733/TestTargetResult"; [2025-09-25T02:27:20.687Z] [2025-09-25T02:27:20.687Z] TEST SETUP: [2025-09-25T02:27:20.687Z] Nothing to be done for setup. [2025-09-25T02:27:20.687Z] [2025-09-25T02:27:20.687Z] TESTING: [2025-09-25T02:27:24.258Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-09-25T02:27:29.152Z] 02:27:28.603 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. [2025-09-25T02:27:31.116Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-25T02:27:31.722Z] Training: 60056, validation: 20285, test: 19854 [2025-09-25T02:27:31.722Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-25T02:27:31.722Z] GC before operation: completed in 175.850 ms, heap usage 190.732 MB -> 75.644 MB. [2025-09-25T02:27:37.376Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:27:40.983Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:27:45.596Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:27:49.179Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:27:51.143Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:27:52.376Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:27:54.343Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:27:56.283Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:27:56.283Z] 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. [2025-09-25T02:27:56.283Z] The best model improves the baseline by 14.34%. [2025-09-25T02:27:56.875Z] Top recommended movies for user id 72: [2025-09-25T02:27:56.875Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:27:56.875Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:27:56.875Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:27:56.875Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:27:56.875Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:27:56.875Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24803.583 ms) ====== [2025-09-25T02:27:56.875Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-25T02:27:56.875Z] GC before operation: completed in 255.087 ms, heap usage 452.032 MB -> 90.057 MB. [2025-09-25T02:28:00.455Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:28:03.192Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:28:05.940Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:28:08.250Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:28:10.200Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:28:11.444Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:28:13.397Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:28:14.643Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:28:15.240Z] 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. [2025-09-25T02:28:15.240Z] The best model improves the baseline by 14.34%. [2025-09-25T02:28:15.240Z] Top recommended movies for user id 72: [2025-09-25T02:28:15.240Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:28:15.240Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:28:15.240Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:28:15.240Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:28:15.240Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:28:15.240Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18323.395 ms) ====== [2025-09-25T02:28:15.240Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-25T02:28:15.240Z] GC before operation: completed in 136.528 ms, heap usage 263.544 MB -> 90.086 MB. [2025-09-25T02:28:18.034Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:28:19.972Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:28:22.686Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:28:25.420Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:28:26.662Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:28:28.642Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:28:29.875Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:28:31.818Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:28:31.818Z] 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. [2025-09-25T02:28:31.818Z] The best model improves the baseline by 14.34%. [2025-09-25T02:28:31.818Z] Top recommended movies for user id 72: [2025-09-25T02:28:31.818Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:28:31.818Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:28:31.818Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:28:31.818Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:28:31.818Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:28:31.818Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16535.287 ms) ====== [2025-09-25T02:28:31.818Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-25T02:28:32.410Z] GC before operation: completed in 228.310 ms, heap usage 179.920 MB -> 88.325 MB. [2025-09-25T02:28:34.349Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:28:37.053Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:28:40.142Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:28:42.075Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:28:44.020Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:28:45.259Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:28:47.197Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:28:48.431Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:28:48.432Z] 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. [2025-09-25T02:28:48.432Z] The best model improves the baseline by 14.34%. [2025-09-25T02:28:49.022Z] Top recommended movies for user id 72: [2025-09-25T02:28:49.022Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:28:49.022Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:28:49.022Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:28:49.022Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:28:49.022Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:28:49.022Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16546.445 ms) ====== [2025-09-25T02:28:49.022Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-25T02:28:49.022Z] GC before operation: completed in 156.026 ms, heap usage 167.776 MB -> 92.077 MB. [2025-09-25T02:28:51.734Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:28:53.679Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:28:56.415Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:28:58.361Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:29:00.297Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:29:01.532Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:29:03.502Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:29:04.748Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:29:04.748Z] 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. [2025-09-25T02:29:05.343Z] The best model improves the baseline by 14.34%. [2025-09-25T02:29:05.343Z] Top recommended movies for user id 72: [2025-09-25T02:29:05.343Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:29:05.343Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:29:05.343Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:29:05.343Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:29:05.343Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:29:05.343Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16297.793 ms) ====== [2025-09-25T02:29:05.343Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-25T02:29:05.343Z] GC before operation: completed in 148.835 ms, heap usage 229.756 MB -> 88.798 MB. [2025-09-25T02:29:08.094Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:29:10.826Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:29:13.552Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:29:15.865Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:29:17.105Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:29:18.335Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:29:20.267Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:29:21.510Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:29:21.510Z] 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. [2025-09-25T02:29:21.510Z] The best model improves the baseline by 14.34%. [2025-09-25T02:29:22.103Z] Top recommended movies for user id 72: [2025-09-25T02:29:22.103Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:29:22.103Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:29:22.103Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:29:22.103Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:29:22.103Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:29:22.103Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16539.022 ms) ====== [2025-09-25T02:29:22.103Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-25T02:29:22.103Z] GC before operation: completed in 176.675 ms, heap usage 169.195 MB -> 89.018 MB. [2025-09-25T02:29:24.813Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:29:26.786Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:29:29.521Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:29:32.237Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:29:33.557Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:29:34.815Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:29:36.072Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:29:38.006Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:29:38.006Z] 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. [2025-09-25T02:29:38.006Z] The best model improves the baseline by 14.34%. [2025-09-25T02:29:38.006Z] Top recommended movies for user id 72: [2025-09-25T02:29:38.006Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:29:38.006Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:29:38.006Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:29:38.006Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:29:38.006Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:29:38.006Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15962.923 ms) ====== [2025-09-25T02:29:38.006Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-25T02:29:38.006Z] GC before operation: completed in 140.064 ms, heap usage 256.446 MB -> 89.179 MB. [2025-09-25T02:29:40.714Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:29:42.665Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:29:45.371Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:29:47.306Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:29:48.536Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:29:49.779Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:29:52.090Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:29:52.705Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:29:53.304Z] 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. [2025-09-25T02:29:53.304Z] The best model improves the baseline by 14.34%. [2025-09-25T02:29:53.304Z] Top recommended movies for user id 72: [2025-09-25T02:29:53.304Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:29:53.304Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:29:53.304Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:29:53.304Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:29:53.304Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:29:53.304Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15200.616 ms) ====== [2025-09-25T02:29:53.304Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-25T02:29:53.304Z] GC before operation: completed in 127.998 ms, heap usage 177.930 MB -> 89.313 MB. [2025-09-25T02:29:56.023Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:29:58.767Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:30:01.476Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:30:03.499Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:30:05.472Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:30:06.842Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:30:08.078Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:30:09.306Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:30:09.910Z] 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. [2025-09-25T02:30:09.910Z] The best model improves the baseline by 14.34%. [2025-09-25T02:30:09.910Z] Top recommended movies for user id 72: [2025-09-25T02:30:09.910Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:30:09.910Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:30:09.910Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:30:09.910Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:30:09.910Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:30:09.910Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16355.773 ms) ====== [2025-09-25T02:30:09.910Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-25T02:30:09.910Z] GC before operation: completed in 136.762 ms, heap usage 411.823 MB -> 89.570 MB. [2025-09-25T02:30:12.639Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:30:14.582Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:30:17.320Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:30:19.319Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:30:21.256Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:30:22.565Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:30:23.798Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:30:25.436Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:30:25.436Z] 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. [2025-09-25T02:30:25.436Z] The best model improves the baseline by 14.34%. [2025-09-25T02:30:25.436Z] Top recommended movies for user id 72: [2025-09-25T02:30:25.436Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:30:25.436Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:30:25.436Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:30:25.436Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:30:25.436Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:30:25.436Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15679.043 ms) ====== [2025-09-25T02:30:25.436Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-25T02:30:26.031Z] GC before operation: completed in 176.424 ms, heap usage 169.220 MB -> 89.305 MB. [2025-09-25T02:30:27.969Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:30:30.687Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:30:33.433Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:30:35.395Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:30:36.626Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:30:37.859Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:30:39.089Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:30:40.394Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:30:40.991Z] 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. [2025-09-25T02:30:40.991Z] The best model improves the baseline by 14.34%. [2025-09-25T02:30:40.991Z] Top recommended movies for user id 72: [2025-09-25T02:30:40.991Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:30:40.991Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:30:40.991Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:30:40.991Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:30:40.991Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:30:40.991Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15035.305 ms) ====== [2025-09-25T02:30:40.991Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-25T02:30:40.991Z] GC before operation: completed in 146.327 ms, heap usage 255.611 MB -> 89.226 MB. [2025-09-25T02:30:42.931Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:30:45.648Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:30:48.360Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:30:50.301Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:30:51.563Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:30:52.812Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:30:54.057Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:30:55.320Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:30:55.911Z] 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. [2025-09-25T02:30:55.911Z] The best model improves the baseline by 14.34%. [2025-09-25T02:30:55.911Z] Top recommended movies for user id 72: [2025-09-25T02:30:55.911Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:30:55.911Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:30:55.911Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:30:55.911Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:30:55.911Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:30:55.911Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14984.634 ms) ====== [2025-09-25T02:30:55.911Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-25T02:30:55.911Z] GC before operation: completed in 192.327 ms, heap usage 142.282 MB -> 89.270 MB. [2025-09-25T02:30:58.636Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:31:00.606Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:31:03.432Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:31:05.363Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:31:07.301Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:31:08.593Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:31:09.840Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:31:11.098Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:31:11.701Z] 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. [2025-09-25T02:31:11.701Z] The best model improves the baseline by 14.34%. [2025-09-25T02:31:11.701Z] Top recommended movies for user id 72: [2025-09-25T02:31:11.701Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:31:11.701Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:31:11.701Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:31:11.701Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:31:11.701Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:31:11.701Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15548.102 ms) ====== [2025-09-25T02:31:11.701Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-25T02:31:11.701Z] GC before operation: completed in 139.561 ms, heap usage 144.638 MB -> 89.348 MB. [2025-09-25T02:31:13.632Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:31:16.339Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:31:18.272Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:31:20.985Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:31:22.232Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:31:23.470Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:31:24.700Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:31:26.032Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:31:26.630Z] 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. [2025-09-25T02:31:26.630Z] The best model improves the baseline by 14.34%. [2025-09-25T02:31:26.630Z] Top recommended movies for user id 72: [2025-09-25T02:31:26.630Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:31:26.630Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:31:26.630Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:31:26.630Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:31:26.630Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:31:26.630Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14809.007 ms) ====== [2025-09-25T02:31:26.630Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-25T02:31:27.220Z] GC before operation: completed in 233.820 ms, heap usage 224.422 MB -> 89.255 MB. [2025-09-25T02:31:29.166Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:31:31.892Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:31:33.853Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:31:35.801Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:31:37.041Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:31:38.996Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:31:40.232Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:31:41.513Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:31:41.514Z] 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. [2025-09-25T02:31:41.514Z] The best model improves the baseline by 14.34%. [2025-09-25T02:31:41.514Z] Top recommended movies for user id 72: [2025-09-25T02:31:41.514Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:31:41.514Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:31:41.514Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:31:41.514Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:31:41.514Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:31:41.514Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14807.970 ms) ====== [2025-09-25T02:31:41.514Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-25T02:31:42.104Z] GC before operation: completed in 203.023 ms, heap usage 236.048 MB -> 89.427 MB. [2025-09-25T02:31:44.066Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:31:46.798Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:31:48.797Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:31:51.549Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:31:52.805Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:31:54.060Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:31:55.312Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:31:57.262Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:31:57.262Z] 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. [2025-09-25T02:31:57.262Z] The best model improves the baseline by 14.34%. [2025-09-25T02:31:57.262Z] Top recommended movies for user id 72: [2025-09-25T02:31:57.262Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:31:57.262Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:31:57.262Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:31:57.262Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:31:57.262Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:31:57.262Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15317.593 ms) ====== [2025-09-25T02:31:57.262Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-25T02:31:57.262Z] GC before operation: completed in 155.525 ms, heap usage 308.191 MB -> 89.443 MB. [2025-09-25T02:32:00.001Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:32:01.935Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:32:04.682Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:32:06.656Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:32:08.936Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:32:09.528Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:32:10.800Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:32:12.776Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:32:12.776Z] 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. [2025-09-25T02:32:12.776Z] The best model improves the baseline by 14.34%. [2025-09-25T02:32:12.776Z] Top recommended movies for user id 72: [2025-09-25T02:32:12.776Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:32:12.776Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:32:12.776Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:32:12.776Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:32:12.776Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:32:12.776Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15415.180 ms) ====== [2025-09-25T02:32:12.776Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-25T02:32:12.776Z] GC before operation: completed in 168.220 ms, heap usage 169.371 MB -> 89.337 MB. [2025-09-25T02:32:15.553Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:32:18.285Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:32:20.265Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:32:22.990Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:32:24.246Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:32:25.479Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:32:26.709Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:32:27.946Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:32:28.540Z] 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. [2025-09-25T02:32:28.540Z] The best model improves the baseline by 14.34%. [2025-09-25T02:32:28.540Z] Top recommended movies for user id 72: [2025-09-25T02:32:28.540Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:32:28.540Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:32:28.540Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:32:28.540Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:32:28.540Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:32:28.540Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15495.393 ms) ====== [2025-09-25T02:32:28.540Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-25T02:32:28.540Z] GC before operation: completed in 165.620 ms, heap usage 219.566 MB -> 89.196 MB. [2025-09-25T02:32:31.287Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:32:33.226Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:32:36.034Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:32:37.967Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:32:39.226Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:32:40.470Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:32:41.704Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:32:42.948Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:32:43.540Z] 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. [2025-09-25T02:32:43.540Z] The best model improves the baseline by 14.34%. [2025-09-25T02:32:43.540Z] Top recommended movies for user id 72: [2025-09-25T02:32:43.540Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:32:43.540Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:32:43.540Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:32:43.540Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:32:43.540Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:32:43.540Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14925.756 ms) ====== [2025-09-25T02:32:43.540Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-25T02:32:43.540Z] GC before operation: completed in 154.116 ms, heap usage 194.204 MB -> 89.220 MB. [2025-09-25T02:32:45.860Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:32:48.593Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:32:50.538Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:32:53.248Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:32:54.483Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:32:55.709Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:32:56.950Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:32:58.189Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:32:58.784Z] 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. [2025-09-25T02:32:58.785Z] The best model improves the baseline by 14.34%. [2025-09-25T02:32:58.785Z] Top recommended movies for user id 72: [2025-09-25T02:32:58.785Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:32:58.785Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:32:58.785Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:32:58.785Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:32:58.785Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:32:58.785Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15075.925 ms) ====== [2025-09-25T02:32:59.388Z] ----------------------------------- [2025-09-25T02:32:59.388Z] renaissance-movie-lens_0_PASSED [2025-09-25T02:32:59.388Z] ----------------------------------- [2025-09-25T02:32:59.388Z] [2025-09-25T02:32:59.388Z] TEST TEARDOWN: [2025-09-25T02:32:59.388Z] Nothing to be done for teardown. [2025-09-25T02:32:59.388Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 02:32:58 2025 Epoch Time (ms): 1758767578875