[2025-08-28T06:41:16.082Z] Running test renaissance-movie-lens_0 ... [2025-08-28T06:41:16.082Z] =============================================== [2025-08-28T06:41:16.082Z] renaissance-movie-lens_0 Start Time: Thu Aug 28 06:41:15 2025 Epoch Time (ms): 1756363275620 [2025-08-28T06:41:16.082Z] variation: NoOptions [2025-08-28T06:41:16.082Z] JVM_OPTIONS: [2025-08-28T06:41:16.082Z] { \ [2025-08-28T06:41:16.082Z] echo ""; echo "TEST SETUP:"; \ [2025-08-28T06:41:16.082Z] echo "Nothing to be done for setup."; \ [2025-08-28T06:41:16.082Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17563632733223/renaissance-movie-lens_0"; \ [2025-08-28T06:41:16.082Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17563632733223/renaissance-movie-lens_0"; \ [2025-08-28T06:41:16.082Z] echo ""; echo "TESTING:"; \ [2025-08-28T06:41:16.082Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/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_s390x_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17563632733223/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-08-28T06:41:16.082Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17563632733223/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-08-28T06:41:16.082Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-08-28T06:41:16.082Z] echo "Nothing to be done for teardown."; \ [2025-08-28T06:41:16.082Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17563632733223/TestTargetResult"; [2025-08-28T06:41:16.082Z] [2025-08-28T06:41:16.082Z] TEST SETUP: [2025-08-28T06:41:16.082Z] Nothing to be done for setup. [2025-08-28T06:41:16.082Z] [2025-08-28T06:41:16.082Z] TESTING: [2025-08-28T06:41:20.746Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-08-28T06:41:26.913Z] 06:41:26.508 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-08-28T06:41:29.739Z] Got 100004 ratings from 671 users on 9066 movies. [2025-08-28T06:41:30.335Z] Training: 60056, validation: 20285, test: 19854 [2025-08-28T06:41:30.335Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-08-28T06:41:30.923Z] GC before operation: completed in 204.684 ms, heap usage 176.569 MB -> 75.815 MB. [2025-08-28T06:41:37.896Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:41:41.532Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:41:45.225Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:41:48.839Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:41:50.774Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:41:52.738Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:41:54.695Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:41:56.677Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:41:57.273Z] 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. [2025-08-28T06:41:57.273Z] The best model improves the baseline by 14.34%. [2025-08-28T06:41:57.273Z] Top recommended movies for user id 72: [2025-08-28T06:41:57.273Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:41:57.273Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:41:57.273Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:41:57.273Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:41:57.274Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:41:57.274Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26661.373 ms) ====== [2025-08-28T06:41:57.274Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-08-28T06:41:57.871Z] GC before operation: completed in 188.519 ms, heap usage 175.630 MB -> 86.085 MB. [2025-08-28T06:42:00.600Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:42:04.202Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:42:06.936Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:42:09.672Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:42:11.653Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:42:13.608Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:42:15.567Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:42:18.288Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:42:18.288Z] 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. [2025-08-28T06:42:18.288Z] The best model improves the baseline by 14.34%. [2025-08-28T06:42:18.288Z] Top recommended movies for user id 72: [2025-08-28T06:42:18.288Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:42:18.288Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:42:18.288Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:42:18.288Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:42:18.288Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:42:18.288Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20735.773 ms) ====== [2025-08-28T06:42:18.288Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-08-28T06:42:18.288Z] GC before operation: completed in 175.459 ms, heap usage 101.691 MB -> 91.570 MB. [2025-08-28T06:42:21.937Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:42:24.742Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:42:27.883Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:42:30.612Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:42:32.616Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:42:33.873Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:42:35.850Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:42:37.808Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:42:37.808Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-08-28T06:42:37.808Z] The best model improves the baseline by 14.34%. [2025-08-28T06:42:38.399Z] Top recommended movies for user id 72: [2025-08-28T06:42:38.399Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:42:38.399Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:42:38.399Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:42:38.399Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:42:38.399Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:42:38.399Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19587.565 ms) ====== [2025-08-28T06:42:38.399Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-08-28T06:42:38.399Z] GC before operation: completed in 226.287 ms, heap usage 165.036 MB -> 88.364 MB. [2025-08-28T06:42:41.134Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:42:43.883Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:42:46.621Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:42:49.365Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:42:51.330Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:42:53.331Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:42:55.301Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:42:57.302Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:42:57.302Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-08-28T06:42:57.302Z] The best model improves the baseline by 14.34%. [2025-08-28T06:42:57.938Z] Top recommended movies for user id 72: [2025-08-28T06:42:57.938Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:42:57.938Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:42:57.938Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:42:57.938Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:42:57.938Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:42:57.938Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19264.960 ms) ====== [2025-08-28T06:42:57.939Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-08-28T06:42:57.939Z] GC before operation: completed in 277.508 ms, heap usage 140.454 MB -> 88.680 MB. [2025-08-28T06:43:00.737Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:43:04.432Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:43:07.203Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:43:10.006Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:43:11.967Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:43:14.014Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:43:15.274Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:43:17.248Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:43:17.248Z] 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. [2025-08-28T06:43:17.248Z] The best model improves the baseline by 14.34%. [2025-08-28T06:43:17.897Z] Top recommended movies for user id 72: [2025-08-28T06:43:17.897Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:43:17.897Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:43:17.897Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:43:17.897Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:43:17.897Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:43:17.897Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19802.164 ms) ====== [2025-08-28T06:43:17.897Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-08-28T06:43:17.897Z] GC before operation: completed in 222.595 ms, heap usage 151.665 MB -> 88.675 MB. [2025-08-28T06:43:21.574Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:43:24.320Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:43:27.123Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:43:29.923Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:43:31.191Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:43:32.433Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:43:34.812Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:43:36.069Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:43:36.070Z] 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. [2025-08-28T06:43:36.070Z] The best model improves the baseline by 14.34%. [2025-08-28T06:43:36.673Z] Top recommended movies for user id 72: [2025-08-28T06:43:36.673Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:43:36.673Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:43:36.673Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:43:36.673Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:43:36.673Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:43:36.673Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18515.529 ms) ====== [2025-08-28T06:43:36.673Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-08-28T06:43:36.673Z] GC before operation: completed in 177.858 ms, heap usage 165.495 MB -> 89.006 MB. [2025-08-28T06:43:39.440Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:43:42.194Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:43:44.991Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:43:46.951Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:43:48.891Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:43:50.125Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:43:52.063Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:43:53.326Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:43:53.326Z] 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. [2025-08-28T06:43:53.326Z] The best model improves the baseline by 14.34%. [2025-08-28T06:43:53.917Z] Top recommended movies for user id 72: [2025-08-28T06:43:53.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:43:53.917Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:43:53.917Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:43:53.917Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:43:53.917Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:43:53.917Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17158.972 ms) ====== [2025-08-28T06:43:53.917Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-08-28T06:43:53.917Z] GC before operation: completed in 242.308 ms, heap usage 216.904 MB -> 89.087 MB. [2025-08-28T06:43:56.625Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:43:59.343Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:44:02.048Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:44:03.986Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:44:05.248Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:44:07.190Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:44:08.436Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:44:10.384Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:44:10.384Z] 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. [2025-08-28T06:44:10.384Z] The best model improves the baseline by 14.34%. [2025-08-28T06:44:10.384Z] Top recommended movies for user id 72: [2025-08-28T06:44:10.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:44:10.384Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:44:10.384Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:44:10.384Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:44:10.384Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:44:10.384Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16393.103 ms) ====== [2025-08-28T06:44:10.384Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-08-28T06:44:10.384Z] GC before operation: completed in 160.778 ms, heap usage 204.547 MB -> 93.322 MB. [2025-08-28T06:44:13.094Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:44:15.063Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:44:17.782Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:44:19.718Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:44:20.993Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:44:22.943Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:44:24.178Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:44:26.114Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:44:26.716Z] 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. [2025-08-28T06:44:26.716Z] The best model improves the baseline by 14.34%. [2025-08-28T06:44:26.716Z] Top recommended movies for user id 72: [2025-08-28T06:44:26.716Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:44:26.716Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:44:26.716Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:44:26.716Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:44:26.716Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:44:26.716Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16177.840 ms) ====== [2025-08-28T06:44:26.716Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-08-28T06:44:26.716Z] GC before operation: completed in 167.159 ms, heap usage 279.164 MB -> 89.211 MB. [2025-08-28T06:44:29.425Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:44:32.144Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:44:34.864Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:44:36.875Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:44:38.822Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:44:40.062Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:44:41.991Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:44:43.252Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:44:43.252Z] 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. [2025-08-28T06:44:43.252Z] The best model improves the baseline by 14.34%. [2025-08-28T06:44:43.850Z] Top recommended movies for user id 72: [2025-08-28T06:44:43.850Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:44:43.850Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:44:43.850Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:44:43.850Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:44:43.850Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:44:43.850Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16694.125 ms) ====== [2025-08-28T06:44:43.850Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-08-28T06:44:43.850Z] GC before operation: completed in 155.195 ms, heap usage 250.179 MB -> 89.422 MB. [2025-08-28T06:44:45.867Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:44:48.598Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:44:51.313Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:44:54.027Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:44:55.273Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:44:57.225Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:44:59.162Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:45:00.476Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:45:00.476Z] 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. [2025-08-28T06:45:00.476Z] The best model improves the baseline by 14.34%. [2025-08-28T06:45:00.476Z] Top recommended movies for user id 72: [2025-08-28T06:45:00.476Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:45:00.476Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:45:00.476Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:45:00.476Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:45:00.476Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:45:00.476Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16789.284 ms) ====== [2025-08-28T06:45:00.476Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-08-28T06:45:00.476Z] GC before operation: completed in 117.187 ms, heap usage 374.917 MB -> 89.376 MB. [2025-08-28T06:45:03.232Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:45:05.936Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:45:08.651Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:45:10.588Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:45:12.523Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:45:13.754Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:45:15.703Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:45:16.938Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:45:17.538Z] 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. [2025-08-28T06:45:17.538Z] The best model improves the baseline by 14.34%. [2025-08-28T06:45:17.538Z] Top recommended movies for user id 72: [2025-08-28T06:45:17.538Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:45:17.538Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:45:17.538Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:45:17.538Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:45:17.538Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:45:17.538Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16830.346 ms) ====== [2025-08-28T06:45:17.538Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-08-28T06:45:17.538Z] GC before operation: completed in 109.682 ms, heap usage 174.600 MB -> 89.198 MB. [2025-08-28T06:45:19.484Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:45:22.191Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:45:24.917Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:45:27.640Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:45:28.880Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:45:30.836Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:45:32.849Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:45:34.080Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:45:34.080Z] 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. [2025-08-28T06:45:34.080Z] The best model improves the baseline by 14.34%. [2025-08-28T06:45:34.080Z] Top recommended movies for user id 72: [2025-08-28T06:45:34.080Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:45:34.080Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:45:34.080Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:45:34.080Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:45:34.080Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:45:34.080Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16671.879 ms) ====== [2025-08-28T06:45:34.080Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-08-28T06:45:34.671Z] GC before operation: completed in 120.486 ms, heap usage 215.617 MB -> 89.378 MB. [2025-08-28T06:45:36.603Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:45:39.752Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:45:42.470Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:45:44.416Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:45:46.368Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:45:47.611Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:45:49.555Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:45:50.832Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:45:50.832Z] 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. [2025-08-28T06:45:50.832Z] The best model improves the baseline by 14.34%. [2025-08-28T06:45:50.832Z] Top recommended movies for user id 72: [2025-08-28T06:45:50.832Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:45:50.832Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:45:50.832Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:45:50.832Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:45:50.832Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:45:50.832Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16628.763 ms) ====== [2025-08-28T06:45:50.832Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-08-28T06:45:51.422Z] GC before operation: completed in 131.255 ms, heap usage 225.059 MB -> 89.282 MB. [2025-08-28T06:45:53.381Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:45:56.132Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:45:58.137Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:46:00.916Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:46:02.159Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:46:03.398Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:46:04.640Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:46:05.941Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:46:05.941Z] 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. [2025-08-28T06:46:05.941Z] The best model improves the baseline by 14.34%. [2025-08-28T06:46:06.548Z] Top recommended movies for user id 72: [2025-08-28T06:46:06.548Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:46:06.548Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:46:06.548Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:46:06.548Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:46:06.548Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:46:06.548Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15168.556 ms) ====== [2025-08-28T06:46:06.548Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-08-28T06:46:06.548Z] GC before operation: completed in 157.049 ms, heap usage 204.588 MB -> 89.415 MB. [2025-08-28T06:46:09.274Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:46:11.238Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:46:13.199Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:46:15.218Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:46:16.463Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:46:17.696Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:46:19.643Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:46:20.324Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:46:20.915Z] 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. [2025-08-28T06:46:20.915Z] The best model improves the baseline by 14.34%. [2025-08-28T06:46:20.915Z] Top recommended movies for user id 72: [2025-08-28T06:46:20.915Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:46:20.915Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:46:20.915Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:46:20.915Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:46:20.915Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:46:20.915Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14501.798 ms) ====== [2025-08-28T06:46:20.915Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-08-28T06:46:20.915Z] GC before operation: completed in 195.122 ms, heap usage 218.336 MB -> 89.319 MB. [2025-08-28T06:46:23.628Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:46:25.567Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:46:28.306Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:46:30.255Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:46:31.490Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:46:32.721Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:46:34.671Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:46:35.907Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:46:35.907Z] 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. [2025-08-28T06:46:35.908Z] The best model improves the baseline by 14.34%. [2025-08-28T06:46:35.908Z] Top recommended movies for user id 72: [2025-08-28T06:46:35.908Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:46:35.908Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:46:35.908Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:46:35.908Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:46:35.908Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:46:35.908Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14883.562 ms) ====== [2025-08-28T06:46:35.908Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-08-28T06:46:36.537Z] GC before operation: completed in 151.045 ms, heap usage 217.069 MB -> 89.410 MB. [2025-08-28T06:46:38.478Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:46:40.779Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:46:43.500Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:46:45.443Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:46:46.671Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:46:47.940Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:46:49.171Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:46:50.407Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:46:51.001Z] 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. [2025-08-28T06:46:51.001Z] The best model improves the baseline by 14.34%. [2025-08-28T06:46:51.001Z] Top recommended movies for user id 72: [2025-08-28T06:46:51.001Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:46:51.001Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:46:51.001Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:46:51.001Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:46:51.001Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:46:51.001Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14706.959 ms) ====== [2025-08-28T06:46:51.001Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-08-28T06:46:51.001Z] GC before operation: completed in 150.662 ms, heap usage 314.705 MB -> 89.512 MB. [2025-08-28T06:46:53.769Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:46:55.729Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:46:58.494Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:47:00.467Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:47:02.420Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:47:03.664Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:47:05.689Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:47:06.997Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:47:06.997Z] 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. [2025-08-28T06:47:06.997Z] The best model improves the baseline by 14.34%. [2025-08-28T06:47:06.997Z] Top recommended movies for user id 72: [2025-08-28T06:47:06.997Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:47:06.997Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:47:06.997Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:47:06.997Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:47:06.997Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:47:06.997Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16085.414 ms) ====== [2025-08-28T06:47:06.997Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-08-28T06:47:07.614Z] GC before operation: completed in 199.563 ms, heap usage 235.003 MB -> 89.397 MB. [2025-08-28T06:47:09.584Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-28T06:47:12.349Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-28T06:47:15.123Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-28T06:47:17.094Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-28T06:47:19.053Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-28T06:47:20.351Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-28T06:47:22.318Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-28T06:47:23.583Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-28T06:47:24.193Z] 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. [2025-08-28T06:47:24.193Z] The best model improves the baseline by 14.34%. [2025-08-28T06:47:24.193Z] Top recommended movies for user id 72: [2025-08-28T06:47:24.193Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-08-28T06:47:24.193Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-08-28T06:47:24.193Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-08-28T06:47:24.193Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-08-28T06:47:24.193Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-08-28T06:47:24.193Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16882.568 ms) ====== [2025-08-28T06:47:24.797Z] ----------------------------------- [2025-08-28T06:47:24.798Z] renaissance-movie-lens_0_PASSED [2025-08-28T06:47:24.798Z] ----------------------------------- [2025-08-28T06:47:24.798Z] [2025-08-28T06:47:24.798Z] TEST TEARDOWN: [2025-08-28T06:47:24.798Z] Nothing to be done for teardown. [2025-08-28T06:47:24.798Z] renaissance-movie-lens_0 Finish Time: Thu Aug 28 06:47:24 2025 Epoch Time (ms): 1756363644291