[2025-12-13T13:36:03.349Z] Running test renaissance-movie-lens_0 ... [2025-12-13T13:36:03.349Z] =============================================== [2025-12-13T13:36:03.349Z] renaissance-movie-lens_0 Start Time: Sat Dec 13 13:36:03 2025 Epoch Time (ms): 1765632963306 [2025-12-13T13:36:03.349Z] variation: NoOptions [2025-12-13T13:36:03.349Z] JVM_OPTIONS: [2025-12-13T13:36:03.349Z] { \ [2025-12-13T13:36:03.349Z] echo ""; echo "TEST SETUP:"; \ [2025-12-13T13:36:03.349Z] echo "Nothing to be done for setup."; \ [2025-12-13T13:36:03.349Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656311645582/renaissance-movie-lens_0"; \ [2025-12-13T13:36:03.349Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656311645582/renaissance-movie-lens_0"; \ [2025-12-13T13:36:03.349Z] echo ""; echo "TESTING:"; \ [2025-12-13T13:36:03.349Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656311645582/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-13T13:36:03.349Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656311645582/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-13T13:36:03.349Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-13T13:36:03.349Z] echo "Nothing to be done for teardown."; \ [2025-12-13T13:36:03.349Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656311645582/TestTargetResult"; [2025-12-13T13:36:03.349Z] [2025-12-13T13:36:03.349Z] TEST SETUP: [2025-12-13T13:36:03.349Z] Nothing to be done for setup. [2025-12-13T13:36:03.349Z] [2025-12-13T13:36:03.349Z] TESTING: [2025-12-13T13:36:04.101Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-13T13:36:04.101Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_17656311645582/renaissance-movie-lens_0/launcher-133603-13072915194780973265/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-13T13:36:04.101Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-13T13:36:04.101Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-13T13:36:09.002Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-13T13:36:16.457Z] 13:36:15.757 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. [2025-12-13T13:36:19.497Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-13T13:36:20.255Z] Training: 60056, validation: 20285, test: 19854 [2025-12-13T13:36:20.255Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-13T13:36:20.603Z] GC before operation: completed in 166.813 ms, heap usage 218.570 MB -> 75.433 MB. [2025-12-13T13:36:28.038Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:36:33.018Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:36:36.916Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:36:40.791Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:36:42.489Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:36:44.194Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:36:46.527Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:36:48.247Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:36:48.247Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:36:48.247Z] The best model improves the baseline by 14.34%. [2025-12-13T13:36:48.594Z] Top recommended movies for user id 72: [2025-12-13T13:36:48.594Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:36:48.594Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:36:48.594Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:36:48.594Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:36:48.594Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:36:48.594Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27999.504 ms) ====== [2025-12-13T13:36:48.594Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-13T13:36:48.594Z] GC before operation: completed in 181.850 ms, heap usage 506.111 MB -> 91.712 MB. [2025-12-13T13:36:51.660Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:36:54.796Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:36:57.104Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:37:00.124Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:37:01.319Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:37:03.020Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:37:04.743Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:37:06.453Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:37:06.453Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:37:06.453Z] The best model improves the baseline by 14.34%. [2025-12-13T13:37:06.792Z] Top recommended movies for user id 72: [2025-12-13T13:37:06.792Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:37:06.792Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:37:06.792Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:37:06.792Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:37:06.792Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:37:06.792Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17977.713 ms) ====== [2025-12-13T13:37:06.792Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-13T13:37:06.792Z] GC before operation: completed in 167.398 ms, heap usage 447.377 MB -> 87.924 MB. [2025-12-13T13:37:09.811Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:37:12.147Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:37:15.205Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:37:17.622Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:37:19.397Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:37:20.584Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:37:22.290Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:37:23.990Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:37:24.329Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:37:24.329Z] The best model improves the baseline by 14.34%. [2025-12-13T13:37:24.329Z] Top recommended movies for user id 72: [2025-12-13T13:37:24.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:37:24.329Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:37:24.329Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:37:24.329Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:37:24.329Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:37:24.329Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17532.891 ms) ====== [2025-12-13T13:37:24.329Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-13T13:37:24.669Z] GC before operation: completed in 170.905 ms, heap usage 116.261 MB -> 87.998 MB. [2025-12-13T13:37:26.981Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:37:29.363Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:37:32.446Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:37:34.824Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:37:36.029Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:37:37.241Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:37:39.076Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:37:40.302Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:37:40.650Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:37:40.650Z] The best model improves the baseline by 14.34%. [2025-12-13T13:37:41.002Z] Top recommended movies for user id 72: [2025-12-13T13:37:41.002Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:37:41.002Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:37:41.002Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:37:41.002Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:37:41.002Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:37:41.002Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16286.668 ms) ====== [2025-12-13T13:37:41.002Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-13T13:37:41.002Z] GC before operation: completed in 171.349 ms, heap usage 419.584 MB -> 88.787 MB. [2025-12-13T13:37:44.116Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:37:46.494Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:37:48.911Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:37:51.341Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:37:53.079Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:37:54.273Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:37:56.020Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:37:57.236Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:37:57.236Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:37:57.236Z] The best model improves the baseline by 14.34%. [2025-12-13T13:37:57.581Z] Top recommended movies for user id 72: [2025-12-13T13:37:57.581Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:37:57.581Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:37:57.581Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:37:57.581Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:37:57.581Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:37:57.581Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16476.779 ms) ====== [2025-12-13T13:37:57.581Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-13T13:37:57.581Z] GC before operation: completed in 174.056 ms, heap usage 204.566 MB -> 88.317 MB. [2025-12-13T13:37:59.891Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:38:03.070Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:38:05.385Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:38:07.719Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:38:08.923Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:38:10.103Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:38:11.834Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:38:13.014Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:38:13.351Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:38:13.351Z] The best model improves the baseline by 14.34%. [2025-12-13T13:38:13.351Z] Top recommended movies for user id 72: [2025-12-13T13:38:13.351Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:38:13.351Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:38:13.351Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:38:13.351Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:38:13.351Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:38:13.351Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15724.697 ms) ====== [2025-12-13T13:38:13.351Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-13T13:38:13.688Z] GC before operation: completed in 162.654 ms, heap usage 115.833 MB -> 92.402 MB. [2025-12-13T13:38:16.010Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:38:18.323Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:38:20.639Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:38:23.045Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:38:24.806Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:38:26.541Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:38:27.724Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:38:29.426Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:38:29.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:38:29.426Z] The best model improves the baseline by 14.34%. [2025-12-13T13:38:29.768Z] Top recommended movies for user id 72: [2025-12-13T13:38:29.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:38:29.768Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:38:29.768Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:38:29.768Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:38:29.768Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:38:29.768Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16000.681 ms) ====== [2025-12-13T13:38:29.768Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-13T13:38:29.768Z] GC before operation: completed in 163.046 ms, heap usage 510.021 MB -> 92.420 MB. [2025-12-13T13:38:32.802Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:38:35.149Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:38:37.451Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:38:39.146Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:38:40.849Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:38:42.029Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:38:43.816Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:38:44.998Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:38:45.336Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:38:45.336Z] The best model improves the baseline by 14.34%. [2025-12-13T13:38:45.678Z] Top recommended movies for user id 72: [2025-12-13T13:38:45.678Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:38:45.678Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:38:45.678Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:38:45.678Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:38:45.678Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:38:45.678Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15755.386 ms) ====== [2025-12-13T13:38:45.678Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-13T13:38:45.678Z] GC before operation: completed in 155.363 ms, heap usage 421.419 MB -> 89.256 MB. [2025-12-13T13:38:47.977Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:38:50.287Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:38:52.592Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:38:54.914Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:38:56.093Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:38:57.804Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:38:59.058Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:39:00.771Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:39:00.771Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:39:00.771Z] The best model improves the baseline by 14.34%. [2025-12-13T13:39:01.112Z] Top recommended movies for user id 72: [2025-12-13T13:39:01.112Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:39:01.112Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:39:01.112Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:39:01.112Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:39:01.112Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:39:01.113Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15287.170 ms) ====== [2025-12-13T13:39:01.113Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-13T13:39:01.113Z] GC before operation: completed in 152.563 ms, heap usage 184.309 MB -> 88.773 MB. [2025-12-13T13:39:03.510Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:39:05.838Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:39:08.154Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:39:10.477Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:39:11.662Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:39:12.839Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:39:14.557Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:39:15.745Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:39:16.090Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:39:16.090Z] The best model improves the baseline by 14.34%. [2025-12-13T13:39:16.090Z] Top recommended movies for user id 72: [2025-12-13T13:39:16.090Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:39:16.090Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:39:16.090Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:39:16.090Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:39:16.090Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:39:16.090Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15034.061 ms) ====== [2025-12-13T13:39:16.090Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-13T13:39:16.452Z] GC before operation: completed in 151.526 ms, heap usage 705.358 MB -> 93.190 MB. [2025-12-13T13:39:18.767Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:39:21.109Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:39:23.433Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:39:25.846Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:39:27.043Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:39:28.745Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:39:29.924Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:39:31.128Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:39:31.475Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:39:31.475Z] The best model improves the baseline by 14.34%. [2025-12-13T13:39:31.822Z] Top recommended movies for user id 72: [2025-12-13T13:39:31.822Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:39:31.822Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:39:31.822Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:39:31.822Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:39:31.822Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:39:31.822Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15366.795 ms) ====== [2025-12-13T13:39:31.822Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-13T13:39:31.822Z] GC before operation: completed in 144.669 ms, heap usage 403.340 MB -> 89.098 MB. [2025-12-13T13:39:34.145Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:39:36.472Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:39:38.832Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:39:41.183Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:39:42.360Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:39:43.556Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:39:45.270Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:39:46.496Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:39:46.496Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:39:46.496Z] The best model improves the baseline by 14.34%. [2025-12-13T13:39:46.921Z] Top recommended movies for user id 72: [2025-12-13T13:39:46.921Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:39:46.921Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:39:46.921Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:39:46.921Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:39:46.921Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:39:46.921Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14886.080 ms) ====== [2025-12-13T13:39:46.921Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-13T13:39:46.921Z] GC before operation: completed in 142.794 ms, heap usage 169.183 MB -> 88.860 MB. [2025-12-13T13:39:49.221Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:39:51.533Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:39:53.857Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:39:56.186Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:39:57.368Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:39:58.564Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:40:00.270Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:40:01.467Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:40:01.467Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:40:01.468Z] The best model improves the baseline by 14.34%. [2025-12-13T13:40:01.866Z] Top recommended movies for user id 72: [2025-12-13T13:40:01.866Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:40:01.866Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:40:01.866Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:40:01.866Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:40:01.866Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:40:01.866Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14888.914 ms) ====== [2025-12-13T13:40:01.866Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-13T13:40:01.866Z] GC before operation: completed in 148.201 ms, heap usage 443.659 MB -> 89.495 MB. [2025-12-13T13:40:04.205Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:40:06.570Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:40:09.107Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:40:11.464Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:40:12.697Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:40:13.922Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:40:15.677Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:40:16.919Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:40:17.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:40:17.290Z] The best model improves the baseline by 14.34%. [2025-12-13T13:40:17.290Z] Top recommended movies for user id 72: [2025-12-13T13:40:17.290Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:40:17.290Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:40:17.290Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:40:17.290Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:40:17.290Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:40:17.290Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15441.910 ms) ====== [2025-12-13T13:40:17.290Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-13T13:40:17.659Z] GC before operation: completed in 144.760 ms, heap usage 313.786 MB -> 89.114 MB. [2025-12-13T13:40:20.071Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:40:21.886Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:40:24.237Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:40:26.624Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:40:27.834Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:40:29.048Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:40:30.295Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:40:31.999Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:40:31.999Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:40:31.999Z] The best model improves the baseline by 14.34%. [2025-12-13T13:40:31.999Z] Top recommended movies for user id 72: [2025-12-13T13:40:31.999Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:40:31.999Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:40:31.999Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:40:31.999Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:40:31.999Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:40:31.999Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14644.969 ms) ====== [2025-12-13T13:40:31.999Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-13T13:40:32.345Z] GC before operation: completed in 150.890 ms, heap usage 443.797 MB -> 89.529 MB. [2025-12-13T13:40:34.674Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:40:36.509Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:40:38.841Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:40:41.218Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:40:42.431Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:40:43.621Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:40:45.356Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:40:47.097Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:40:47.097Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:40:47.097Z] The best model improves the baseline by 14.34%. [2025-12-13T13:40:47.097Z] Top recommended movies for user id 72: [2025-12-13T13:40:47.097Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:40:47.097Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:40:47.097Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:40:47.097Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:40:47.097Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:40:47.097Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14930.810 ms) ====== [2025-12-13T13:40:47.097Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-13T13:40:47.448Z] GC before operation: completed in 146.480 ms, heap usage 414.092 MB -> 89.309 MB. [2025-12-13T13:40:49.805Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:40:52.129Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:40:54.457Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:40:56.176Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:40:57.367Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:40:59.065Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:41:00.244Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:41:01.420Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:41:01.780Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:41:01.781Z] The best model improves the baseline by 14.34%. [2025-12-13T13:41:01.781Z] Top recommended movies for user id 72: [2025-12-13T13:41:01.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:41:01.781Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:41:01.781Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:41:01.781Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:41:01.781Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:41:01.781Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14585.432 ms) ====== [2025-12-13T13:41:01.781Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-13T13:41:02.125Z] GC before operation: completed in 152.228 ms, heap usage 655.337 MB -> 93.105 MB. [2025-12-13T13:41:04.466Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:41:06.806Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:41:09.166Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:41:10.889Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:41:12.662Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:41:13.849Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:41:15.542Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:41:16.712Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:41:16.712Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:41:16.712Z] The best model improves the baseline by 14.34%. [2025-12-13T13:41:17.051Z] Top recommended movies for user id 72: [2025-12-13T13:41:17.051Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:41:17.051Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:41:17.051Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:41:17.051Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:41:17.051Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:41:17.051Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14889.317 ms) ====== [2025-12-13T13:41:17.051Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-13T13:41:17.051Z] GC before operation: completed in 144.453 ms, heap usage 178.415 MB -> 88.875 MB. [2025-12-13T13:41:19.421Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:41:21.725Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:41:24.060Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:41:25.768Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:41:27.501Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:41:28.737Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:41:29.952Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:41:31.666Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:41:31.666Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:41:31.666Z] The best model improves the baseline by 14.34%. [2025-12-13T13:41:31.666Z] Top recommended movies for user id 72: [2025-12-13T13:41:31.666Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:41:31.666Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:41:31.666Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:41:31.666Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:41:31.666Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:41:31.666Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14612.625 ms) ====== [2025-12-13T13:41:31.666Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-13T13:41:32.100Z] GC before operation: completed in 146.946 ms, heap usage 213.807 MB -> 89.044 MB. [2025-12-13T13:41:34.475Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T13:41:36.215Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T13:41:38.527Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T13:41:40.862Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T13:41:42.083Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T13:41:43.269Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T13:41:44.444Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T13:41:45.635Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T13:41:45.979Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-13T13:41:45.979Z] The best model improves the baseline by 14.34%. [2025-12-13T13:41:46.330Z] Top recommended movies for user id 72: [2025-12-13T13:41:46.330Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T13:41:46.330Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T13:41:46.330Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T13:41:46.330Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T13:41:46.330Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T13:41:46.330Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14339.874 ms) ====== [2025-12-13T13:41:46.669Z] ----------------------------------- [2025-12-13T13:41:46.669Z] renaissance-movie-lens_0_PASSED [2025-12-13T13:41:46.669Z] ----------------------------------- [2025-12-13T13:41:46.669Z] [2025-12-13T13:41:46.669Z] TEST TEARDOWN: [2025-12-13T13:41:46.669Z] Nothing to be done for teardown. [2025-12-13T13:41:46.669Z] renaissance-movie-lens_0 Finish Time: Sat Dec 13 13:41:46 2025 Epoch Time (ms): 1765633306447