[2025-12-27T13:34:39.373Z] Running test renaissance-movie-lens_0 ... [2025-12-27T13:34:39.373Z] =============================================== [2025-12-27T13:34:39.373Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 13:34:39 2025 Epoch Time (ms): 1766842479169 [2025-12-27T13:34:39.373Z] variation: NoOptions [2025-12-27T13:34:39.373Z] JVM_OPTIONS: [2025-12-27T13:34:39.373Z] { \ [2025-12-27T13:34:39.373Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T13:34:39.373Z] echo "Nothing to be done for setup."; \ [2025-12-27T13:34:39.373Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668406205434/renaissance-movie-lens_0"; \ [2025-12-27T13:34:39.373Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668406205434/renaissance-movie-lens_0"; \ [2025-12-27T13:34:39.373Z] echo ""; echo "TESTING:"; \ [2025-12-27T13:34:39.373Z] "/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_17668406205434/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T13:34:39.373Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668406205434/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T13:34:39.373Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T13:34:39.373Z] echo "Nothing to be done for teardown."; \ [2025-12-27T13:34:39.373Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668406205434/TestTargetResult"; [2025-12-27T13:34:39.373Z] [2025-12-27T13:34:39.373Z] TEST SETUP: [2025-12-27T13:34:39.373Z] Nothing to be done for setup. [2025-12-27T13:34:39.373Z] [2025-12-27T13:34:39.373Z] TESTING: [2025-12-27T13:34:39.711Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T13:34:39.711Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_17668406205434/renaissance-movie-lens_0/launcher-133439-3456786185326092683/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T13:34:39.711Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T13:34:39.711Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T13:34:44.533Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-27T13:34:51.961Z] 13:34:51.681 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. [2025-12-27T13:34:54.966Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T13:34:55.691Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T13:34:55.691Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T13:34:55.691Z] GC before operation: completed in 165.340 ms, heap usage 268.308 MB -> 75.326 MB. [2025-12-27T13:35:04.677Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:35:09.493Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:35:16.832Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:35:19.832Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:35:22.916Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:35:25.211Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:35:26.904Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:35:28.589Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:35:28.922Z] 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. [2025-12-27T13:35:28.922Z] The best model improves the baseline by 14.34%. [2025-12-27T13:35:29.262Z] Top recommended movies for user id 72: [2025-12-27T13:35:29.262Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:35:29.262Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:35:29.262Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:35:29.262Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:35:29.262Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:35:29.262Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33327.249 ms) ====== [2025-12-27T13:35:29.262Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T13:35:29.262Z] GC before operation: completed in 176.756 ms, heap usage 371.957 MB -> 89.040 MB. [2025-12-27T13:35:33.106Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:35:35.394Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:35:38.392Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:35:41.390Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:35:42.560Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:35:44.245Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:35:46.027Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:35:47.272Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:35:47.610Z] 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. [2025-12-27T13:35:47.610Z] The best model improves the baseline by 14.34%. [2025-12-27T13:35:47.956Z] Top recommended movies for user id 72: [2025-12-27T13:35:47.956Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:35:47.956Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:35:47.956Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:35:47.956Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:35:47.956Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:35:47.956Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18558.234 ms) ====== [2025-12-27T13:35:47.956Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T13:35:47.956Z] GC before operation: completed in 165.105 ms, heap usage 436.066 MB -> 87.787 MB. [2025-12-27T13:35:50.950Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:35:53.242Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:35:56.234Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:35:58.580Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:36:00.268Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:36:01.434Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:36:03.735Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:36:05.422Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:36:05.422Z] 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. [2025-12-27T13:36:05.422Z] The best model improves the baseline by 14.34%. [2025-12-27T13:36:05.757Z] Top recommended movies for user id 72: [2025-12-27T13:36:05.757Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:36:05.757Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:36:05.757Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:36:05.757Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:36:05.757Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:36:05.757Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17574.501 ms) ====== [2025-12-27T13:36:05.757Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T13:36:05.757Z] GC before operation: completed in 162.578 ms, heap usage 245.021 MB -> 88.071 MB. [2025-12-27T13:36:08.828Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:36:11.116Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:36:13.405Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:36:15.691Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:36:17.369Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:36:18.561Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:36:20.246Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:36:21.933Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:36:21.933Z] 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. [2025-12-27T13:36:21.933Z] The best model improves the baseline by 14.34%. [2025-12-27T13:36:22.271Z] Top recommended movies for user id 72: [2025-12-27T13:36:22.271Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:36:22.271Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:36:22.271Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:36:22.271Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:36:22.271Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:36:22.271Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16370.606 ms) ====== [2025-12-27T13:36:22.271Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T13:36:22.271Z] GC before operation: completed in 164.731 ms, heap usage 512.554 MB -> 91.966 MB. [2025-12-27T13:36:25.262Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:36:27.583Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:36:29.934Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:36:32.221Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:36:33.921Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:36:35.088Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:36:36.776Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:36:38.463Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:36:38.463Z] 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. [2025-12-27T13:36:38.463Z] The best model improves the baseline by 14.34%. [2025-12-27T13:36:38.797Z] Top recommended movies for user id 72: [2025-12-27T13:36:38.797Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:36:38.797Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:36:38.797Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:36:38.797Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:36:38.797Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:36:38.797Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16531.786 ms) ====== [2025-12-27T13:36:38.797Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T13:36:39.135Z] GC before operation: completed in 159.695 ms, heap usage 150.027 MB -> 88.172 MB. [2025-12-27T13:36:41.428Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:36:44.418Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:36:46.700Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:36:48.988Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:36:50.154Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:36:51.411Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:36:53.090Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:36:54.775Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:36:54.775Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-27T13:36:54.775Z] The best model improves the baseline by 14.34%. [2025-12-27T13:36:54.775Z] Top recommended movies for user id 72: [2025-12-27T13:36:54.775Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:36:54.775Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:36:54.775Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:36:54.775Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:36:54.775Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:36:54.775Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15865.013 ms) ====== [2025-12-27T13:36:54.775Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T13:36:55.109Z] GC before operation: completed in 164.587 ms, heap usage 644.111 MB -> 92.541 MB. [2025-12-27T13:36:57.392Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:36:59.679Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:37:02.682Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:37:04.966Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:37:06.133Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:37:07.815Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:37:09.504Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:37:10.669Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:37:11.002Z] 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. [2025-12-27T13:37:11.002Z] The best model improves the baseline by 14.34%. [2025-12-27T13:37:11.002Z] Top recommended movies for user id 72: [2025-12-27T13:37:11.002Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:37:11.002Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:37:11.002Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:37:11.002Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:37:11.002Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:37:11.002Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16053.247 ms) ====== [2025-12-27T13:37:11.002Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T13:37:11.405Z] GC before operation: completed in 162.755 ms, heap usage 399.760 MB -> 88.890 MB. [2025-12-27T13:37:13.691Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:37:15.979Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:37:18.265Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:37:20.547Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:37:22.234Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:37:23.919Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:37:25.601Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:37:26.769Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:37:27.105Z] 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. [2025-12-27T13:37:27.105Z] The best model improves the baseline by 14.34%. [2025-12-27T13:37:27.443Z] Top recommended movies for user id 72: [2025-12-27T13:37:27.443Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:37:27.443Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:37:27.443Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:37:27.443Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:37:27.443Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:37:27.443Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16061.096 ms) ====== [2025-12-27T13:37:27.443Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T13:37:27.443Z] GC before operation: completed in 150.104 ms, heap usage 218.969 MB -> 88.799 MB. [2025-12-27T13:37:29.730Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:37:32.831Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:37:35.117Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:37:36.803Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:37:38.482Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:37:39.651Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:37:41.339Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:37:43.021Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:37:43.021Z] 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. [2025-12-27T13:37:43.021Z] The best model improves the baseline by 14.34%. [2025-12-27T13:37:43.357Z] Top recommended movies for user id 72: [2025-12-27T13:37:43.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:37:43.357Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:37:43.357Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:37:43.357Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:37:43.357Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:37:43.357Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15815.060 ms) ====== [2025-12-27T13:37:43.357Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T13:37:43.357Z] GC before operation: completed in 154.839 ms, heap usage 394.505 MB -> 88.968 MB. [2025-12-27T13:37:46.354Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:37:48.042Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:37:51.030Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:37:52.709Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:37:54.389Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:37:55.630Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:37:56.796Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:37:58.477Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:37:58.812Z] 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. [2025-12-27T13:37:58.812Z] The best model improves the baseline by 14.34%. [2025-12-27T13:37:58.812Z] Top recommended movies for user id 72: [2025-12-27T13:37:58.812Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:37:58.812Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:37:58.812Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:37:58.812Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:37:58.812Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:37:58.812Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15401.686 ms) ====== [2025-12-27T13:37:58.812Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T13:37:59.152Z] GC before operation: completed in 159.813 ms, heap usage 594.804 MB -> 92.728 MB. [2025-12-27T13:38:01.448Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:38:03.748Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:38:06.029Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:38:08.318Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:38:09.998Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:38:11.165Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:38:12.854Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:38:14.021Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:38:14.355Z] 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. [2025-12-27T13:38:14.355Z] The best model improves the baseline by 14.34%. [2025-12-27T13:38:14.355Z] Top recommended movies for user id 72: [2025-12-27T13:38:14.355Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:38:14.355Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:38:14.355Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:38:14.355Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:38:14.355Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:38:14.355Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15411.393 ms) ====== [2025-12-27T13:38:14.355Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T13:38:14.691Z] GC before operation: completed in 154.951 ms, heap usage 363.566 MB -> 88.958 MB. [2025-12-27T13:38:16.991Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:38:19.279Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:38:21.579Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:38:23.888Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:38:25.070Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:38:26.758Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:38:27.927Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:38:29.616Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:38:29.616Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-27T13:38:29.616Z] The best model improves the baseline by 14.34%. [2025-12-27T13:38:29.616Z] Top recommended movies for user id 72: [2025-12-27T13:38:29.616Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:38:29.616Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:38:29.616Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:38:29.616Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:38:29.616Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:38:29.616Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15128.932 ms) ====== [2025-12-27T13:38:29.616Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T13:38:29.954Z] GC before operation: completed in 152.846 ms, heap usage 157.254 MB -> 88.734 MB. [2025-12-27T13:38:32.237Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:38:34.536Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:38:36.821Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:38:39.185Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:38:40.346Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:38:41.510Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:38:43.191Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:38:44.909Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:38:44.909Z] 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. [2025-12-27T13:38:44.909Z] The best model improves the baseline by 14.34%. [2025-12-27T13:38:44.909Z] Top recommended movies for user id 72: [2025-12-27T13:38:44.909Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:38:44.909Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:38:44.909Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:38:44.909Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:38:44.909Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:38:44.909Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15163.695 ms) ====== [2025-12-27T13:38:44.909Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T13:38:45.244Z] GC before operation: completed in 159.235 ms, heap usage 602.615 MB -> 92.799 MB. [2025-12-27T13:38:47.531Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:38:49.825Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:38:52.822Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:38:54.503Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:38:56.190Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:38:57.352Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:38:58.518Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:39:00.285Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:39:00.285Z] 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. [2025-12-27T13:39:00.285Z] The best model improves the baseline by 14.34%. [2025-12-27T13:39:00.285Z] Top recommended movies for user id 72: [2025-12-27T13:39:00.285Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:39:00.285Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:39:00.285Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:39:00.285Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:39:00.285Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:39:00.285Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15230.105 ms) ====== [2025-12-27T13:39:00.285Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T13:39:00.636Z] GC before operation: completed in 153.459 ms, heap usage 223.928 MB -> 88.750 MB. [2025-12-27T13:39:02.955Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:39:05.281Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:39:07.587Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:39:09.877Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:39:11.038Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:39:12.210Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:39:13.433Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:39:15.108Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:39:15.108Z] 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. [2025-12-27T13:39:15.108Z] The best model improves the baseline by 14.34%. [2025-12-27T13:39:15.108Z] Top recommended movies for user id 72: [2025-12-27T13:39:15.108Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:39:15.108Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:39:15.108Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:39:15.108Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:39:15.108Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:39:15.108Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14613.038 ms) ====== [2025-12-27T13:39:15.108Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T13:39:15.442Z] GC before operation: completed in 159.867 ms, heap usage 655.492 MB -> 92.996 MB. [2025-12-27T13:39:17.734Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:39:20.020Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:39:22.404Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:39:24.692Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:39:25.857Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:39:27.024Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:39:28.716Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:39:29.906Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:39:30.243Z] 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. [2025-12-27T13:39:30.243Z] The best model improves the baseline by 14.34%. [2025-12-27T13:39:30.243Z] Top recommended movies for user id 72: [2025-12-27T13:39:30.243Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:39:30.243Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:39:30.243Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:39:30.243Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:39:30.243Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:39:30.243Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14932.268 ms) ====== [2025-12-27T13:39:30.243Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T13:39:30.586Z] GC before operation: completed in 155.324 ms, heap usage 208.351 MB -> 88.778 MB. [2025-12-27T13:39:32.879Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:39:35.187Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:39:37.495Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:39:39.805Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:39:40.988Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:39:42.283Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:39:43.456Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:39:45.137Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:39:45.137Z] 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. [2025-12-27T13:39:45.137Z] The best model improves the baseline by 14.34%. [2025-12-27T13:39:45.137Z] Top recommended movies for user id 72: [2025-12-27T13:39:45.137Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:39:45.137Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:39:45.137Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:39:45.137Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:39:45.137Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:39:45.137Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14802.139 ms) ====== [2025-12-27T13:39:45.137Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T13:39:45.476Z] GC before operation: completed in 156.284 ms, heap usage 115.421 MB -> 91.478 MB. [2025-12-27T13:39:47.776Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:39:50.099Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:39:52.447Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:39:54.194Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:39:55.386Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:39:57.137Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:39:58.317Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:40:00.013Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:40:00.014Z] 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. [2025-12-27T13:40:00.014Z] The best model improves the baseline by 14.34%. [2025-12-27T13:40:00.014Z] Top recommended movies for user id 72: [2025-12-27T13:40:00.014Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:40:00.014Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:40:00.014Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:40:00.014Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:40:00.014Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:40:00.014Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14664.188 ms) ====== [2025-12-27T13:40:00.014Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T13:40:00.374Z] GC before operation: completed in 165.794 ms, heap usage 616.487 MB -> 92.599 MB. [2025-12-27T13:40:02.790Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:40:04.720Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:40:07.060Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:40:09.410Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:40:10.616Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:40:11.815Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:40:13.037Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:40:14.786Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:40:14.786Z] 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. [2025-12-27T13:40:14.786Z] The best model improves the baseline by 14.34%. [2025-12-27T13:40:14.786Z] Top recommended movies for user id 72: [2025-12-27T13:40:14.786Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:40:14.786Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:40:14.786Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:40:14.786Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:40:14.786Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:40:14.786Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14653.539 ms) ====== [2025-12-27T13:40:14.786Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T13:40:15.139Z] GC before operation: completed in 156.264 ms, heap usage 363.781 MB -> 89.129 MB. [2025-12-27T13:40:17.484Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:40:19.825Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:40:22.140Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:40:23.870Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:40:25.039Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:40:26.308Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:40:28.016Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:40:29.226Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:40:29.572Z] 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. [2025-12-27T13:40:29.573Z] The best model improves the baseline by 14.34%. [2025-12-27T13:40:29.573Z] Top recommended movies for user id 72: [2025-12-27T13:40:29.573Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T13:40:29.573Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T13:40:29.573Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T13:40:29.573Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T13:40:29.573Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T13:40:29.573Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14495.625 ms) ====== [2025-12-27T13:40:29.917Z] ----------------------------------- [2025-12-27T13:40:29.917Z] renaissance-movie-lens_0_PASSED [2025-12-27T13:40:29.918Z] ----------------------------------- [2025-12-27T13:40:29.918Z] [2025-12-27T13:40:29.918Z] TEST TEARDOWN: [2025-12-27T13:40:29.918Z] Nothing to be done for teardown. [2025-12-27T13:40:29.918Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 13:40:29 2025 Epoch Time (ms): 1766842829798