Test Results Summary Service

renaissance-movie-lens_0

[2025-12-27T14:23:37.110Z] Running test renaissance-movie-lens_0 ... [2025-12-27T14:23:37.110Z] =============================================== [2025-12-27T14:23:37.110Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 14:23:35 2025 Epoch Time (ms): 1766845415959 [2025-12-27T14:23:37.110Z] variation: NoOptions [2025-12-27T14:23:37.110Z] JVM_OPTIONS: [2025-12-27T14:23:37.110Z] { \ [2025-12-27T14:23:37.110Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T14:23:37.110Z] echo "Nothing to be done for setup."; \ [2025-12-27T14:23:37.110Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668443397974/renaissance-movie-lens_0"; \ [2025-12-27T14:23:37.110Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668443397974/renaissance-movie-lens_0"; \ [2025-12-27T14:23:37.110Z] echo ""; echo "TESTING:"; \ [2025-12-27T14:23:37.110Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/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_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668443397974/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T14:23:37.110Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668443397974/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T14:23:37.110Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T14:23:37.110Z] echo "Nothing to be done for teardown."; \ [2025-12-27T14:23:37.110Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668443397974/TestTargetResult"; [2025-12-27T14:23:37.110Z] [2025-12-27T14:23:37.110Z] TEST SETUP: [2025-12-27T14:23:37.110Z] Nothing to be done for setup. [2025-12-27T14:23:37.110Z] [2025-12-27T14:23:37.110Z] TESTING: [2025-12-27T14:23:37.110Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T14:23:37.110Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/output_17668443397974/renaissance-movie-lens_0/launcher-142336-10924876857405578397/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T14:23:37.110Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T14:23:37.110Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T14:23:41.302Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-27T14:23:48.053Z] 14:23:47.623 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-27T14:23:50.036Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T14:23:50.997Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T14:23:50.997Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T14:23:50.997Z] GC before operation: completed in 147.213 ms, heap usage 384.000 MB -> 75.914 MB. [2025-12-27T14:23:56.418Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:23:59.489Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:24:01.641Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:24:04.690Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:24:06.667Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:24:08.656Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:24:09.618Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:24:11.592Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:24:11.592Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:24:11.592Z] The best model improves the baseline by 14.52%. [2025-12-27T14:24:12.554Z] Top recommended movies for user id 72: [2025-12-27T14:24:12.554Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:24:12.554Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:24:12.554Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:24:12.554Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:24:12.554Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:24:12.554Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21314.365 ms) ====== [2025-12-27T14:24:12.554Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T14:24:12.554Z] GC before operation: completed in 159.364 ms, heap usage 109.054 MB -> 89.279 MB. [2025-12-27T14:24:15.600Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:24:17.584Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:24:20.631Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:24:22.604Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:24:24.578Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:24:26.557Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:24:27.522Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:24:29.502Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:24:29.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:24:29.502Z] The best model improves the baseline by 14.52%. [2025-12-27T14:24:29.502Z] Top recommended movies for user id 72: [2025-12-27T14:24:29.502Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:24:29.502Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:24:29.502Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:24:29.502Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:24:29.502Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:24:29.502Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17488.712 ms) ====== [2025-12-27T14:24:29.502Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T14:24:30.465Z] GC before operation: completed in 132.828 ms, heap usage 545.634 MB -> 92.055 MB. [2025-12-27T14:24:32.443Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:24:35.491Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:24:37.467Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:24:39.440Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:24:41.419Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:24:43.717Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:24:44.680Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:24:45.644Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:24:46.606Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:24:46.606Z] The best model improves the baseline by 14.52%. [2025-12-27T14:24:46.606Z] Top recommended movies for user id 72: [2025-12-27T14:24:46.606Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:24:46.606Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:24:46.606Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:24:46.606Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:24:46.606Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:24:46.606Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16618.161 ms) ====== [2025-12-27T14:24:46.606Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T14:24:46.606Z] GC before operation: completed in 124.206 ms, heap usage 126.644 MB -> 89.133 MB. [2025-12-27T14:24:48.649Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:24:51.696Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:24:53.672Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:24:55.649Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:24:56.610Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:24:58.586Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:24:59.548Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:25:01.642Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:25:01.642Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:25:01.642Z] The best model improves the baseline by 14.52%. [2025-12-27T14:25:01.642Z] Top recommended movies for user id 72: [2025-12-27T14:25:01.642Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:25:01.642Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:25:01.642Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:25:01.642Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:25:01.642Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:25:01.642Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14819.884 ms) ====== [2025-12-27T14:25:01.642Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T14:25:01.642Z] GC before operation: completed in 144.950 ms, heap usage 621.796 MB -> 93.289 MB. [2025-12-27T14:25:04.696Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:25:06.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:25:08.644Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:25:10.619Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:25:12.598Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:25:13.562Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:25:15.542Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:25:16.504Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:25:17.468Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:25:17.468Z] The best model improves the baseline by 14.52%. [2025-12-27T14:25:17.468Z] Top recommended movies for user id 72: [2025-12-27T14:25:17.468Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:25:17.468Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:25:17.468Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:25:17.468Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:25:17.468Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:25:17.468Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15601.529 ms) ====== [2025-12-27T14:25:17.468Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T14:25:17.468Z] GC before operation: completed in 132.241 ms, heap usage 370.938 MB -> 89.732 MB. [2025-12-27T14:25:19.444Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:25:22.494Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:25:24.471Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:25:26.449Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:25:28.424Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:25:29.386Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:25:31.364Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:25:32.329Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:25:32.329Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:25:32.329Z] The best model improves the baseline by 14.52%. [2025-12-27T14:25:32.329Z] Top recommended movies for user id 72: [2025-12-27T14:25:32.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:25:32.329Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:25:32.329Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:25:32.329Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:25:32.329Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:25:32.329Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15139.566 ms) ====== [2025-12-27T14:25:32.329Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T14:25:32.329Z] GC before operation: completed in 137.400 ms, heap usage 406.360 MB -> 89.995 MB. [2025-12-27T14:25:35.383Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:25:37.363Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:25:39.375Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:25:42.608Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:25:43.569Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:25:44.548Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:25:46.530Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:25:47.491Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:25:47.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:25:47.491Z] The best model improves the baseline by 14.52%. [2025-12-27T14:25:47.491Z] Top recommended movies for user id 72: [2025-12-27T14:25:47.491Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:25:47.491Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:25:47.491Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:25:47.491Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:25:47.491Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:25:47.491Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15158.995 ms) ====== [2025-12-27T14:25:47.491Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T14:25:48.453Z] GC before operation: completed in 130.233 ms, heap usage 300.970 MB -> 89.811 MB. [2025-12-27T14:25:50.428Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:25:52.406Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:25:54.388Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:25:56.362Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:25:58.336Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:25:59.298Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:26:02.385Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:26:02.385Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:26:02.385Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:26:02.385Z] The best model improves the baseline by 14.52%. [2025-12-27T14:26:02.385Z] Top recommended movies for user id 72: [2025-12-27T14:26:02.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:26:02.385Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:26:02.385Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:26:02.385Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:26:02.385Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:26:02.385Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14771.345 ms) ====== [2025-12-27T14:26:02.385Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T14:26:03.348Z] GC before operation: completed in 159.511 ms, heap usage 401.109 MB -> 90.159 MB. [2025-12-27T14:26:05.322Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:26:07.298Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:26:10.345Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:26:12.328Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:26:13.289Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:26:15.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:26:16.227Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:26:17.189Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:26:18.153Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:26:18.153Z] The best model improves the baseline by 14.52%. [2025-12-27T14:26:18.153Z] Top recommended movies for user id 72: [2025-12-27T14:26:18.153Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:26:18.153Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:26:18.153Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:26:18.153Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:26:18.153Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:26:18.153Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15068.819 ms) ====== [2025-12-27T14:26:18.153Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T14:26:18.153Z] GC before operation: completed in 126.774 ms, heap usage 447.051 MB -> 90.093 MB. [2025-12-27T14:26:20.128Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:26:22.105Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:26:24.086Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:26:26.061Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:26:28.035Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:26:28.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:26:29.961Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:26:31.936Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:26:31.936Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:26:31.936Z] The best model improves the baseline by 14.52%. [2025-12-27T14:26:31.936Z] Top recommended movies for user id 72: [2025-12-27T14:26:31.936Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:26:31.936Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:26:31.936Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:26:31.936Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:26:31.936Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:26:31.936Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13733.854 ms) ====== [2025-12-27T14:26:31.936Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T14:26:31.936Z] GC before operation: completed in 137.233 ms, heap usage 517.242 MB -> 90.416 MB. [2025-12-27T14:26:33.911Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:26:35.895Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:26:38.946Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:26:40.921Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:26:41.884Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:26:42.848Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:26:44.825Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:26:45.823Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:26:45.823Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:26:45.823Z] The best model improves the baseline by 14.52%. [2025-12-27T14:26:45.823Z] Top recommended movies for user id 72: [2025-12-27T14:26:45.823Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:26:45.823Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:26:45.823Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:26:45.823Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:26:45.823Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:26:45.823Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14164.572 ms) ====== [2025-12-27T14:26:45.823Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T14:26:46.787Z] GC before operation: completed in 132.678 ms, heap usage 282.682 MB -> 89.835 MB. [2025-12-27T14:26:48.764Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:26:50.739Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:26:52.719Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:26:54.693Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:26:56.677Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:26:57.646Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:26:59.622Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:27:00.631Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:27:00.631Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:27:00.631Z] The best model improves the baseline by 14.52%. [2025-12-27T14:27:00.631Z] Top recommended movies for user id 72: [2025-12-27T14:27:00.631Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:27:00.631Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:27:00.631Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:27:00.631Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:27:00.631Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:27:00.631Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14553.780 ms) ====== [2025-12-27T14:27:00.631Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T14:27:00.631Z] GC before operation: completed in 129.440 ms, heap usage 424.070 MB -> 90.193 MB. [2025-12-27T14:27:03.687Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:27:05.662Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:27:07.637Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:27:09.613Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:27:11.589Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:27:12.554Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:27:14.534Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:27:15.498Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:27:16.460Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:27:16.460Z] The best model improves the baseline by 14.52%. [2025-12-27T14:27:16.460Z] Top recommended movies for user id 72: [2025-12-27T14:27:16.460Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:27:16.460Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:27:16.460Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:27:16.460Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:27:16.460Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:27:16.460Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15172.062 ms) ====== [2025-12-27T14:27:16.460Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T14:27:16.460Z] GC before operation: completed in 154.932 ms, heap usage 162.904 MB -> 90.103 MB. [2025-12-27T14:27:18.437Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:27:20.418Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:27:23.864Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:27:24.827Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:27:26.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:27:27.769Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:27:29.747Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:27:30.711Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:27:30.711Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:27:31.673Z] The best model improves the baseline by 14.52%. [2025-12-27T14:27:31.673Z] Top recommended movies for user id 72: [2025-12-27T14:27:31.673Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:27:31.673Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:27:31.673Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:27:31.673Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:27:31.673Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:27:31.673Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14958.919 ms) ====== [2025-12-27T14:27:31.673Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T14:27:31.673Z] GC before operation: completed in 125.957 ms, heap usage 340.942 MB -> 90.036 MB. [2025-12-27T14:27:33.650Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:27:35.626Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:27:38.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:27:40.648Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:27:41.611Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:27:43.590Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:27:44.553Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:27:45.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:27:46.479Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:27:46.479Z] The best model improves the baseline by 14.52%. [2025-12-27T14:27:46.479Z] Top recommended movies for user id 72: [2025-12-27T14:27:46.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:27:46.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:27:46.480Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:27:46.480Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:27:46.480Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:27:46.480Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14867.827 ms) ====== [2025-12-27T14:27:46.480Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T14:27:46.480Z] GC before operation: completed in 150.069 ms, heap usage 332.784 MB -> 90.304 MB. [2025-12-27T14:27:48.458Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:27:51.508Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:27:53.485Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:27:55.462Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:27:56.426Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:27:58.401Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:27:59.380Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:28:01.468Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:28:01.468Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:28:01.468Z] The best model improves the baseline by 14.52%. [2025-12-27T14:28:01.468Z] Top recommended movies for user id 72: [2025-12-27T14:28:01.468Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:28:01.468Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:28:01.468Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:28:01.468Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:28:01.468Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:28:01.468Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15276.319 ms) ====== [2025-12-27T14:28:01.468Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T14:28:01.469Z] GC before operation: completed in 132.680 ms, heap usage 95.169 MB -> 90.066 MB. [2025-12-27T14:28:04.526Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:28:06.504Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:28:08.482Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:28:10.460Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:28:12.442Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:28:13.407Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:28:15.384Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:28:16.347Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:28:16.347Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:28:16.347Z] The best model improves the baseline by 14.52%. [2025-12-27T14:28:17.310Z] Top recommended movies for user id 72: [2025-12-27T14:28:17.310Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:28:17.310Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:28:17.310Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:28:17.310Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:28:17.310Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:28:17.310Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15034.004 ms) ====== [2025-12-27T14:28:17.310Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T14:28:17.310Z] GC before operation: completed in 128.483 ms, heap usage 367.422 MB -> 90.313 MB. [2025-12-27T14:28:19.289Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:28:21.270Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:28:23.250Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:28:25.228Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:28:27.207Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:28:28.172Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:28:29.150Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:28:30.113Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:28:31.079Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:28:31.079Z] The best model improves the baseline by 14.52%. [2025-12-27T14:28:31.080Z] Top recommended movies for user id 72: [2025-12-27T14:28:31.080Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:28:31.080Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:28:31.080Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:28:31.080Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:28:31.080Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:28:31.080Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13830.114 ms) ====== [2025-12-27T14:28:31.080Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T14:28:31.080Z] GC before operation: completed in 142.656 ms, heap usage 624.221 MB -> 93.652 MB. [2025-12-27T14:28:33.057Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:28:35.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:28:38.082Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:28:40.062Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:28:41.027Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:28:41.991Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:28:43.971Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:28:44.936Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:28:44.936Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:28:44.936Z] The best model improves the baseline by 14.52%. [2025-12-27T14:28:44.936Z] Top recommended movies for user id 72: [2025-12-27T14:28:44.936Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:28:44.936Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:28:44.936Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:28:44.936Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:28:44.936Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:28:44.936Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14302.693 ms) ====== [2025-12-27T14:28:44.936Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T14:28:46.914Z] GC before operation: completed in 139.398 ms, heap usage 270.708 MB -> 90.136 MB. [2025-12-27T14:28:47.933Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:28:49.918Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:28:51.899Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:28:53.880Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:28:54.845Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:28:56.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:28:57.790Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:28:58.753Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:28:59.717Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T14:28:59.717Z] The best model improves the baseline by 14.52%. [2025-12-27T14:28:59.717Z] Top recommended movies for user id 72: [2025-12-27T14:28:59.717Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T14:28:59.717Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T14:28:59.717Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T14:28:59.717Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T14:28:59.717Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T14:28:59.717Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14085.734 ms) ====== [2025-12-27T14:28:59.717Z] ----------------------------------- [2025-12-27T14:28:59.717Z] renaissance-movie-lens_0_PASSED [2025-12-27T14:28:59.717Z] ----------------------------------- [2025-12-27T14:28:59.717Z] [2025-12-27T14:28:59.717Z] TEST TEARDOWN: [2025-12-27T14:28:59.717Z] Nothing to be done for teardown. [2025-12-27T14:28:59.717Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 14:28:59 2025 Epoch Time (ms): 1766845739532