[2025-09-05T14:36:22.328Z] Running test renaissance-movie-lens_0 ... [2025-09-05T14:36:22.328Z] =============================================== [2025-09-05T14:36:22.328Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 10:36:21 2025 Epoch Time (ms): 1757082981773 [2025-09-05T14:36:22.328Z] variation: NoOptions [2025-09-05T14:36:22.328Z] JVM_OPTIONS: [2025-09-05T14:36:22.328Z] { \ [2025-09-05T14:36:22.328Z] echo ""; echo "TEST SETUP:"; \ [2025-09-05T14:36:22.328Z] echo "Nothing to be done for setup."; \ [2025-09-05T14:36:22.328Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17570822028035/renaissance-movie-lens_0"; \ [2025-09-05T14:36:22.328Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17570822028035/renaissance-movie-lens_0"; \ [2025-09-05T14:36:22.328Z] echo ""; echo "TESTING:"; \ [2025-09-05T14:36:22.328Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17570822028035/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-05T14:36:22.328Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17570822028035/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-05T14:36:22.328Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-05T14:36:22.328Z] echo "Nothing to be done for teardown."; \ [2025-09-05T14:36:22.328Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17570822028035/TestTargetResult"; [2025-09-05T14:36:22.328Z] [2025-09-05T14:36:22.328Z] TEST SETUP: [2025-09-05T14:36:22.328Z] Nothing to be done for setup. [2025-09-05T14:36:22.328Z] [2025-09-05T14:36:22.328Z] TESTING: [2025-09-05T14:36:22.328Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-09-05T14:36:22.328Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/output_17570822028035/renaissance-movie-lens_0/launcher-103621-6626690647874886470/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-09-05T14:36:22.328Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-09-05T14:36:22.328Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-09-05T14:36:24.716Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-09-05T14:36:27.121Z] 10:36:26.831 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB. [2025-09-05T14:36:27.901Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-05T14:36:28.291Z] Training: 60056, validation: 20285, test: 19854 [2025-09-05T14:36:28.291Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-05T14:36:28.291Z] GC before operation: completed in 61.572 ms, heap usage 151.306 MB -> 75.821 MB. [2025-09-05T14:36:31.411Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:36:33.226Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:36:34.473Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:36:36.289Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:36:36.662Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:36:37.914Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:36:38.675Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:36:39.450Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:36:39.450Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:36:39.450Z] The best model improves the baseline by 14.52%. [2025-09-05T14:36:39.450Z] Top recommended movies for user id 72: [2025-09-05T14:36:39.450Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:36:39.450Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:36:39.450Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:36:39.450Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:36:39.450Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:36:39.450Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11218.164 ms) ====== [2025-09-05T14:36:39.450Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-05T14:36:39.451Z] GC before operation: completed in 58.186 ms, heap usage 443.487 MB -> 89.566 MB. [2025-09-05T14:36:40.717Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:36:41.989Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:36:43.251Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:36:44.501Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:36:45.267Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:36:46.028Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:36:46.805Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:36:47.570Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:36:47.570Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:36:47.570Z] The best model improves the baseline by 14.52%. [2025-09-05T14:36:47.570Z] Top recommended movies for user id 72: [2025-09-05T14:36:47.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:36:47.570Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:36:47.570Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:36:47.570Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:36:47.570Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:36:47.570Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8064.839 ms) ====== [2025-09-05T14:36:47.570Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-05T14:36:47.570Z] GC before operation: completed in 51.343 ms, heap usage 199.853 MB -> 88.009 MB. [2025-09-05T14:36:48.817Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:36:50.067Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:36:51.335Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:36:52.616Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:36:53.385Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:36:54.182Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:36:54.968Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:36:55.735Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:36:55.735Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:36:55.735Z] The best model improves the baseline by 14.52%. [2025-09-05T14:36:55.735Z] Top recommended movies for user id 72: [2025-09-05T14:36:55.735Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:36:55.735Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:36:55.735Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:36:55.735Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:36:55.735Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:36:55.735Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (7980.388 ms) ====== [2025-09-05T14:36:55.735Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-05T14:36:55.735Z] GC before operation: completed in 50.595 ms, heap usage 414.889 MB -> 89.202 MB. [2025-09-05T14:36:56.991Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:36:58.248Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:36:59.494Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:00.273Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:01.069Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:01.845Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:02.226Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:03.007Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:03.007Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:03.007Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:03.382Z] Top recommended movies for user id 72: [2025-09-05T14:37:03.382Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:03.382Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:03.382Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:03.382Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:03.382Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:03.382Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (7471.213 ms) ====== [2025-09-05T14:37:03.382Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-05T14:37:03.382Z] GC before operation: completed in 48.612 ms, heap usage 435.810 MB -> 89.543 MB. [2025-09-05T14:37:04.173Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:05.452Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:06.238Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:07.499Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:07.855Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:08.624Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:08.989Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:09.780Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:09.780Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:09.780Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:09.780Z] Top recommended movies for user id 72: [2025-09-05T14:37:09.780Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:09.780Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:09.780Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:09.780Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:09.780Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:09.780Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (6595.451 ms) ====== [2025-09-05T14:37:09.780Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-05T14:37:09.780Z] GC before operation: completed in 50.777 ms, heap usage 178.444 MB -> 91.289 MB. [2025-09-05T14:37:11.026Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:11.799Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:13.048Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:13.820Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:14.185Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:14.957Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:15.751Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:16.114Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:16.114Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:16.470Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:16.470Z] Top recommended movies for user id 72: [2025-09-05T14:37:16.470Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:16.470Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:16.470Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:16.470Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:16.470Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:16.470Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (6471.864 ms) ====== [2025-09-05T14:37:16.470Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-05T14:37:16.470Z] GC before operation: completed in 50.360 ms, heap usage 227.242 MB -> 89.418 MB. [2025-09-05T14:37:17.715Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:18.988Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:19.770Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:21.022Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:21.383Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:22.151Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:22.934Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:23.291Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:23.649Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:23.649Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:23.649Z] Top recommended movies for user id 72: [2025-09-05T14:37:23.649Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:23.649Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:23.649Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:23.649Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:23.649Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:23.649Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7133.392 ms) ====== [2025-09-05T14:37:23.649Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-05T14:37:23.649Z] GC before operation: completed in 51.000 ms, heap usage 265.323 MB -> 89.601 MB. [2025-09-05T14:37:24.888Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:25.663Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:26.906Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:27.679Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:28.450Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:28.806Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:29.577Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:30.365Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:30.365Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:30.365Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:30.365Z] Top recommended movies for user id 72: [2025-09-05T14:37:30.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:30.365Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:30.365Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:30.365Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:30.365Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:30.365Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (6687.403 ms) ====== [2025-09-05T14:37:30.365Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-05T14:37:30.365Z] GC before operation: completed in 48.613 ms, heap usage 301.541 MB -> 89.736 MB. [2025-09-05T14:37:31.626Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:32.419Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:33.647Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:34.412Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:35.206Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:35.990Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:36.350Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:37.115Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:37.115Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:37.115Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:37.115Z] Top recommended movies for user id 72: [2025-09-05T14:37:37.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:37.115Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:37.115Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:37.115Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:37.115Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:37.115Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (6817.121 ms) ====== [2025-09-05T14:37:37.115Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-05T14:37:37.115Z] GC before operation: completed in 49.467 ms, heap usage 449.838 MB -> 89.882 MB. [2025-09-05T14:37:38.376Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:39.142Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:40.391Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:41.156Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:41.934Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:42.711Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:43.070Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:43.843Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:43.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:43.843Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:43.843Z] Top recommended movies for user id 72: [2025-09-05T14:37:43.843Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:43.843Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:43.843Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:43.843Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:43.843Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:43.843Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (6718.748 ms) ====== [2025-09-05T14:37:43.843Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-05T14:37:43.843Z] GC before operation: completed in 50.522 ms, heap usage 193.805 MB -> 89.735 MB. [2025-09-05T14:37:45.090Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:45.859Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:47.121Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:47.892Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:48.664Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:49.444Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:50.211Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:50.588Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:50.588Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:50.588Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:50.588Z] Top recommended movies for user id 72: [2025-09-05T14:37:50.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:50.588Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:50.588Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:50.588Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:50.588Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:50.588Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6761.272 ms) ====== [2025-09-05T14:37:50.588Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-05T14:37:50.951Z] GC before operation: completed in 52.099 ms, heap usage 219.464 MB -> 89.441 MB. [2025-09-05T14:37:51.713Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:37:52.968Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:37:53.734Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:37:54.991Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:37:55.784Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:37:56.217Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:37:57.014Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:37:57.388Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:37:57.758Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:37:57.758Z] The best model improves the baseline by 14.52%. [2025-09-05T14:37:57.758Z] Top recommended movies for user id 72: [2025-09-05T14:37:57.758Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:37:57.758Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:37:57.758Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:37:57.758Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:37:57.758Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:37:57.758Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (6958.522 ms) ====== [2025-09-05T14:37:57.758Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-05T14:37:57.758Z] GC before operation: completed in 51.917 ms, heap usage 392.521 MB -> 89.912 MB. [2025-09-05T14:37:59.006Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:00.260Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:01.068Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:02.366Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:02.737Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:03.537Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:04.333Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:04.697Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:04.697Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:04.697Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:05.060Z] Top recommended movies for user id 72: [2025-09-05T14:38:05.060Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:05.060Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:05.060Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:05.060Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:05.060Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:05.060Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7099.951 ms) ====== [2025-09-05T14:38:05.060Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-05T14:38:05.060Z] GC before operation: completed in 53.675 ms, heap usage 331.566 MB -> 90.010 MB. [2025-09-05T14:38:06.318Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:07.093Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:08.360Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:09.127Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:09.904Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:10.262Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:11.033Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:11.402Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:11.402Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:11.402Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:11.765Z] Top recommended movies for user id 72: [2025-09-05T14:38:11.765Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:11.765Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:11.765Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:11.765Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:11.765Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:11.765Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (6647.124 ms) ====== [2025-09-05T14:38:11.765Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-05T14:38:11.765Z] GC before operation: completed in 56.772 ms, heap usage 208.480 MB -> 89.623 MB. [2025-09-05T14:38:12.539Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:13.792Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:14.553Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:15.809Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:16.185Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:16.954Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:17.799Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:18.155Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:18.155Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:18.155Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:18.521Z] Top recommended movies for user id 72: [2025-09-05T14:38:18.521Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:18.521Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:18.521Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:18.521Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:18.521Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:18.521Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (6673.173 ms) ====== [2025-09-05T14:38:18.521Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-05T14:38:18.521Z] GC before operation: completed in 50.830 ms, heap usage 266.068 MB -> 89.938 MB. [2025-09-05T14:38:19.290Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:20.537Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:21.305Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:22.542Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:23.323Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:23.712Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:24.551Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:24.907Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:24.907Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:24.907Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:25.271Z] Top recommended movies for user id 72: [2025-09-05T14:38:25.271Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:25.271Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:25.271Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:25.271Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:25.271Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:25.271Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6710.429 ms) ====== [2025-09-05T14:38:25.271Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-05T14:38:25.271Z] GC before operation: completed in 51.125 ms, heap usage 249.591 MB -> 89.888 MB. [2025-09-05T14:38:26.040Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:27.279Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:28.528Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:29.297Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:29.660Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:30.426Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:31.197Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:31.552Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:31.911Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:31.911Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:31.911Z] Top recommended movies for user id 72: [2025-09-05T14:38:31.911Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:31.911Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:31.911Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:31.911Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:31.911Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:31.911Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (6742.315 ms) ====== [2025-09-05T14:38:31.912Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-05T14:38:31.912Z] GC before operation: completed in 53.756 ms, heap usage 176.138 MB -> 89.788 MB. [2025-09-05T14:38:33.154Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:33.932Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:35.172Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:35.940Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:36.720Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:37.076Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:37.846Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:38.219Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:38.585Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:38.585Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:38.585Z] Top recommended movies for user id 72: [2025-09-05T14:38:38.585Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:38.585Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:38.585Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:38.585Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:38.585Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:38.585Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (6609.356 ms) ====== [2025-09-05T14:38:38.585Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-05T14:38:38.585Z] GC before operation: completed in 51.701 ms, heap usage 261.258 MB -> 89.765 MB. [2025-09-05T14:38:39.852Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:40.621Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:41.390Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:42.645Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:43.004Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:43.774Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:44.136Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:44.906Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:44.906Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:44.906Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:44.906Z] Top recommended movies for user id 72: [2025-09-05T14:38:44.906Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:44.906Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:44.906Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:44.906Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:44.906Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:44.906Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (6333.814 ms) ====== [2025-09-05T14:38:44.906Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-05T14:38:44.906Z] GC before operation: completed in 50.851 ms, heap usage 261.642 MB -> 89.831 MB. [2025-09-05T14:38:46.153Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T14:38:46.925Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T14:38:47.705Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T14:38:48.970Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T14:38:49.327Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T14:38:50.119Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T14:38:50.482Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T14:38:51.248Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T14:38:51.248Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-05T14:38:51.248Z] The best model improves the baseline by 14.52%. [2025-09-05T14:38:51.248Z] Top recommended movies for user id 72: [2025-09-05T14:38:51.248Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-05T14:38:51.248Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-05T14:38:51.248Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-05T14:38:51.248Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-05T14:38:51.248Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-05T14:38:51.248Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (6210.792 ms) ====== [2025-09-05T14:38:51.248Z] ----------------------------------- [2025-09-05T14:38:51.248Z] renaissance-movie-lens_0_PASSED [2025-09-05T14:38:51.248Z] ----------------------------------- [2025-09-05T14:38:51.248Z] [2025-09-05T14:38:51.248Z] TEST TEARDOWN: [2025-09-05T14:38:51.248Z] Nothing to be done for teardown. [2025-09-05T14:38:51.608Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 10:38:51 2025 Epoch Time (ms): 1757083131216