[2025-05-28T21:11:20.400Z] Running test renaissance-movie-lens_0 ... [2025-05-28T21:11:20.400Z] =============================================== [2025-05-28T21:11:20.400Z] renaissance-movie-lens_0 Start Time: Wed May 28 17:11:20 2025 Epoch Time (ms): 1748466680124 [2025-05-28T21:11:20.400Z] variation: NoOptions [2025-05-28T21:11:20.400Z] JVM_OPTIONS: [2025-05-28T21:11:20.400Z] { \ [2025-05-28T21:11:20.400Z] echo ""; echo "TEST SETUP:"; \ [2025-05-28T21:11:20.400Z] echo "Nothing to be done for setup."; \ [2025-05-28T21:11:20.400Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484660466246/renaissance-movie-lens_0"; \ [2025-05-28T21:11:20.400Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484660466246/renaissance-movie-lens_0"; \ [2025-05-28T21:11:20.400Z] echo ""; echo "TESTING:"; \ [2025-05-28T21:11:20.400Z] "/Users/admin/workspace/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484660466246/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-28T21:11:20.400Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484660466246/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-28T21:11:20.400Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-28T21:11:20.400Z] echo "Nothing to be done for teardown."; \ [2025-05-28T21:11:20.400Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484660466246/TestTargetResult"; [2025-05-28T21:11:20.400Z] [2025-05-28T21:11:20.400Z] TEST SETUP: [2025-05-28T21:11:20.400Z] Nothing to be done for setup. [2025-05-28T21:11:20.400Z] [2025-05-28T21:11:20.400Z] TESTING: [2025-05-28T21:11:23.524Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-05-28T21:11:26.655Z] 17:11:26.303 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB. [2025-05-28T21:11:27.917Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-28T21:11:28.287Z] Training: 60056, validation: 20285, test: 19854 [2025-05-28T21:11:28.287Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-28T21:11:28.287Z] GC before operation: completed in 45.357 ms, heap usage 217.981 MB -> 75.610 MB. [2025-05-28T21:11:32.415Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:11:34.186Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:11:36.628Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:11:38.492Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:11:39.265Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:11:40.036Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:11:41.259Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:11:42.041Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:11:42.041Z] 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. [2025-05-28T21:11:42.402Z] The best model improves the baseline by 14.52%. [2025-05-28T21:11:42.402Z] Top recommended movies for user id 72: [2025-05-28T21:11:42.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:11:42.402Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:11:42.402Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:11:42.402Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:11:42.402Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:11:42.402Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (14181.803 ms) ====== [2025-05-28T21:11:42.402Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-28T21:11:42.402Z] GC before operation: completed in 60.589 ms, heap usage 278.456 MB -> 94.942 MB. [2025-05-28T21:11:44.174Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:11:45.435Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:11:47.244Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:11:48.480Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:11:49.286Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:11:50.043Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:11:50.830Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:11:51.596Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:11:51.950Z] 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. [2025-05-28T21:11:51.950Z] The best model improves the baseline by 14.52%. [2025-05-28T21:11:51.950Z] Top recommended movies for user id 72: [2025-05-28T21:11:51.950Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:11:51.950Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:11:51.950Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:11:51.950Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:11:51.950Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:11:51.950Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9554.378 ms) ====== [2025-05-28T21:11:51.950Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-28T21:11:51.950Z] GC before operation: completed in 46.989 ms, heap usage 162.945 MB -> 90.449 MB. [2025-05-28T21:11:53.742Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:11:54.985Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:11:56.267Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:11:58.041Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:11:58.814Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:11:59.581Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:12:00.377Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:12:01.164Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:12:01.164Z] 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. [2025-05-28T21:12:01.164Z] The best model improves the baseline by 14.52%. [2025-05-28T21:12:01.555Z] Top recommended movies for user id 72: [2025-05-28T21:12:01.555Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:12:01.555Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:12:01.555Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:12:01.555Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:12:01.555Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:12:01.555Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9396.302 ms) ====== [2025-05-28T21:12:01.555Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-28T21:12:01.555Z] GC before operation: completed in 71.051 ms, heap usage 200.007 MB -> 88.687 MB. [2025-05-28T21:12:02.824Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:12:04.136Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:12:05.960Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:12:07.207Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:12:07.971Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:12:09.218Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:12:09.992Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:12:10.785Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:12:10.785Z] 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. [2025-05-28T21:12:10.785Z] The best model improves the baseline by 14.52%. [2025-05-28T21:12:11.162Z] Top recommended movies for user id 72: [2025-05-28T21:12:11.162Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:12:11.162Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:12:11.162Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:12:11.162Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:12:11.162Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:12:11.162Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9573.720 ms) ====== [2025-05-28T21:12:11.162Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-28T21:12:11.162Z] GC before operation: completed in 54.898 ms, heap usage 157.426 MB -> 92.887 MB. [2025-05-28T21:12:12.411Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:12:14.189Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:12:15.477Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:12:16.703Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:12:17.475Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:12:18.253Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:12:19.014Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:12:19.778Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:12:19.778Z] 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. [2025-05-28T21:12:19.778Z] The best model improves the baseline by 14.52%. [2025-05-28T21:12:20.146Z] Top recommended movies for user id 72: [2025-05-28T21:12:20.146Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:12:20.146Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:12:20.146Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:12:20.146Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:12:20.146Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:12:20.146Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8859.166 ms) ====== [2025-05-28T21:12:20.146Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-28T21:12:20.146Z] GC before operation: completed in 49.855 ms, heap usage 202.160 MB -> 89.247 MB. [2025-05-28T21:12:21.386Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:12:22.655Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:12:23.897Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:12:25.147Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:12:25.935Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:12:26.701Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:12:27.951Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:12:28.326Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:12:28.688Z] 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. [2025-05-28T21:12:28.688Z] The best model improves the baseline by 14.52%. [2025-05-28T21:12:28.688Z] Top recommended movies for user id 72: [2025-05-28T21:12:28.688Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:12:28.688Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:12:28.688Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:12:28.688Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:12:28.688Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:12:28.688Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8698.552 ms) ====== [2025-05-28T21:12:28.688Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-28T21:12:28.688Z] GC before operation: completed in 67.663 ms, heap usage 274.712 MB -> 89.565 MB. [2025-05-28T21:12:30.457Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:12:31.714Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:12:32.956Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:12:34.741Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:12:35.576Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:12:36.337Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:12:37.119Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:12:37.932Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:12:38.303Z] 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. [2025-05-28T21:12:38.304Z] The best model improves the baseline by 14.52%. [2025-05-28T21:12:38.304Z] Top recommended movies for user id 72: [2025-05-28T21:12:38.304Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:12:38.304Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:12:38.304Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:12:38.304Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:12:38.304Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:12:38.304Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (9519.830 ms) ====== [2025-05-28T21:12:38.304Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-28T21:12:38.304Z] GC before operation: completed in 55.891 ms, heap usage 268.819 MB -> 89.506 MB. [2025-05-28T21:12:39.542Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:12:41.325Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:12:42.567Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:12:44.327Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:12:44.715Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:12:45.536Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:12:46.296Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:12:47.550Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:12:47.550Z] 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. [2025-05-28T21:12:47.550Z] The best model improves the baseline by 14.52%. [2025-05-28T21:12:47.550Z] Top recommended movies for user id 72: [2025-05-28T21:12:47.550Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:12:47.550Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:12:47.550Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:12:47.550Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:12:47.550Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:12:47.550Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9145.869 ms) ====== [2025-05-28T21:12:47.550Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-28T21:12:47.550Z] GC before operation: completed in 48.338 ms, heap usage 494.069 MB -> 93.228 MB. [2025-05-28T21:12:48.798Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:12:50.601Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:12:51.851Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:12:53.090Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:12:53.856Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:12:54.636Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:12:55.418Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:12:56.184Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:12:56.549Z] 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. [2025-05-28T21:12:56.549Z] The best model improves the baseline by 14.52%. [2025-05-28T21:12:56.549Z] Top recommended movies for user id 72: [2025-05-28T21:12:56.549Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:12:56.549Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:12:56.549Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:12:56.549Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:12:56.549Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:12:56.549Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8943.229 ms) ====== [2025-05-28T21:12:56.549Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-28T21:12:56.549Z] GC before operation: completed in 65.455 ms, heap usage 219.245 MB -> 89.433 MB. [2025-05-28T21:12:57.792Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:12:59.054Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:13:00.823Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:13:02.091Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:13:02.873Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:13:03.649Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:13:04.504Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:13:05.277Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:13:05.277Z] 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. [2025-05-28T21:13:05.277Z] The best model improves the baseline by 14.52%. [2025-05-28T21:13:05.638Z] Top recommended movies for user id 72: [2025-05-28T21:13:05.638Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:13:05.638Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:13:05.638Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:13:05.638Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:13:05.638Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:13:05.638Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8906.449 ms) ====== [2025-05-28T21:13:05.638Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-28T21:13:05.638Z] GC before operation: completed in 72.745 ms, heap usage 473.669 MB -> 90.124 MB. [2025-05-28T21:13:06.888Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:13:08.120Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:13:09.377Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:13:11.158Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:13:11.519Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:13:12.749Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:13:13.541Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:13:13.896Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:13:14.271Z] 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. [2025-05-28T21:13:14.272Z] The best model improves the baseline by 14.52%. [2025-05-28T21:13:14.272Z] Top recommended movies for user id 72: [2025-05-28T21:13:14.272Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:13:14.272Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:13:14.272Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:13:14.272Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:13:14.272Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:13:14.272Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8691.443 ms) ====== [2025-05-28T21:13:14.272Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-28T21:13:14.272Z] GC before operation: completed in 50.009 ms, heap usage 274.704 MB -> 89.477 MB. [2025-05-28T21:13:15.510Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:13:17.295Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:13:18.548Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:13:19.329Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:13:20.095Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:13:21.350Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:13:21.708Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:13:22.510Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:13:22.511Z] 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. [2025-05-28T21:13:22.868Z] The best model improves the baseline by 14.52%. [2025-05-28T21:13:22.868Z] Top recommended movies for user id 72: [2025-05-28T21:13:22.868Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:13:22.868Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:13:22.868Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:13:22.868Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:13:22.868Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:13:22.868Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8498.830 ms) ====== [2025-05-28T21:13:22.868Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-28T21:13:22.868Z] GC before operation: completed in 51.676 ms, heap usage 164.156 MB -> 89.574 MB. [2025-05-28T21:13:24.096Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:13:25.359Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:13:27.124Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:13:28.357Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:13:29.162Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:13:29.535Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:13:30.319Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:13:31.093Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:13:31.093Z] 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. [2025-05-28T21:13:31.093Z] The best model improves the baseline by 14.52%. [2025-05-28T21:13:31.093Z] Top recommended movies for user id 72: [2025-05-28T21:13:31.093Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:13:31.093Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:13:31.093Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:13:31.093Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:13:31.093Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:13:31.093Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8428.361 ms) ====== [2025-05-28T21:13:31.093Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-28T21:13:31.449Z] GC before operation: completed in 63.972 ms, heap usage 112.581 MB -> 89.529 MB. [2025-05-28T21:13:32.707Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:13:33.945Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:13:34.719Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:13:35.971Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:13:36.742Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:13:37.536Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:13:38.312Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:13:39.082Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:13:39.082Z] 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. [2025-05-28T21:13:39.082Z] The best model improves the baseline by 14.52%. [2025-05-28T21:13:39.082Z] Top recommended movies for user id 72: [2025-05-28T21:13:39.082Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:13:39.082Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:13:39.082Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:13:39.082Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:13:39.082Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:13:39.082Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (7828.549 ms) ====== [2025-05-28T21:13:39.082Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-28T21:13:39.082Z] GC before operation: completed in 56.493 ms, heap usage 274.600 MB -> 89.738 MB. [2025-05-28T21:13:40.313Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:13:41.565Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:13:43.371Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:13:44.614Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:13:44.982Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:13:45.796Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:13:46.587Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:13:47.406Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:13:47.406Z] 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. [2025-05-28T21:13:47.406Z] The best model improves the baseline by 14.52%. [2025-05-28T21:13:47.763Z] Top recommended movies for user id 72: [2025-05-28T21:13:47.763Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:13:47.763Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:13:47.763Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:13:47.763Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:13:47.763Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:13:47.763Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8449.815 ms) ====== [2025-05-28T21:13:47.763Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-28T21:13:47.763Z] GC before operation: completed in 58.284 ms, heap usage 205.558 MB -> 89.872 MB. [2025-05-28T21:13:49.001Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:13:50.245Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:13:51.521Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:13:53.320Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:13:53.673Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:13:54.452Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:13:55.212Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:13:55.982Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:13:55.982Z] 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. [2025-05-28T21:13:56.338Z] The best model improves the baseline by 14.52%. [2025-05-28T21:13:56.338Z] Top recommended movies for user id 72: [2025-05-28T21:13:56.338Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:13:56.338Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:13:56.338Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:13:56.338Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:13:56.338Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:13:56.338Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8501.973 ms) ====== [2025-05-28T21:13:56.338Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-28T21:13:56.338Z] GC before operation: completed in 61.533 ms, heap usage 438.540 MB -> 90.045 MB. [2025-05-28T21:13:57.576Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:13:59.394Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:14:00.211Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:14:01.498Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:14:02.274Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:14:03.576Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:14:04.387Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:14:05.169Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:14:05.169Z] 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. [2025-05-28T21:14:05.169Z] The best model improves the baseline by 14.52%. [2025-05-28T21:14:05.169Z] Top recommended movies for user id 72: [2025-05-28T21:14:05.169Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:14:05.169Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:14:05.169Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:14:05.169Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:14:05.169Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:14:05.169Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8873.539 ms) ====== [2025-05-28T21:14:05.169Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-28T21:14:05.169Z] GC before operation: completed in 47.397 ms, heap usage 246.551 MB -> 91.095 MB. [2025-05-28T21:14:06.459Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:14:07.679Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:14:09.454Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:14:10.230Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:14:11.015Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:14:11.786Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:14:12.547Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:14:13.314Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:14:13.682Z] 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. [2025-05-28T21:14:13.682Z] The best model improves the baseline by 14.52%. [2025-05-28T21:14:13.682Z] Top recommended movies for user id 72: [2025-05-28T21:14:13.682Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:14:13.682Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:14:13.682Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:14:13.682Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:14:13.682Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:14:13.682Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8434.143 ms) ====== [2025-05-28T21:14:13.682Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-28T21:14:13.682Z] GC before operation: completed in 50.167 ms, heap usage 209.809 MB -> 89.555 MB. [2025-05-28T21:14:14.938Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:14:16.698Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:14:17.970Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:14:18.732Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:14:19.500Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:14:20.268Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:14:21.062Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:14:22.310Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:14:22.310Z] 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. [2025-05-28T21:14:22.310Z] The best model improves the baseline by 14.52%. [2025-05-28T21:14:22.310Z] Top recommended movies for user id 72: [2025-05-28T21:14:22.310Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:14:22.310Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:14:22.310Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:14:22.310Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:14:22.310Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:14:22.310Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8562.258 ms) ====== [2025-05-28T21:14:22.310Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-28T21:14:22.310Z] GC before operation: completed in 46.513 ms, heap usage 226.759 MB -> 89.676 MB. [2025-05-28T21:14:23.543Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:14:25.332Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:14:26.586Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:14:27.860Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:14:28.622Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:14:29.399Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:14:30.645Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:14:31.022Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:14:31.389Z] 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. [2025-05-28T21:14:31.389Z] The best model improves the baseline by 14.52%. [2025-05-28T21:14:31.389Z] Top recommended movies for user id 72: [2025-05-28T21:14:31.389Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T21:14:31.390Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T21:14:31.390Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T21:14:31.390Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T21:14:31.390Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T21:14:31.390Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (9031.576 ms) ====== [2025-05-28T21:14:31.744Z] ----------------------------------- [2025-05-28T21:14:31.744Z] renaissance-movie-lens_0_PASSED [2025-05-28T21:14:31.744Z] ----------------------------------- [2025-05-28T21:14:31.744Z] [2025-05-28T21:14:31.744Z] TEST TEARDOWN: [2025-05-28T21:14:31.744Z] Nothing to be done for teardown. [2025-05-28T21:14:31.744Z] renaissance-movie-lens_0 Finish Time: Wed May 28 17:14:31 2025 Epoch Time (ms): 1748466871419