[2025-06-26T16:46:41.853Z] Running test renaissance-movie-lens_0 ... [2025-06-26T16:46:41.853Z] =============================================== [2025-06-26T16:46:41.853Z] renaissance-movie-lens_0 Start Time: Thu Jun 26 12:46:41 2025 Epoch Time (ms): 1750956401654 [2025-06-26T16:46:41.853Z] variation: NoOptions [2025-06-26T16:46:41.853Z] JVM_OPTIONS: [2025-06-26T16:46:41.853Z] { \ [2025-06-26T16:46:41.853Z] echo ""; echo "TEST SETUP:"; \ [2025-06-26T16:46:41.853Z] echo "Nothing to be done for setup."; \ [2025-06-26T16:46:41.853Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17509557086572/renaissance-movie-lens_0"; \ [2025-06-26T16:46:41.853Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17509557086572/renaissance-movie-lens_0"; \ [2025-06-26T16:46:41.853Z] echo ""; echo "TESTING:"; \ [2025-06-26T16:46:41.853Z] "/Users/admin/workspace/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17509557086572/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-26T16:46:41.853Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17509557086572/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-26T16:46:41.853Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-26T16:46:41.853Z] echo "Nothing to be done for teardown."; \ [2025-06-26T16:46:41.853Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17509557086572/TestTargetResult"; [2025-06-26T16:46:41.853Z] [2025-06-26T16:46:41.853Z] TEST SETUP: [2025-06-26T16:46:41.853Z] Nothing to be done for setup. [2025-06-26T16:46:41.853Z] [2025-06-26T16:46:41.853Z] TESTING: [2025-06-26T16:46:45.002Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-06-26T16:46:48.148Z] 12:46:47.809 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB. [2025-06-26T16:46:49.454Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-26T16:46:49.820Z] Training: 60056, validation: 20285, test: 19854 [2025-06-26T16:46:49.820Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-26T16:46:50.176Z] GC before operation: completed in 87.380 ms, heap usage 141.750 MB -> 75.696 MB. [2025-06-26T16:46:53.318Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:46:54.583Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:46:57.013Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:46:58.299Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:46:59.551Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:47:00.367Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:47:01.704Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:47:02.506Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:47:02.506Z] 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. [2025-06-26T16:47:02.506Z] The best model improves the baseline by 14.52%. [2025-06-26T16:47:02.506Z] Top recommended movies for user id 72: [2025-06-26T16:47:02.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:47:02.506Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:47:02.506Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:47:02.506Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:47:02.506Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:47:02.506Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (12580.657 ms) ====== [2025-06-26T16:47:02.506Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-26T16:47:02.506Z] GC before operation: completed in 76.146 ms, heap usage 248.110 MB -> 91.370 MB. [2025-06-26T16:47:04.354Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:47:05.644Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:47:06.900Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:47:08.731Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:47:09.507Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:47:10.278Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:47:11.536Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:47:11.897Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:47:12.253Z] 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. [2025-06-26T16:47:12.253Z] The best model improves the baseline by 14.52%. [2025-06-26T16:47:12.253Z] Top recommended movies for user id 72: [2025-06-26T16:47:12.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:47:12.253Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:47:12.253Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:47:12.253Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:47:12.253Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:47:12.253Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9504.434 ms) ====== [2025-06-26T16:47:12.253Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-26T16:47:12.253Z] GC before operation: completed in 66.718 ms, heap usage 267.616 MB -> 88.377 MB. [2025-06-26T16:47:13.637Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:47:14.878Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:47:16.144Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:47:17.929Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:47:18.712Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:47:19.990Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:47:20.345Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:47:21.600Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:47:21.600Z] 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. [2025-06-26T16:47:21.600Z] The best model improves the baseline by 14.52%. [2025-06-26T16:47:21.600Z] Top recommended movies for user id 72: [2025-06-26T16:47:21.600Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:47:21.600Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:47:21.600Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:47:21.600Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:47:21.600Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:47:21.600Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9301.325 ms) ====== [2025-06-26T16:47:21.600Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-26T16:47:21.600Z] GC before operation: completed in 58.508 ms, heap usage 310.063 MB -> 89.097 MB. [2025-06-26T16:47:22.843Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:47:24.108Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:47:25.922Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:47:27.174Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:47:28.471Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:47:28.917Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:47:30.162Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:47:30.926Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:47:30.926Z] 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. [2025-06-26T16:47:30.926Z] The best model improves the baseline by 14.52%. [2025-06-26T16:47:30.926Z] Top recommended movies for user id 72: [2025-06-26T16:47:30.926Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:47:30.926Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:47:30.926Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:47:30.927Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:47:30.927Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:47:30.927Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9364.561 ms) ====== [2025-06-26T16:47:30.927Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-26T16:47:30.927Z] GC before operation: completed in 53.320 ms, heap usage 414.908 MB -> 89.629 MB. [2025-06-26T16:47:32.177Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:47:33.449Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:47:35.276Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:47:36.520Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:47:37.298Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:47:38.580Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:47:39.356Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:47:40.133Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:47:40.133Z] 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. [2025-06-26T16:47:40.133Z] The best model improves the baseline by 14.52%. [2025-06-26T16:47:40.133Z] Top recommended movies for user id 72: [2025-06-26T16:47:40.133Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:47:40.133Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:47:40.133Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:47:40.133Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:47:40.133Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:47:40.133Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (9183.234 ms) ====== [2025-06-26T16:47:40.133Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-26T16:47:40.133Z] GC before operation: completed in 52.949 ms, heap usage 338.691 MB -> 89.430 MB. [2025-06-26T16:47:41.380Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:47:42.648Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:47:43.895Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:47:45.135Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:47:45.936Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:47:46.708Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:47:47.957Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:47:48.746Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:47:48.746Z] 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. [2025-06-26T16:47:48.746Z] The best model improves the baseline by 14.52%. [2025-06-26T16:47:48.746Z] Top recommended movies for user id 72: [2025-06-26T16:47:48.746Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:47:48.746Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:47:48.746Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:47:48.746Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:47:48.746Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:47:48.746Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8452.087 ms) ====== [2025-06-26T16:47:48.746Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-26T16:47:48.746Z] GC before operation: completed in 51.761 ms, heap usage 109.411 MB -> 89.526 MB. [2025-06-26T16:47:50.043Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:47:51.288Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:47:52.529Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:47:53.778Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:47:54.543Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:47:55.317Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:47:56.554Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:47:57.353Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:47:57.353Z] 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. [2025-06-26T16:47:57.353Z] The best model improves the baseline by 14.52%. [2025-06-26T16:47:57.353Z] Top recommended movies for user id 72: [2025-06-26T16:47:57.353Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:47:57.353Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:47:57.353Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:47:57.353Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:47:57.353Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:47:57.353Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8668.312 ms) ====== [2025-06-26T16:47:57.353Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-26T16:47:57.353Z] GC before operation: completed in 78.675 ms, heap usage 182.121 MB -> 89.441 MB. [2025-06-26T16:47:58.586Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:47:59.848Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:01.132Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:48:01.988Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:48:03.262Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:48:03.618Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:48:04.975Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:48:05.357Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:48:05.723Z] 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. [2025-06-26T16:48:05.723Z] The best model improves the baseline by 14.52%. [2025-06-26T16:48:05.723Z] Top recommended movies for user id 72: [2025-06-26T16:48:05.723Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:48:05.723Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:48:05.723Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:48:05.723Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:48:05.723Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:48:05.723Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8165.374 ms) ====== [2025-06-26T16:48:05.723Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-26T16:48:05.723Z] GC before operation: completed in 77.568 ms, heap usage 568.428 MB -> 93.433 MB. [2025-06-26T16:48:06.974Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:48:08.213Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:09.565Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:48:10.791Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:48:11.560Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:48:12.319Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:48:13.175Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:48:13.947Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:48:13.947Z] 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. [2025-06-26T16:48:14.313Z] The best model improves the baseline by 14.52%. [2025-06-26T16:48:14.313Z] Top recommended movies for user id 72: [2025-06-26T16:48:14.313Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:48:14.313Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:48:14.313Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:48:14.313Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:48:14.313Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:48:14.313Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8457.042 ms) ====== [2025-06-26T16:48:14.313Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-26T16:48:14.313Z] GC before operation: completed in 67.124 ms, heap usage 190.320 MB -> 89.592 MB. [2025-06-26T16:48:16.100Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:48:17.328Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:18.605Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:48:19.830Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:48:20.673Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:48:21.040Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:48:21.807Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:48:22.572Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:48:22.572Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-06-26T16:48:22.572Z] The best model improves the baseline by 14.52%. [2025-06-26T16:48:22.572Z] Top recommended movies for user id 72: [2025-06-26T16:48:22.572Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:48:22.572Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:48:22.572Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:48:22.572Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:48:22.572Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:48:22.572Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8333.392 ms) ====== [2025-06-26T16:48:22.572Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-26T16:48:22.572Z] GC before operation: completed in 58.399 ms, heap usage 612.643 MB -> 93.825 MB. [2025-06-26T16:48:23.806Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:48:25.050Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:25.820Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:48:27.053Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:48:27.408Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:48:28.174Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:48:28.980Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:48:29.338Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:48:29.691Z] 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. [2025-06-26T16:48:29.691Z] The best model improves the baseline by 14.52%. [2025-06-26T16:48:29.691Z] Top recommended movies for user id 72: [2025-06-26T16:48:29.691Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:48:29.691Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:48:29.691Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:48:29.691Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:48:29.691Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:48:29.691Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6919.519 ms) ====== [2025-06-26T16:48:29.691Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-26T16:48:29.691Z] GC before operation: completed in 49.934 ms, heap usage 246.800 MB -> 89.642 MB. [2025-06-26T16:48:30.923Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:48:31.694Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:32.929Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:48:34.169Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:48:34.954Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:48:35.756Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:48:36.110Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:48:36.902Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:48:36.902Z] 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. [2025-06-26T16:48:36.902Z] The best model improves the baseline by 14.52%. [2025-06-26T16:48:37.259Z] Top recommended movies for user id 72: [2025-06-26T16:48:37.259Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:48:37.259Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:48:37.259Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:48:37.259Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:48:37.259Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:48:37.259Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (7438.762 ms) ====== [2025-06-26T16:48:37.259Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-26T16:48:37.259Z] GC before operation: completed in 62.960 ms, heap usage 263.127 MB -> 89.928 MB. [2025-06-26T16:48:38.501Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:48:39.738Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:40.970Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:48:42.210Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:48:42.617Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:48:43.378Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:48:44.144Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:48:45.397Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:48:45.397Z] 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. [2025-06-26T16:48:45.397Z] The best model improves the baseline by 14.52%. [2025-06-26T16:48:45.397Z] Top recommended movies for user id 72: [2025-06-26T16:48:45.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:48:45.397Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:48:45.397Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:48:45.397Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:48:45.397Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:48:45.397Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8241.950 ms) ====== [2025-06-26T16:48:45.397Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-26T16:48:45.397Z] GC before operation: completed in 71.350 ms, heap usage 285.310 MB -> 89.947 MB. [2025-06-26T16:48:47.180Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:48:48.424Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:50.235Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:48:51.467Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:48:52.234Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:48:53.510Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:48:54.282Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:48:55.045Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:48:55.045Z] 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. [2025-06-26T16:48:55.045Z] The best model improves the baseline by 14.52%. [2025-06-26T16:48:55.045Z] Top recommended movies for user id 72: [2025-06-26T16:48:55.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:48:55.045Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:48:55.045Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:48:55.045Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:48:55.045Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:48:55.045Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (9601.337 ms) ====== [2025-06-26T16:48:55.045Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-26T16:48:55.045Z] GC before operation: completed in 73.094 ms, heap usage 230.310 MB -> 89.694 MB. [2025-06-26T16:48:56.816Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:48:58.065Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:48:59.311Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:49:00.576Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:49:00.945Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:49:01.731Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:49:02.515Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:49:02.889Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:49:03.266Z] 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. [2025-06-26T16:49:03.266Z] The best model improves the baseline by 14.52%. [2025-06-26T16:49:03.266Z] Top recommended movies for user id 72: [2025-06-26T16:49:03.266Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:49:03.266Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:49:03.266Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:49:03.266Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:49:03.266Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:49:03.266Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (7989.434 ms) ====== [2025-06-26T16:49:03.266Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-26T16:49:03.266Z] GC before operation: completed in 52.044 ms, heap usage 115.673 MB -> 89.691 MB. [2025-06-26T16:49:04.531Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:49:05.298Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:49:06.055Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:49:07.302Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:49:07.668Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:49:08.031Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:49:08.809Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:49:09.162Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:49:09.569Z] 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. [2025-06-26T16:49:09.569Z] The best model improves the baseline by 14.52%. [2025-06-26T16:49:09.569Z] Top recommended movies for user id 72: [2025-06-26T16:49:09.569Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:49:09.569Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:49:09.569Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:49:09.569Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:49:09.569Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:49:09.569Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6259.675 ms) ====== [2025-06-26T16:49:09.569Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-26T16:49:09.569Z] GC before operation: completed in 48.264 ms, heap usage 181.994 MB -> 89.800 MB. [2025-06-26T16:49:10.811Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:49:11.583Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:49:12.840Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:49:13.600Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:49:13.969Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:49:14.752Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:49:15.521Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:49:16.301Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:49:16.301Z] 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. [2025-06-26T16:49:16.301Z] The best model improves the baseline by 14.52%. [2025-06-26T16:49:16.301Z] Top recommended movies for user id 72: [2025-06-26T16:49:16.301Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:49:16.301Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:49:16.301Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:49:16.301Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:49:16.301Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:49:16.301Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (6865.635 ms) ====== [2025-06-26T16:49:16.301Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-26T16:49:16.301Z] GC before operation: completed in 60.845 ms, heap usage 243.237 MB -> 89.932 MB. [2025-06-26T16:49:17.545Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:49:18.794Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:49:20.048Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:49:21.304Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:49:21.665Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:49:22.427Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:49:23.210Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:49:23.566Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:49:23.920Z] 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. [2025-06-26T16:49:23.920Z] The best model improves the baseline by 14.52%. [2025-06-26T16:49:23.920Z] Top recommended movies for user id 72: [2025-06-26T16:49:23.920Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:49:23.920Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:49:23.920Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:49:23.920Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:49:23.920Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:49:23.920Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (7412.751 ms) ====== [2025-06-26T16:49:23.920Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-26T16:49:23.920Z] GC before operation: completed in 54.913 ms, heap usage 337.339 MB -> 89.855 MB. [2025-06-26T16:49:25.193Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:49:26.452Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:49:27.710Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:49:28.939Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:49:29.756Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:49:30.537Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:49:31.313Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:49:32.084Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:49:32.439Z] 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. [2025-06-26T16:49:32.439Z] The best model improves the baseline by 14.52%. [2025-06-26T16:49:32.439Z] Top recommended movies for user id 72: [2025-06-26T16:49:32.439Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:49:32.439Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:49:32.439Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:49:32.439Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:49:32.439Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:49:32.439Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8588.462 ms) ====== [2025-06-26T16:49:32.439Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-26T16:49:32.439Z] GC before operation: completed in 64.484 ms, heap usage 218.774 MB -> 89.833 MB. [2025-06-26T16:49:34.242Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-26T16:49:35.605Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-26T16:49:36.905Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-26T16:49:37.679Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-26T16:49:38.455Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-26T16:49:39.229Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-26T16:49:40.004Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-26T16:49:40.362Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-26T16:49:40.722Z] 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. [2025-06-26T16:49:40.722Z] The best model improves the baseline by 14.52%. [2025-06-26T16:49:40.722Z] Top recommended movies for user id 72: [2025-06-26T16:49:40.722Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-26T16:49:40.722Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-26T16:49:40.722Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-26T16:49:40.722Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-26T16:49:40.722Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-26T16:49:40.722Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8152.677 ms) ====== [2025-06-26T16:49:40.722Z] ----------------------------------- [2025-06-26T16:49:40.722Z] renaissance-movie-lens_0_PASSED [2025-06-26T16:49:40.722Z] ----------------------------------- [2025-06-26T16:49:40.722Z] [2025-06-26T16:49:40.722Z] TEST TEARDOWN: [2025-06-26T16:49:40.722Z] Nothing to be done for teardown. [2025-06-26T16:49:40.722Z] renaissance-movie-lens_0 Finish Time: Thu Jun 26 12:49:40 2025 Epoch Time (ms): 1750956580648