[2025-06-30T19:43:59.385Z] Running test renaissance-movie-lens_0 ... [2025-06-30T19:43:59.385Z] =============================================== [2025-06-30T19:43:59.385Z] renaissance-movie-lens_0 Start Time: Mon Jun 30 15:43:59 2025 Epoch Time (ms): 1751312639195 [2025-06-30T19:43:59.385Z] variation: NoOptions [2025-06-30T19:43:59.385Z] JVM_OPTIONS: [2025-06-30T19:43:59.385Z] { \ [2025-06-30T19:43:59.385Z] echo ""; echo "TEST SETUP:"; \ [2025-06-30T19:43:59.385Z] echo "Nothing to be done for setup."; \ [2025-06-30T19:43:59.385Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17513120162304/renaissance-movie-lens_0"; \ [2025-06-30T19:43:59.385Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17513120162304/renaissance-movie-lens_0"; \ [2025-06-30T19:43:59.385Z] echo ""; echo "TESTING:"; \ [2025-06-30T19:43:59.385Z] "/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_17513120162304/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-30T19:43:59.385Z] 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_17513120162304/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-30T19:43:59.385Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-30T19:43:59.385Z] echo "Nothing to be done for teardown."; \ [2025-06-30T19:43:59.385Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17513120162304/TestTargetResult"; [2025-06-30T19:43:59.385Z] [2025-06-30T19:43:59.385Z] TEST SETUP: [2025-06-30T19:43:59.385Z] Nothing to be done for setup. [2025-06-30T19:43:59.385Z] [2025-06-30T19:43:59.385Z] TESTING: [2025-06-30T19:44:02.590Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-06-30T19:44:05.761Z] 15:44:05.212 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. [2025-06-30T19:44:07.021Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-30T19:44:07.021Z] Training: 60056, validation: 20285, test: 19854 [2025-06-30T19:44:07.021Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-30T19:44:07.021Z] GC before operation: completed in 76.857 ms, heap usage 147.232 MB -> 75.837 MB. [2025-06-30T19:44:10.230Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:44:12.029Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:44:13.895Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:44:15.685Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:44:16.462Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:44:17.692Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:44:19.024Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:44:20.266Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:44:20.267Z] 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. [2025-06-30T19:44:20.267Z] The best model improves the baseline by 14.52%. [2025-06-30T19:44:20.267Z] Top recommended movies for user id 72: [2025-06-30T19:44:20.267Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:44:20.267Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:44:20.267Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:44:20.267Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:44:20.267Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:44:20.267Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (13164.890 ms) ====== [2025-06-30T19:44:20.267Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-30T19:44:20.267Z] GC before operation: completed in 79.811 ms, heap usage 356.378 MB -> 88.865 MB. [2025-06-30T19:44:22.034Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:44:23.837Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:44:25.105Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:44:26.890Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:44:27.657Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:44:28.416Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:44:29.193Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:44:29.986Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:44:30.363Z] 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. [2025-06-30T19:44:30.363Z] The best model improves the baseline by 14.52%. [2025-06-30T19:44:30.363Z] Top recommended movies for user id 72: [2025-06-30T19:44:30.363Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:44:30.363Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:44:30.363Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:44:30.363Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:44:30.363Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:44:30.363Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9970.152 ms) ====== [2025-06-30T19:44:30.363Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-30T19:44:30.363Z] GC before operation: completed in 65.742 ms, heap usage 153.997 MB -> 88.323 MB. [2025-06-30T19:44:32.143Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:44:33.400Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:44:35.221Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:44:36.461Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:44:37.725Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:44:38.500Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:44:39.264Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:44:40.042Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:44:40.405Z] 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. [2025-06-30T19:44:40.405Z] The best model improves the baseline by 14.52%. [2025-06-30T19:44:40.405Z] Top recommended movies for user id 72: [2025-06-30T19:44:40.405Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:44:40.405Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:44:40.405Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:44:40.405Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:44:40.405Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:44:40.405Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9948.409 ms) ====== [2025-06-30T19:44:40.405Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-30T19:44:40.405Z] GC before operation: completed in 70.762 ms, heap usage 147.888 MB -> 88.983 MB. [2025-06-30T19:44:42.175Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:44:43.418Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:44:45.200Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:44:46.425Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:44:47.192Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:44:47.973Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:44:49.219Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:44:50.029Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:44:50.385Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-06-30T19:44:50.385Z] The best model improves the baseline by 14.52%. [2025-06-30T19:44:50.385Z] Top recommended movies for user id 72: [2025-06-30T19:44:50.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:44:50.385Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:44:50.385Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:44:50.385Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:44:50.385Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:44:50.385Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9982.747 ms) ====== [2025-06-30T19:44:50.385Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-30T19:44:50.385Z] GC before operation: completed in 81.272 ms, heap usage 235.899 MB -> 89.400 MB. [2025-06-30T19:44:52.180Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:44:53.412Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:44:54.694Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:44:56.480Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:44:57.240Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:44:58.003Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:44:58.840Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:44:59.610Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:44:59.610Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-06-30T19:44:59.610Z] The best model improves the baseline by 14.52%. [2025-06-30T19:44:59.610Z] Top recommended movies for user id 72: [2025-06-30T19:44:59.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:44:59.610Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:44:59.610Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:44:59.610Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:44:59.610Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:44:59.610Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (9181.369 ms) ====== [2025-06-30T19:44:59.610Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-30T19:44:59.610Z] GC before operation: completed in 71.716 ms, heap usage 262.457 MB -> 89.351 MB. [2025-06-30T19:45:00.846Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:45:02.091Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:45:03.339Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:45:04.609Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:45:05.390Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:45:06.178Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:45:06.937Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:45:07.708Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:45:08.072Z] 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. [2025-06-30T19:45:08.072Z] The best model improves the baseline by 14.52%. [2025-06-30T19:45:08.072Z] Top recommended movies for user id 72: [2025-06-30T19:45:08.072Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:45:08.072Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:45:08.072Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:45:08.072Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:45:08.072Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:45:08.072Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8264.690 ms) ====== [2025-06-30T19:45:08.072Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-30T19:45:08.072Z] GC before operation: completed in 69.274 ms, heap usage 141.351 MB -> 90.476 MB. [2025-06-30T19:45:09.898Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:45:11.189Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:45:12.437Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:45:13.686Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:45:14.970Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:45:15.792Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:45:16.577Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:45:17.352Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:45:17.352Z] 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. [2025-06-30T19:45:17.352Z] The best model improves the baseline by 14.52%. [2025-06-30T19:45:17.705Z] Top recommended movies for user id 72: [2025-06-30T19:45:17.705Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:45:17.705Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:45:17.705Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:45:17.705Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:45:17.705Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:45:17.705Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (9503.132 ms) ====== [2025-06-30T19:45:17.705Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-30T19:45:17.705Z] GC before operation: completed in 70.873 ms, heap usage 212.067 MB -> 89.470 MB. [2025-06-30T19:45:18.940Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:45:20.714Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:45:22.555Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:45:23.795Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:45:24.563Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:45:25.366Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:45:26.615Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:45:27.400Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:45:27.768Z] 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. [2025-06-30T19:45:27.768Z] The best model improves the baseline by 14.52%. [2025-06-30T19:45:27.768Z] Top recommended movies for user id 72: [2025-06-30T19:45:27.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:45:27.768Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:45:27.768Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:45:27.768Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:45:27.768Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:45:27.768Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (10095.767 ms) ====== [2025-06-30T19:45:27.768Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-30T19:45:27.768Z] GC before operation: completed in 71.719 ms, heap usage 212.452 MB -> 89.721 MB. [2025-06-30T19:45:29.601Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:45:30.845Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:45:32.095Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:45:33.869Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:45:34.652Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:45:35.419Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:45:36.208Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:45:37.451Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:45:37.451Z] 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. [2025-06-30T19:45:37.451Z] The best model improves the baseline by 14.52%. [2025-06-30T19:45:37.451Z] Top recommended movies for user id 72: [2025-06-30T19:45:37.451Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:45:37.451Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:45:37.451Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:45:37.451Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:45:37.451Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:45:37.451Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (9627.287 ms) ====== [2025-06-30T19:45:37.451Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-30T19:45:37.451Z] GC before operation: completed in 80.092 ms, heap usage 392.492 MB -> 89.909 MB. [2025-06-30T19:45:39.232Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:45:40.566Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:45:42.364Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:45:43.657Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:45:44.438Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:45:45.233Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:45:46.048Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:45:46.843Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:45:46.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-06-30T19:45:46.843Z] The best model improves the baseline by 14.52%. [2025-06-30T19:45:47.205Z] Top recommended movies for user id 72: [2025-06-30T19:45:47.205Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:45:47.205Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:45:47.205Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:45:47.205Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:45:47.205Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:45:47.205Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (9520.221 ms) ====== [2025-06-30T19:45:47.205Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-30T19:45:47.205Z] GC before operation: completed in 76.632 ms, heap usage 230.145 MB -> 89.969 MB. [2025-06-30T19:45:48.442Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:45:50.224Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:45:51.478Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:45:52.712Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:45:53.947Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:45:54.720Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:45:55.490Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:45:56.253Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:45:56.253Z] 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. [2025-06-30T19:45:56.607Z] The best model improves the baseline by 14.52%. [2025-06-30T19:45:56.607Z] Top recommended movies for user id 72: [2025-06-30T19:45:56.607Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:45:56.607Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:45:56.607Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:45:56.607Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:45:56.607Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:45:56.607Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (9379.793 ms) ====== [2025-06-30T19:45:56.607Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-30T19:45:56.607Z] GC before operation: completed in 106.411 ms, heap usage 229.461 MB -> 89.626 MB. [2025-06-30T19:45:57.886Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:45:59.670Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:46:00.913Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:46:02.206Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:46:03.492Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:46:03.882Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:46:05.161Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:46:05.561Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:46:05.941Z] 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. [2025-06-30T19:46:05.941Z] The best model improves the baseline by 14.52%. [2025-06-30T19:46:05.941Z] Top recommended movies for user id 72: [2025-06-30T19:46:05.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:46:05.941Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:46:05.941Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:46:05.941Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:46:05.941Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:46:05.941Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (9300.573 ms) ====== [2025-06-30T19:46:05.941Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-30T19:46:05.941Z] GC before operation: completed in 72.603 ms, heap usage 401.958 MB -> 90.188 MB. [2025-06-30T19:46:07.744Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:46:08.996Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:46:10.279Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:46:11.521Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:46:12.290Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:46:13.080Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:46:13.858Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:46:14.645Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:46:14.645Z] 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. [2025-06-30T19:46:14.645Z] The best model improves the baseline by 14.52%. [2025-06-30T19:46:14.645Z] Top recommended movies for user id 72: [2025-06-30T19:46:14.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:46:14.645Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:46:14.645Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:46:14.645Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:46:14.645Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:46:14.645Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8738.920 ms) ====== [2025-06-30T19:46:14.645Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-30T19:46:14.645Z] GC before operation: completed in 82.717 ms, heap usage 205.041 MB -> 89.882 MB. [2025-06-30T19:46:16.432Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:46:17.696Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:46:18.953Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:46:20.185Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:46:20.986Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:46:21.755Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:46:22.537Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:46:23.326Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:46:23.687Z] 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. [2025-06-30T19:46:23.687Z] The best model improves the baseline by 14.52%. [2025-06-30T19:46:23.687Z] Top recommended movies for user id 72: [2025-06-30T19:46:23.687Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:46:23.687Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:46:23.687Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:46:23.687Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:46:23.687Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:46:23.687Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8820.028 ms) ====== [2025-06-30T19:46:23.687Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-30T19:46:23.687Z] GC before operation: completed in 76.187 ms, heap usage 236.687 MB -> 89.829 MB. [2025-06-30T19:46:24.938Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:46:26.193Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:46:27.442Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:46:28.700Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:46:29.471Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:46:30.243Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:46:31.023Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:46:31.815Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:46:31.815Z] 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. [2025-06-30T19:46:31.815Z] The best model improves the baseline by 14.52%. [2025-06-30T19:46:31.815Z] Top recommended movies for user id 72: [2025-06-30T19:46:31.815Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:46:31.815Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:46:31.815Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:46:31.815Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:46:31.815Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:46:31.815Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8250.147 ms) ====== [2025-06-30T19:46:31.815Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-30T19:46:32.192Z] GC before operation: completed in 74.199 ms, heap usage 222.761 MB -> 89.998 MB. [2025-06-30T19:46:33.445Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:46:35.249Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:46:36.060Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:46:37.330Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:46:38.138Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:46:38.930Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:46:39.725Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:46:40.513Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:46:40.513Z] 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. [2025-06-30T19:46:40.513Z] The best model improves the baseline by 14.52%. [2025-06-30T19:46:40.513Z] Top recommended movies for user id 72: [2025-06-30T19:46:40.513Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:46:40.513Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:46:40.513Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:46:40.513Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:46:40.513Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:46:40.513Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8596.504 ms) ====== [2025-06-30T19:46:40.513Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-30T19:46:40.878Z] GC before operation: completed in 87.378 ms, heap usage 473.562 MB -> 90.288 MB. [2025-06-30T19:46:42.172Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:46:43.436Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:46:44.677Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:46:46.004Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:46:46.382Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:46:47.158Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:46:47.948Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:46:48.730Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:46:49.088Z] 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. [2025-06-30T19:46:49.088Z] The best model improves the baseline by 14.52%. [2025-06-30T19:46:49.088Z] Top recommended movies for user id 72: [2025-06-30T19:46:49.088Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:46:49.088Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:46:49.088Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:46:49.088Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:46:49.088Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:46:49.088Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8294.555 ms) ====== [2025-06-30T19:46:49.088Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-30T19:46:49.088Z] GC before operation: completed in 82.376 ms, heap usage 185.566 MB -> 89.799 MB. [2025-06-30T19:46:50.868Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:46:52.135Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:46:53.380Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:46:54.635Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:46:55.011Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:46:55.808Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:46:56.580Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:46:57.355Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:46:57.717Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-06-30T19:46:57.717Z] The best model improves the baseline by 14.52%. [2025-06-30T19:46:57.717Z] Top recommended movies for user id 72: [2025-06-30T19:46:57.717Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:46:57.717Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:46:57.717Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:46:57.717Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:46:57.717Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:46:57.717Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8564.086 ms) ====== [2025-06-30T19:46:57.717Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-30T19:46:57.717Z] GC before operation: completed in 81.744 ms, heap usage 237.288 MB -> 89.716 MB. [2025-06-30T19:46:58.941Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:47:00.203Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:47:01.480Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:47:03.343Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:47:03.711Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:47:04.480Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:47:05.258Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:47:06.049Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:47:06.049Z] 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. [2025-06-30T19:47:06.049Z] The best model improves the baseline by 14.52%. [2025-06-30T19:47:06.416Z] Top recommended movies for user id 72: [2025-06-30T19:47:06.416Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:47:06.416Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:47:06.416Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:47:06.416Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:47:06.416Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:47:06.416Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8518.862 ms) ====== [2025-06-30T19:47:06.416Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-30T19:47:06.416Z] GC before operation: completed in 74.828 ms, heap usage 338.058 MB -> 90.083 MB. [2025-06-30T19:47:07.663Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T19:47:09.446Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T19:47:10.698Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T19:47:11.935Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T19:47:12.712Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T19:47:13.493Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T19:47:14.748Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T19:47:15.514Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T19:47:15.514Z] 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. [2025-06-30T19:47:15.514Z] The best model improves the baseline by 14.52%. [2025-06-30T19:47:15.514Z] Top recommended movies for user id 72: [2025-06-30T19:47:15.514Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-30T19:47:15.514Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-30T19:47:15.514Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-30T19:47:15.514Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-30T19:47:15.514Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-30T19:47:15.514Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (9275.861 ms) ====== [2025-06-30T19:47:15.869Z] ----------------------------------- [2025-06-30T19:47:15.869Z] renaissance-movie-lens_0_PASSED [2025-06-30T19:47:15.869Z] ----------------------------------- [2025-06-30T19:47:15.869Z] [2025-06-30T19:47:15.869Z] TEST TEARDOWN: [2025-06-30T19:47:15.869Z] Nothing to be done for teardown. [2025-06-30T19:47:15.869Z] renaissance-movie-lens_0 Finish Time: Mon Jun 30 15:47:15 2025 Epoch Time (ms): 1751312835694