[2025-05-28T23:41:41.395Z] Running test renaissance-movie-lens_0 ... [2025-05-28T23:41:41.395Z] =============================================== [2025-05-28T23:41:41.395Z] renaissance-movie-lens_0 Start Time: Wed May 28 19:41:41 2025 Epoch Time (ms): 1748475701058 [2025-05-28T23:41:41.395Z] variation: NoOptions [2025-05-28T23:41:41.395Z] JVM_OPTIONS: [2025-05-28T23:41:41.395Z] { \ [2025-05-28T23:41:41.395Z] echo ""; echo "TEST SETUP:"; \ [2025-05-28T23:41:41.395Z] echo "Nothing to be done for setup."; \ [2025-05-28T23:41:41.395Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484749396624/renaissance-movie-lens_0"; \ [2025-05-28T23:41:41.395Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484749396624/renaissance-movie-lens_0"; \ [2025-05-28T23:41:41.395Z] echo ""; echo "TESTING:"; \ [2025-05-28T23:41:41.396Z] "/Users/admin/workspace/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484749396624/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-28T23:41:41.396Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484749396624/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-28T23:41:41.396Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-28T23:41:41.396Z] echo "Nothing to be done for teardown."; \ [2025-05-28T23:41:41.396Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484749396624/TestTargetResult"; [2025-05-28T23:41:41.396Z] [2025-05-28T23:41:41.396Z] TEST SETUP: [2025-05-28T23:41:41.396Z] Nothing to be done for setup. [2025-05-28T23:41:41.396Z] [2025-05-28T23:41:41.396Z] TESTING: [2025-05-28T23:41:43.944Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-05-28T23:41:47.317Z] 19:41:46.539 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. [2025-05-28T23:41:47.747Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-28T23:41:48.131Z] Training: 60056, validation: 20285, test: 19854 [2025-05-28T23:41:48.131Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-28T23:41:48.131Z] GC before operation: completed in 69.351 ms, heap usage 317.135 MB -> 74.540 MB. [2025-05-28T23:41:51.427Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:41:53.321Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:41:54.655Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:41:55.993Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:41:57.321Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:41:58.160Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:41:58.992Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:41:59.823Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:41:59.823Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:41:59.823Z] The best model improves the baseline by 14.52%. [2025-05-28T23:41:59.823Z] Top recommended movies for user id 72: [2025-05-28T23:42:00.246Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:42:00.246Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:42:00.246Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:42:00.246Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:42:00.246Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:42:00.246Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11966.098 ms) ====== [2025-05-28T23:42:00.246Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-28T23:42:00.246Z] GC before operation: completed in 77.349 ms, heap usage 398.590 MB -> 85.439 MB. [2025-05-28T23:42:01.641Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:42:03.016Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:42:04.401Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:42:05.765Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:42:06.645Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:42:07.483Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:42:08.329Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:42:09.168Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:42:09.168Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:42:09.168Z] The best model improves the baseline by 14.52%. [2025-05-28T23:42:09.168Z] Top recommended movies for user id 72: [2025-05-28T23:42:09.168Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:42:09.168Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:42:09.168Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:42:09.168Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:42:09.168Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:42:09.168Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9116.734 ms) ====== [2025-05-28T23:42:09.168Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-28T23:42:09.168Z] GC before operation: completed in 72.685 ms, heap usage 319.977 MB -> 87.290 MB. [2025-05-28T23:42:10.522Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:42:12.517Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:42:13.871Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:42:15.222Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:42:15.616Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:42:16.458Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:42:17.334Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:42:18.687Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:42:18.687Z] 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. [2025-05-28T23:42:18.687Z] The best model improves the baseline by 14.52%. [2025-05-28T23:42:18.687Z] Top recommended movies for user id 72: [2025-05-28T23:42:18.687Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:42:18.687Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:42:18.687Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:42:18.687Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:42:18.687Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:42:18.687Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9310.687 ms) ====== [2025-05-28T23:42:18.687Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-28T23:42:18.687Z] GC before operation: completed in 63.653 ms, heap usage 189.726 MB -> 87.733 MB. [2025-05-28T23:42:20.121Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:42:21.449Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:42:22.795Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:42:24.157Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:42:24.979Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:42:25.815Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:42:26.661Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:42:27.495Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:42:27.495Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:42:27.495Z] The best model improves the baseline by 14.52%. [2025-05-28T23:42:27.915Z] Top recommended movies for user id 72: [2025-05-28T23:42:27.915Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:42:27.915Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:42:27.915Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:42:27.915Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:42:27.915Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:42:27.915Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9058.651 ms) ====== [2025-05-28T23:42:27.915Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-28T23:42:27.915Z] GC before operation: completed in 78.472 ms, heap usage 186.560 MB -> 88.015 MB. [2025-05-28T23:42:29.250Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:42:30.597Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:42:31.924Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:42:33.261Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:42:34.104Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:42:34.963Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:42:35.792Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:42:36.638Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:42:36.638Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:42:36.638Z] The best model improves the baseline by 14.52%. [2025-05-28T23:42:36.638Z] Top recommended movies for user id 72: [2025-05-28T23:42:36.638Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:42:36.638Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:42:36.638Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:42:36.638Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:42:36.638Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:42:36.638Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8833.272 ms) ====== [2025-05-28T23:42:36.638Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-28T23:42:36.638Z] GC before operation: completed in 74.753 ms, heap usage 457.437 MB -> 88.351 MB. [2025-05-28T23:42:37.992Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:42:39.346Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:42:40.695Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:42:42.030Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:42:42.865Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:42:43.704Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:42:44.538Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:42:45.377Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:42:45.377Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:42:45.377Z] The best model improves the baseline by 14.52%. [2025-05-28T23:42:45.787Z] Top recommended movies for user id 72: [2025-05-28T23:42:45.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:42:45.787Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:42:45.787Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:42:45.787Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:42:45.787Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:42:45.787Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8865.994 ms) ====== [2025-05-28T23:42:45.787Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-28T23:42:45.788Z] GC before operation: completed in 64.951 ms, heap usage 157.287 MB -> 88.368 MB. [2025-05-28T23:42:47.137Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:42:48.468Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:42:49.794Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:42:51.118Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:42:51.953Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:42:52.794Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:42:53.617Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:42:54.453Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:42:54.453Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:42:54.453Z] The best model improves the baseline by 14.52%. [2025-05-28T23:42:54.453Z] Top recommended movies for user id 72: [2025-05-28T23:42:54.453Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:42:54.453Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:42:54.453Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:42:54.453Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:42:54.453Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:42:54.453Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8875.911 ms) ====== [2025-05-28T23:42:54.453Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-28T23:42:54.453Z] GC before operation: completed in 63.235 ms, heap usage 108.088 MB -> 88.207 MB. [2025-05-28T23:42:55.808Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:42:57.153Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:42:59.079Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:42:59.912Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:43:00.766Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:43:01.619Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:43:02.464Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:43:03.346Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:43:03.748Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:43:03.748Z] The best model improves the baseline by 14.52%. [2025-05-28T23:43:03.748Z] Top recommended movies for user id 72: [2025-05-28T23:43:03.748Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:43:03.748Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:43:03.748Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:43:03.748Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:43:03.748Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:43:03.748Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9040.662 ms) ====== [2025-05-28T23:43:03.748Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-28T23:43:03.748Z] GC before operation: completed in 63.290 ms, heap usage 222.223 MB -> 88.525 MB. [2025-05-28T23:43:05.117Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:43:06.481Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:43:07.819Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:43:09.207Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:43:10.062Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:43:10.894Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:43:11.725Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:43:12.584Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:43:12.584Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:43:12.584Z] The best model improves the baseline by 14.52%. [2025-05-28T23:43:12.584Z] Top recommended movies for user id 72: [2025-05-28T23:43:12.584Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:43:12.584Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:43:12.584Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:43:12.584Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:43:12.584Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:43:12.584Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8901.681 ms) ====== [2025-05-28T23:43:12.584Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-28T23:43:12.584Z] GC before operation: completed in 61.783 ms, heap usage 274.191 MB -> 88.522 MB. [2025-05-28T23:43:13.933Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:43:15.272Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:43:16.627Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:43:17.975Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:43:18.804Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:43:19.639Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:43:20.477Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:43:21.311Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:43:21.311Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:43:21.311Z] The best model improves the baseline by 14.52%. [2025-05-28T23:43:21.311Z] Top recommended movies for user id 72: [2025-05-28T23:43:21.311Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:43:21.311Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:43:21.311Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:43:21.311Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:43:21.311Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:43:21.311Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8661.200 ms) ====== [2025-05-28T23:43:21.311Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-28T23:43:21.311Z] GC before operation: completed in 60.723 ms, heap usage 399.398 MB -> 88.896 MB. [2025-05-28T23:43:22.648Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:43:23.983Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:43:25.340Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:43:26.716Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:43:27.107Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:43:28.446Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:43:29.275Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:43:30.130Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:43:30.130Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:43:30.130Z] The best model improves the baseline by 14.52%. [2025-05-28T23:43:30.130Z] Top recommended movies for user id 72: [2025-05-28T23:43:30.130Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:43:30.130Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:43:30.130Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:43:30.130Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:43:30.130Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:43:30.130Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8775.260 ms) ====== [2025-05-28T23:43:30.130Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-28T23:43:30.130Z] GC before operation: completed in 60.780 ms, heap usage 159.573 MB -> 88.260 MB. [2025-05-28T23:43:31.464Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:43:32.799Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:43:34.150Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:43:35.476Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:43:35.863Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:43:36.721Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:43:37.549Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:43:38.396Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:43:38.396Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:43:38.396Z] The best model improves the baseline by 14.52%. [2025-05-28T23:43:38.783Z] Top recommended movies for user id 72: [2025-05-28T23:43:38.783Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:43:38.783Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:43:38.783Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:43:38.783Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:43:38.783Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:43:38.783Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8449.144 ms) ====== [2025-05-28T23:43:38.783Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-28T23:43:38.783Z] GC before operation: completed in 61.822 ms, heap usage 403.353 MB -> 88.814 MB. [2025-05-28T23:43:40.115Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:43:41.428Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:43:42.757Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:43:44.082Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:43:44.485Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:43:45.315Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:43:46.157Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:43:47.048Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:43:47.048Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:43:47.048Z] The best model improves the baseline by 14.52%. [2025-05-28T23:43:47.048Z] Top recommended movies for user id 72: [2025-05-28T23:43:47.048Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:43:47.048Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:43:47.048Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:43:47.048Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:43:47.048Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:43:47.048Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8441.229 ms) ====== [2025-05-28T23:43:47.048Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-28T23:43:47.048Z] GC before operation: completed in 63.694 ms, heap usage 155.029 MB -> 88.550 MB. [2025-05-28T23:43:48.375Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:43:49.729Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:43:51.066Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:43:52.410Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:43:53.250Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:43:54.081Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:43:54.930Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:43:55.780Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:43:55.780Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:43:55.780Z] The best model improves the baseline by 14.52%. [2025-05-28T23:43:55.780Z] Top recommended movies for user id 72: [2025-05-28T23:43:55.780Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:43:55.780Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:43:55.780Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:43:55.780Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:43:55.780Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:43:55.780Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8701.591 ms) ====== [2025-05-28T23:43:55.780Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-28T23:43:56.165Z] GC before operation: completed in 63.952 ms, heap usage 157.920 MB -> 88.350 MB. [2025-05-28T23:43:57.499Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:43:58.824Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:44:00.244Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:44:01.104Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:44:01.979Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:44:02.832Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:44:03.694Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:44:04.570Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:44:04.570Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:44:04.570Z] The best model improves the baseline by 14.52%. [2025-05-28T23:44:04.570Z] Top recommended movies for user id 72: [2025-05-28T23:44:04.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:44:04.570Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:44:04.570Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:44:04.570Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:44:04.570Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:44:04.570Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8572.345 ms) ====== [2025-05-28T23:44:04.570Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-28T23:44:04.570Z] GC before operation: completed in 65.640 ms, heap usage 371.822 MB -> 88.942 MB. [2025-05-28T23:44:05.949Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:44:07.293Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:44:08.622Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:44:09.974Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:44:10.799Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:44:11.635Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:44:12.510Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:44:12.900Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:44:13.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:44:13.291Z] The best model improves the baseline by 14.52%. [2025-05-28T23:44:13.291Z] Top recommended movies for user id 72: [2025-05-28T23:44:13.291Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:44:13.291Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:44:13.291Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:44:13.291Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:44:13.291Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:44:13.291Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8551.132 ms) ====== [2025-05-28T23:44:13.291Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-28T23:44:13.291Z] GC before operation: completed in 63.043 ms, heap usage 157.600 MB -> 88.515 MB. [2025-05-28T23:44:14.660Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:44:15.529Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:44:16.868Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:44:17.699Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:44:18.563Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:44:19.385Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:44:20.230Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:44:21.102Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:44:21.102Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:44:21.102Z] The best model improves the baseline by 14.52%. [2025-05-28T23:44:21.102Z] Top recommended movies for user id 72: [2025-05-28T23:44:21.102Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:44:21.102Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:44:21.102Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:44:21.102Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:44:21.102Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:44:21.102Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (7821.447 ms) ====== [2025-05-28T23:44:21.102Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-28T23:44:21.102Z] GC before operation: completed in 64.158 ms, heap usage 129.419 MB -> 88.492 MB. [2025-05-28T23:44:22.444Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:44:23.776Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:44:25.122Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:44:26.451Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:44:27.320Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:44:27.710Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:44:28.544Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:44:29.376Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:44:29.763Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:44:29.763Z] The best model improves the baseline by 14.52%. [2025-05-28T23:44:29.763Z] Top recommended movies for user id 72: [2025-05-28T23:44:29.763Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:44:29.763Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:44:29.763Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:44:29.763Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:44:29.763Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:44:29.763Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8564.645 ms) ====== [2025-05-28T23:44:29.763Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-28T23:44:29.763Z] GC before operation: completed in 65.776 ms, heap usage 154.321 MB -> 88.398 MB. [2025-05-28T23:44:31.113Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:44:32.456Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:44:33.816Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:44:35.143Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:44:35.540Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:44:36.377Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:44:37.215Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:44:38.058Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:44:38.443Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:44:38.443Z] The best model improves the baseline by 14.52%. [2025-05-28T23:44:38.443Z] Top recommended movies for user id 72: [2025-05-28T23:44:38.443Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:44:38.443Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:44:38.443Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:44:38.443Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:44:38.443Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:44:38.443Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8612.461 ms) ====== [2025-05-28T23:44:38.443Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-28T23:44:38.443Z] GC before operation: completed in 61.091 ms, heap usage 162.461 MB -> 88.484 MB. [2025-05-28T23:44:39.793Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:44:41.110Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:44:42.440Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:44:43.771Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:44:44.593Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:44:45.450Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:44:46.287Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:44:47.110Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:44:47.110Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-05-28T23:44:47.110Z] The best model improves the baseline by 14.52%. [2025-05-28T23:44:47.110Z] Top recommended movies for user id 72: [2025-05-28T23:44:47.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T23:44:47.110Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T23:44:47.110Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T23:44:47.110Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T23:44:47.110Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T23:44:47.110Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8685.288 ms) ====== [2025-05-28T23:44:47.496Z] ----------------------------------- [2025-05-28T23:44:47.496Z] renaissance-movie-lens_0_PASSED [2025-05-28T23:44:47.496Z] ----------------------------------- [2025-05-28T23:44:47.496Z] [2025-05-28T23:44:47.496Z] TEST TEARDOWN: [2025-05-28T23:44:47.496Z] Nothing to be done for teardown. [2025-05-28T23:44:47.496Z] renaissance-movie-lens_0 Finish Time: Wed May 28 19:44:47 2025 Epoch Time (ms): 1748475887170