renaissance-movie-lens_0
[2025-09-24T20:11:17.216Z] Running test renaissance-movie-lens_0 ...
[2025-09-24T20:11:17.216Z] ===============================================
[2025-09-24T20:11:17.216Z] renaissance-movie-lens_0 Start Time: Wed Sep 24 16:11:17 2025 Epoch Time (ms): 1758744677149
[2025-09-24T20:11:17.216Z] variation: NoOptions
[2025-09-24T20:11:17.216Z] JVM_OPTIONS:
[2025-09-24T20:11:17.216Z] { \
[2025-09-24T20:11:17.216Z] echo ""; echo "TEST SETUP:"; \
[2025-09-24T20:11:17.216Z] echo "Nothing to be done for setup."; \
[2025-09-24T20:11:17.216Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17587439889819/renaissance-movie-lens_0"; \
[2025-09-24T20:11:17.216Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17587439889819/renaissance-movie-lens_0"; \
[2025-09-24T20:11:17.216Z] echo ""; echo "TESTING:"; \
[2025-09-24T20:11:17.216Z] "/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_17587439889819/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-24T20:11:17.216Z] 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_17587439889819/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-24T20:11:17.216Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-24T20:11:17.216Z] echo "Nothing to be done for teardown."; \
[2025-09-24T20:11:17.216Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17587439889819/TestTargetResult";
[2025-09-24T20:11:17.216Z]
[2025-09-24T20:11:17.216Z] TEST SETUP:
[2025-09-24T20:11:17.216Z] Nothing to be done for setup.
[2025-09-24T20:11:17.216Z]
[2025-09-24T20:11:17.216Z] TESTING:
[2025-09-24T20:11:21.170Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-09-24T20:11:25.155Z] 16:11:24.497 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-24T20:11:25.945Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-24T20:11:26.315Z] Training: 60056, validation: 20285, test: 19854
[2025-09-24T20:11:26.315Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-24T20:11:26.315Z] GC before operation: completed in 70.444 ms, heap usage 173.078 MB -> 75.940 MB.
[2025-09-24T20:11:30.368Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:11:32.786Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:11:35.234Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:11:37.012Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:11:38.346Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:11:39.571Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:11:40.798Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:11:42.040Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:11:42.410Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:11:42.410Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:11:42.410Z] Top recommended movies for user id 72:
[2025-09-24T20:11:42.410Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:11:42.410Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:11:42.410Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:11:42.410Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:11:42.410Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:11:42.410Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (16052.025 ms) ======
[2025-09-24T20:11:42.410Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-24T20:11:42.410Z] GC before operation: completed in 84.666 ms, heap usage 155.857 MB -> 87.573 MB.
[2025-09-24T20:11:44.192Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:11:45.994Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:11:47.777Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:11:49.567Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:11:50.828Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:11:51.671Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:11:52.905Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:11:53.687Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:11:54.044Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:11:54.044Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:11:54.044Z] Top recommended movies for user id 72:
[2025-09-24T20:11:54.044Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:11:54.044Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:11:54.044Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:11:54.044Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:11:54.044Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:11:54.044Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (11633.421 ms) ======
[2025-09-24T20:11:54.044Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-24T20:11:54.044Z] GC before operation: completed in 82.578 ms, heap usage 406.633 MB -> 88.772 MB.
[2025-09-24T20:11:55.824Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:11:57.607Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:11:59.400Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:12:00.656Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:12:01.913Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:12:02.689Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:12:03.970Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:12:04.739Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:12:04.739Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:12:04.739Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:12:05.093Z] Top recommended movies for user id 72:
[2025-09-24T20:12:05.093Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:12:05.093Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:12:05.093Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:12:05.093Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:12:05.093Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:12:05.093Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (10818.977 ms) ======
[2025-09-24T20:12:05.093Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-24T20:12:05.093Z] GC before operation: completed in 94.103 ms, heap usage 399.486 MB -> 89.365 MB.
[2025-09-24T20:12:06.856Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:12:08.708Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:12:09.931Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:12:11.696Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:12:12.925Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:12:13.679Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:12:14.449Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:12:15.688Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:12:15.688Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:12:15.688Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:12:15.688Z] Top recommended movies for user id 72:
[2025-09-24T20:12:15.688Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:12:15.688Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:12:15.688Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:12:15.688Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:12:15.688Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:12:15.688Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (10692.781 ms) ======
[2025-09-24T20:12:15.688Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-24T20:12:15.688Z] GC before operation: completed in 72.271 ms, heap usage 164.701 MB -> 89.462 MB.
[2025-09-24T20:12:17.452Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:12:19.245Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:12:20.497Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:12:22.259Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:12:23.041Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:12:24.303Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:12:25.073Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:12:25.857Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:12:26.212Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:12:26.212Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:12:26.212Z] Top recommended movies for user id 72:
[2025-09-24T20:12:26.212Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:12:26.212Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:12:26.212Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:12:26.212Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:12:26.212Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:12:26.212Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (10342.673 ms) ======
[2025-09-24T20:12:26.212Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-24T20:12:26.212Z] GC before operation: completed in 72.720 ms, heap usage 471.766 MB -> 89.822 MB.
[2025-09-24T20:12:27.981Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:12:29.764Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:12:31.535Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:12:32.798Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:12:34.065Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:12:36.025Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:12:36.025Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:12:36.818Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:12:36.818Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:12:36.818Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:12:36.818Z] Top recommended movies for user id 72:
[2025-09-24T20:12:36.818Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:12:36.818Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:12:36.818Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:12:36.818Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:12:36.819Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:12:36.819Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (10682.503 ms) ======
[2025-09-24T20:12:36.819Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-24T20:12:37.172Z] GC before operation: completed in 69.491 ms, heap usage 553.983 MB -> 93.506 MB.
[2025-09-24T20:12:38.949Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:12:40.198Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:12:41.969Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:12:43.799Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:12:44.562Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:12:45.325Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:12:46.579Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:12:47.352Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:12:47.352Z] 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.
[2025-09-24T20:12:47.352Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:12:47.703Z] Top recommended movies for user id 72:
[2025-09-24T20:12:47.703Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:12:47.703Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:12:47.703Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:12:47.703Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:12:47.703Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:12:47.703Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (10565.838 ms) ======
[2025-09-24T20:12:47.703Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-24T20:12:47.703Z] GC before operation: completed in 74.848 ms, heap usage 345.163 MB -> 90.474 MB.
[2025-09-24T20:12:49.474Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:12:50.705Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:12:52.483Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:12:53.745Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:12:54.994Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:12:55.768Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:12:56.574Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:12:57.813Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:12:57.813Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:12:57.813Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:12:57.813Z] Top recommended movies for user id 72:
[2025-09-24T20:12:57.813Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:12:57.813Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:12:57.813Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:12:57.813Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:12:57.813Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:12:57.813Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (10228.637 ms) ======
[2025-09-24T20:12:57.813Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-24T20:12:57.813Z] GC before operation: completed in 74.481 ms, heap usage 215.794 MB -> 89.925 MB.
[2025-09-24T20:12:59.601Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:13:01.455Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:13:02.704Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:13:04.528Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:13:05.305Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:13:06.088Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:13:07.322Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:13:08.121Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:13:08.478Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:13:08.478Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:13:08.478Z] Top recommended movies for user id 72:
[2025-09-24T20:13:08.478Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:13:08.478Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:13:08.478Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:13:08.478Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:13:08.478Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:13:08.478Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (10597.142 ms) ======
[2025-09-24T20:13:08.478Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-24T20:13:08.478Z] GC before operation: completed in 58.541 ms, heap usage 147.194 MB -> 89.694 MB.
[2025-09-24T20:13:10.267Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:13:12.079Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:13:13.848Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:13:15.097Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:13:16.336Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:13:17.111Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:13:18.350Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:13:19.301Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:13:19.301Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:13:19.301Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:13:19.666Z] Top recommended movies for user id 72:
[2025-09-24T20:13:19.666Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:13:19.666Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:13:19.666Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:13:19.666Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:13:19.666Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:13:19.666Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (10900.339 ms) ======
[2025-09-24T20:13:19.666Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-24T20:13:19.666Z] GC before operation: completed in 70.228 ms, heap usage 112.623 MB -> 89.827 MB.
[2025-09-24T20:13:21.465Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:13:22.708Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:13:23.976Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:13:25.757Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:13:26.519Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:13:27.307Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:13:28.076Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:13:29.357Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:13:29.357Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:13:29.357Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:13:29.357Z] Top recommended movies for user id 72:
[2025-09-24T20:13:29.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:13:29.357Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:13:29.357Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:13:29.357Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:13:29.357Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:13:29.357Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (9747.913 ms) ======
[2025-09-24T20:13:29.357Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-24T20:13:29.357Z] GC before operation: completed in 58.885 ms, heap usage 315.451 MB -> 89.801 MB.
[2025-09-24T20:13:30.618Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:13:31.853Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:13:33.634Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:13:34.420Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:13:35.198Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:13:35.958Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:13:37.233Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:13:37.616Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:13:37.965Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:13:37.965Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:13:37.965Z] Top recommended movies for user id 72:
[2025-09-24T20:13:37.965Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:13:37.965Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:13:37.965Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:13:37.965Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:13:37.965Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:13:37.965Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8509.320 ms) ======
[2025-09-24T20:13:37.965Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-24T20:13:37.965Z] GC before operation: completed in 60.045 ms, heap usage 262.450 MB -> 90.015 MB.
[2025-09-24T20:13:39.278Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:13:40.535Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:13:42.335Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:13:43.143Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:13:44.431Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:13:45.207Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:13:45.962Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:13:46.765Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:13:46.765Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:13:46.765Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:13:46.765Z] Top recommended movies for user id 72:
[2025-09-24T20:13:46.765Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:13:46.765Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:13:46.765Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:13:46.765Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:13:46.765Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:13:46.765Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8886.424 ms) ======
[2025-09-24T20:13:46.765Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-24T20:13:46.765Z] GC before operation: completed in 59.244 ms, heap usage 301.418 MB -> 90.129 MB.
[2025-09-24T20:13:48.530Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:13:49.766Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:13:50.999Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:13:52.762Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:13:53.127Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:13:53.885Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:13:55.113Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:13:55.886Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:13:55.886Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:13:55.886Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:13:55.886Z] Top recommended movies for user id 72:
[2025-09-24T20:13:55.886Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:13:55.886Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:13:55.886Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:13:55.886Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:13:55.886Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:13:55.886Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (9056.960 ms) ======
[2025-09-24T20:13:55.886Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-24T20:13:55.886Z] GC before operation: completed in 63.356 ms, heap usage 325.056 MB -> 89.957 MB.
[2025-09-24T20:13:57.157Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:13:58.919Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:14:00.171Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:14:01.423Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:14:02.236Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:14:03.020Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:14:03.796Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:14:04.572Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:14:04.937Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:14:04.937Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:14:04.937Z] Top recommended movies for user id 72:
[2025-09-24T20:14:04.937Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:14:04.937Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:14:04.937Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:14:04.937Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:14:04.937Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:14:04.937Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8868.881 ms) ======
[2025-09-24T20:14:04.937Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-24T20:14:04.937Z] GC before operation: completed in 56.763 ms, heap usage 121.593 MB -> 89.915 MB.
[2025-09-24T20:14:06.159Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:14:07.422Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:14:09.201Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:14:09.962Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:14:10.733Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:14:12.006Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:14:12.766Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:14:13.534Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:14:13.534Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:14:13.534Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:14:13.534Z] Top recommended movies for user id 72:
[2025-09-24T20:14:13.534Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:14:13.534Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:14:13.534Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:14:13.534Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:14:13.534Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:14:13.534Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8542.169 ms) ======
[2025-09-24T20:14:13.534Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-24T20:14:13.534Z] GC before operation: completed in 48.765 ms, heap usage 422.972 MB -> 90.193 MB.
[2025-09-24T20:14:14.761Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:14:15.993Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:14:17.250Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:14:18.512Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:14:19.291Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:14:20.057Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:14:20.825Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:14:21.615Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:14:21.615Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:14:21.615Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:14:21.970Z] Top recommended movies for user id 72:
[2025-09-24T20:14:21.970Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:14:21.971Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:14:21.971Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:14:21.971Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:14:21.971Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:14:21.971Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8294.324 ms) ======
[2025-09-24T20:14:21.971Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-24T20:14:21.971Z] GC before operation: completed in 53.542 ms, heap usage 217.933 MB -> 92.104 MB.
[2025-09-24T20:14:23.197Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:14:24.440Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:14:25.694Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:14:26.991Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:14:27.744Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:14:28.502Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:14:29.262Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:14:30.028Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:14:30.028Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:14:30.028Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:14:30.028Z] Top recommended movies for user id 72:
[2025-09-24T20:14:30.028Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:14:30.028Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:14:30.028Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:14:30.028Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:14:30.028Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:14:30.028Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8280.455 ms) ======
[2025-09-24T20:14:30.028Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-24T20:14:30.385Z] GC before operation: completed in 51.597 ms, heap usage 115.477 MB -> 89.724 MB.
[2025-09-24T20:14:31.618Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:14:32.849Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:14:34.084Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:14:35.324Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:14:35.681Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:14:36.442Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:14:37.203Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:14:37.962Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:14:37.962Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:14:38.311Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:14:38.311Z] Top recommended movies for user id 72:
[2025-09-24T20:14:38.311Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:14:38.311Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:14:38.311Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:14:38.311Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:14:38.311Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:14:38.311Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (7960.229 ms) ======
[2025-09-24T20:14:38.311Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-24T20:14:38.311Z] GC before operation: completed in 45.905 ms, heap usage 479.309 MB -> 90.414 MB.
[2025-09-24T20:14:39.547Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-24T20:14:41.332Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-24T20:14:42.568Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-24T20:14:43.859Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-24T20:14:45.095Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-24T20:14:45.853Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-24T20:14:46.622Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-24T20:14:47.902Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-24T20:14:47.902Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-09-24T20:14:47.902Z] The best model improves the baseline by 14.52%.
[2025-09-24T20:14:47.902Z] Top recommended movies for user id 72:
[2025-09-24T20:14:47.902Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-09-24T20:14:47.902Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-09-24T20:14:47.902Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-09-24T20:14:47.902Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-09-24T20:14:47.902Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-09-24T20:14:47.902Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (9596.261 ms) ======
[2025-09-24T20:14:48.257Z] -----------------------------------
[2025-09-24T20:14:48.257Z] renaissance-movie-lens_0_PASSED
[2025-09-24T20:14:48.257Z] -----------------------------------
[2025-09-24T20:14:48.257Z]
[2025-09-24T20:14:48.257Z] TEST TEARDOWN:
[2025-09-24T20:14:48.257Z] Nothing to be done for teardown.
[2025-09-24T20:14:48.257Z] renaissance-movie-lens_0 Finish Time: Wed Sep 24 16:14:47 2025 Epoch Time (ms): 1758744887901