renaissance-movie-lens_0
[2025-11-05T22:30:03.299Z] Running test renaissance-movie-lens_0 ...
[2025-11-05T22:30:03.299Z] ===============================================
[2025-11-05T22:30:03.299Z] renaissance-movie-lens_0 Start Time: Wed Nov 5 17:30:03 2025 Epoch Time (ms): 1762381803118
[2025-11-05T22:30:03.299Z] variation: NoOptions
[2025-11-05T22:30:03.299Z] JVM_OPTIONS:
[2025-11-05T22:30:03.299Z] { \
[2025-11-05T22:30:03.299Z] echo ""; echo "TEST SETUP:"; \
[2025-11-05T22:30:03.299Z] echo "Nothing to be done for setup."; \
[2025-11-05T22:30:03.299Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17623813625276/renaissance-movie-lens_0"; \
[2025-11-05T22:30:03.299Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17623813625276/renaissance-movie-lens_0"; \
[2025-11-05T22:30:03.299Z] echo ""; echo "TESTING:"; \
[2025-11-05T22:30:03.299Z] "/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_17623813625276/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-05T22:30:03.299Z] 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_17623813625276/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-05T22:30:03.299Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-05T22:30:03.299Z] echo "Nothing to be done for teardown."; \
[2025-11-05T22:30:03.299Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17623813625276/TestTargetResult";
[2025-11-05T22:30:03.299Z]
[2025-11-05T22:30:03.299Z] TEST SETUP:
[2025-11-05T22:30:03.299Z] Nothing to be done for setup.
[2025-11-05T22:30:03.299Z]
[2025-11-05T22:30:03.299Z] TESTING:
[2025-11-05T22:30:05.849Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-05T22:30:09.079Z] 17:30:08.591 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-05T22:30:09.882Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-05T22:30:09.882Z] Training: 60056, validation: 20285, test: 19854
[2025-11-05T22:30:09.882Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-05T22:30:09.882Z] GC before operation: completed in 50.712 ms, heap usage 234.958 MB -> 76.117 MB.
[2025-11-05T22:30:12.456Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:30:14.361Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:30:15.632Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:30:16.906Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:30:17.721Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:30:19.016Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:30:19.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:30:21.133Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:30:21.133Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:30:21.133Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:30:21.133Z] Top recommended movies for user id 72:
[2025-11-05T22:30:21.133Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:30:21.133Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:30:21.133Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:30:21.133Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:30:21.133Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:30:21.133Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11256.010 ms) ======
[2025-11-05T22:30:21.133Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-05T22:30:21.133Z] GC before operation: completed in 64.316 ms, heap usage 291.735 MB -> 86.866 MB.
[2025-11-05T22:30:22.491Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:30:24.405Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:30:25.770Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:30:26.628Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:30:27.405Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:30:28.201Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:30:29.060Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:30:29.929Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:30:29.929Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:30:29.929Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:30:29.929Z] Top recommended movies for user id 72:
[2025-11-05T22:30:29.929Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:30:29.929Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:30:29.929Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:30:29.929Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:30:29.929Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:30:29.929Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8618.876 ms) ======
[2025-11-05T22:30:29.929Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-05T22:30:29.929Z] GC before operation: completed in 52.709 ms, heap usage 209.943 MB -> 88.863 MB.
[2025-11-05T22:30:31.209Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:30:32.455Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:30:33.701Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:30:35.526Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:30:35.903Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:30:37.162Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:30:37.951Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:30:38.731Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:30:38.731Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:30:38.731Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:30:38.731Z] Top recommended movies for user id 72:
[2025-11-05T22:30:38.731Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:30:38.731Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:30:38.731Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:30:38.731Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:30:38.731Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:30:38.731Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9016.850 ms) ======
[2025-11-05T22:30:38.731Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-05T22:30:39.083Z] GC before operation: completed in 75.555 ms, heap usage 339.767 MB -> 89.772 MB.
[2025-11-05T22:30:40.353Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:30:42.132Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:30:43.368Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:30:44.614Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:30:45.867Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:30:46.659Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:30:47.015Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:30:48.259Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:30:48.259Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:30:48.259Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:30:48.259Z] Top recommended movies for user id 72:
[2025-11-05T22:30:48.259Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:30:48.259Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:30:48.259Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:30:48.259Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:30:48.259Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:30:48.259Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9259.209 ms) ======
[2025-11-05T22:30:48.259Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-05T22:30:48.259Z] GC before operation: completed in 56.776 ms, heap usage 306.916 MB -> 90.088 MB.
[2025-11-05T22:30:49.517Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:30:50.761Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:30:52.023Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:30:53.274Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:30:54.048Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:30:54.811Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:30:55.589Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:30:56.352Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:30:56.352Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:30:56.352Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:30:56.352Z] Top recommended movies for user id 72:
[2025-11-05T22:30:56.352Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:30:56.352Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:30:56.352Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:30:56.352Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:30:56.352Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:30:56.352Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8109.694 ms) ======
[2025-11-05T22:30:56.352Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-05T22:30:56.352Z] GC before operation: completed in 45.815 ms, heap usage 300.294 MB -> 90.025 MB.
[2025-11-05T22:30:57.593Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:30:58.868Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:30:59.714Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:01.100Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:01.465Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:02.057Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:02.878Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:03.274Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:03.643Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:03.643Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:03.643Z] Top recommended movies for user id 72:
[2025-11-05T22:31:03.643Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:03.643Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:03.643Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:03.643Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:03.643Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:03.643Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (7134.142 ms) ======
[2025-11-05T22:31:03.643Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-05T22:31:03.643Z] GC before operation: completed in 51.175 ms, heap usage 366.296 MB -> 90.434 MB.
[2025-11-05T22:31:05.000Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:31:06.290Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:31:07.573Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:08.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:09.218Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:10.007Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:10.409Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:11.186Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:11.186Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:11.186Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:11.186Z] Top recommended movies for user id 72:
[2025-11-05T22:31:11.186Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:11.186Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:11.186Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:11.186Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:11.186Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:11.186Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7616.511 ms) ======
[2025-11-05T22:31:11.186Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-05T22:31:11.186Z] GC before operation: completed in 52.317 ms, heap usage 521.295 MB -> 90.609 MB.
[2025-11-05T22:31:12.476Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:31:13.252Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:31:14.509Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:15.266Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:16.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:16.382Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:17.143Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:17.515Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:17.515Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:17.515Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:17.876Z] Top recommended movies for user id 72:
[2025-11-05T22:31:17.876Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:17.876Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:17.876Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:17.876Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:17.876Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:17.876Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (6397.384 ms) ======
[2025-11-05T22:31:17.876Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-05T22:31:17.876Z] GC before operation: completed in 49.913 ms, heap usage 491.778 MB -> 90.914 MB.
[2025-11-05T22:31:18.635Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:31:19.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:31:20.631Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:21.872Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:22.239Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:22.599Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:23.358Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:24.124Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:24.124Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:24.124Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:24.124Z] Top recommended movies for user id 72:
[2025-11-05T22:31:24.124Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:24.124Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:24.124Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:24.124Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:24.124Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:24.124Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (6519.013 ms) ======
[2025-11-05T22:31:24.124Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-05T22:31:24.488Z] GC before operation: completed in 60.393 ms, heap usage 188.038 MB -> 90.217 MB.
[2025-11-05T22:31:25.728Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:31:26.496Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:31:27.728Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:28.572Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:29.350Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:30.120Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:30.901Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:31.269Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:31.719Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:31.719Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:31.719Z] Top recommended movies for user id 72:
[2025-11-05T22:31:31.719Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:31.719Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:31.719Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:31.719Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:31.719Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:31.719Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (7280.303 ms) ======
[2025-11-05T22:31:31.719Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-05T22:31:31.719Z] GC before operation: completed in 53.216 ms, heap usage 264.475 MB -> 90.631 MB.
[2025-11-05T22:31:32.941Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:31:34.741Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:31:35.981Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:37.218Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:37.980Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:38.732Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:39.495Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:40.264Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:40.613Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:40.613Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:40.613Z] Top recommended movies for user id 72:
[2025-11-05T22:31:40.613Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:40.613Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:40.613Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:40.613Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:40.613Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:40.613Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8869.138 ms) ======
[2025-11-05T22:31:40.613Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-05T22:31:40.613Z] GC before operation: completed in 51.397 ms, heap usage 192.727 MB -> 90.193 MB.
[2025-11-05T22:31:41.845Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:31:43.094Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:31:44.320Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:46.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:46.454Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:47.223Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:47.977Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:48.742Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:48.742Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:48.742Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:49.092Z] Top recommended movies for user id 72:
[2025-11-05T22:31:49.092Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:49.092Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:49.092Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:49.092Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:49.092Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:49.092Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8366.743 ms) ======
[2025-11-05T22:31:49.092Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-05T22:31:49.092Z] GC before operation: completed in 68.807 ms, heap usage 491.642 MB -> 90.921 MB.
[2025-11-05T22:31:50.858Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:31:52.101Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:31:53.347Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:31:55.125Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:31:55.896Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:31:57.171Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:31:57.957Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:31:59.218Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:31:59.218Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:31:59.218Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:31:59.218Z] Top recommended movies for user id 72:
[2025-11-05T22:31:59.218Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:31:59.218Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:31:59.218Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:31:59.218Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:31:59.218Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:31:59.218Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (10262.407 ms) ======
[2025-11-05T22:31:59.218Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-05T22:31:59.218Z] GC before operation: completed in 68.826 ms, heap usage 291.653 MB -> 90.716 MB.
[2025-11-05T22:32:01.653Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:32:02.955Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:32:04.832Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:32:06.622Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:32:07.882Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:32:08.641Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:32:09.410Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:32:10.673Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:32:10.673Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:32:10.673Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:32:10.673Z] Top recommended movies for user id 72:
[2025-11-05T22:32:10.673Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:32:10.673Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:32:10.673Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:32:10.673Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:32:10.673Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:32:10.673Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11415.753 ms) ======
[2025-11-05T22:32:10.673Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-05T22:32:10.673Z] GC before operation: completed in 69.163 ms, heap usage 259.138 MB -> 90.536 MB.
[2025-11-05T22:32:12.471Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:32:14.276Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:32:16.073Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:32:17.314Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:32:18.089Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:32:19.378Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:32:20.148Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:32:21.392Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:32:21.392Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:32:21.393Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:32:21.393Z] Top recommended movies for user id 72:
[2025-11-05T22:32:21.393Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:32:21.393Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:32:21.393Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:32:21.393Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:32:21.393Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:32:21.393Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (10646.934 ms) ======
[2025-11-05T22:32:21.393Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-05T22:32:21.393Z] GC before operation: completed in 65.493 ms, heap usage 227.551 MB -> 90.583 MB.
[2025-11-05T22:32:23.811Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:32:25.069Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:32:26.896Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:32:28.720Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:32:29.971Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:32:30.754Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:32:32.004Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:32:32.797Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:32:33.170Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:32:33.171Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:32:33.171Z] Top recommended movies for user id 72:
[2025-11-05T22:32:33.171Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:32:33.171Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:32:33.171Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:32:33.171Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:32:33.171Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:32:33.171Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11550.694 ms) ======
[2025-11-05T22:32:33.171Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-05T22:32:33.171Z] GC before operation: completed in 67.956 ms, heap usage 473.474 MB -> 90.902 MB.
[2025-11-05T22:32:35.007Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:32:36.787Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:32:38.563Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:32:40.378Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:32:41.148Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:32:42.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:32:43.295Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:32:44.563Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:32:44.563Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:32:44.563Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:32:44.563Z] Top recommended movies for user id 72:
[2025-11-05T22:32:44.563Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:32:44.563Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:32:44.563Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:32:44.563Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:32:44.563Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:32:44.563Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (11439.385 ms) ======
[2025-11-05T22:32:44.563Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-05T22:32:44.563Z] GC before operation: completed in 66.119 ms, heap usage 168.367 MB -> 90.540 MB.
[2025-11-05T22:32:46.357Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:32:48.128Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:32:49.898Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:32:51.674Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:32:52.436Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:32:53.694Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:32:54.498Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:32:55.743Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:32:55.743Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:32:55.743Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:32:55.743Z] Top recommended movies for user id 72:
[2025-11-05T22:32:55.743Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:32:55.743Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:32:55.743Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:32:55.743Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:32:55.743Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:32:55.743Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11135.493 ms) ======
[2025-11-05T22:32:55.743Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-05T22:32:55.743Z] GC before operation: completed in 66.750 ms, heap usage 371.506 MB -> 90.700 MB.
[2025-11-05T22:32:57.567Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:32:59.368Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:33:01.173Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:33:02.996Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:33:03.793Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:33:04.580Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:33:05.847Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:33:07.094Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:33:07.095Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:33:07.095Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:33:07.095Z] Top recommended movies for user id 72:
[2025-11-05T22:33:07.095Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:33:07.095Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:33:07.095Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:33:07.095Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:33:07.095Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:33:07.095Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11282.342 ms) ======
[2025-11-05T22:33:07.095Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-05T22:33:07.095Z] GC before operation: completed in 58.327 ms, heap usage 191.886 MB -> 90.529 MB.
[2025-11-05T22:33:08.900Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-05T22:33:10.696Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-05T22:33:12.508Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-05T22:33:13.748Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-05T22:33:14.991Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-05T22:33:15.779Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-05T22:33:17.017Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-05T22:33:17.810Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-05T22:33:18.172Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-05T22:33:18.172Z] The best model improves the baseline by 14.52%.
[2025-11-05T22:33:18.172Z] Top recommended movies for user id 72:
[2025-11-05T22:33:18.172Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-05T22:33:18.172Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-05T22:33:18.172Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-05T22:33:18.172Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-05T22:33:18.172Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-05T22:33:18.172Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11040.507 ms) ======
[2025-11-05T22:33:18.923Z] -----------------------------------
[2025-11-05T22:33:18.923Z] renaissance-movie-lens_0_PASSED
[2025-11-05T22:33:18.923Z] -----------------------------------
[2025-11-05T22:33:18.923Z]
[2025-11-05T22:33:18.923Z] TEST TEARDOWN:
[2025-11-05T22:33:18.923Z] Nothing to be done for teardown.
[2025-11-05T22:33:18.923Z] renaissance-movie-lens_0 Finish Time: Wed Nov 5 17:33:18 2025 Epoch Time (ms): 1762381998510