renaissance-movie-lens_0
[2025-06-11T23:29:48.973Z] Running test renaissance-movie-lens_0 ...
[2025-06-11T23:29:48.973Z] ===============================================
[2025-06-11T23:29:48.973Z] renaissance-movie-lens_0 Start Time: Wed Jun 11 19:29:48 2025 Epoch Time (ms): 1749684588663
[2025-06-11T23:29:48.973Z] variation: NoOptions
[2025-06-11T23:29:48.973Z] JVM_OPTIONS:
[2025-06-11T23:29:48.973Z] { \
[2025-06-11T23:29:48.973Z] echo ""; echo "TEST SETUP:"; \
[2025-06-11T23:29:48.973Z] echo "Nothing to be done for setup."; \
[2025-06-11T23:29:48.973Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496839143366/renaissance-movie-lens_0"; \
[2025-06-11T23:29:48.973Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496839143366/renaissance-movie-lens_0"; \
[2025-06-11T23:29:48.973Z] echo ""; echo "TESTING:"; \
[2025-06-11T23:29:48.973Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496839143366/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-06-11T23:29:48.973Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496839143366/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-06-11T23:29:48.973Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-06-11T23:29:48.973Z] echo "Nothing to be done for teardown."; \
[2025-06-11T23:29:48.973Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496839143366/TestTargetResult";
[2025-06-11T23:29:48.973Z]
[2025-06-11T23:29:48.973Z] TEST SETUP:
[2025-06-11T23:29:48.973Z] Nothing to be done for setup.
[2025-06-11T23:29:48.973Z]
[2025-06-11T23:29:48.973Z] TESTING:
[2025-06-11T23:29:53.011Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-06-11T23:29:57.012Z] 19:29:56.824 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB.
[2025-06-11T23:29:58.801Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-06-11T23:29:58.801Z] Training: 60056, validation: 20285, test: 19854
[2025-06-11T23:29:58.801Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-06-11T23:29:59.155Z] GC before operation: completed in 83.335 ms, heap usage 236.745 MB -> 74.486 MB.
[2025-06-11T23:30:03.211Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:30:05.684Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:30:08.124Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:30:10.573Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:30:11.850Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:30:13.108Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:30:14.358Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:30:15.633Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:30:15.995Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:30:15.995Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:30:15.995Z] Top recommended movies for user id 72:
[2025-06-11T23:30:15.995Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:30:15.995Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:30:15.995Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:30:15.995Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:30:15.995Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:30:15.995Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (17034.856 ms) ======
[2025-06-11T23:30:15.995Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-06-11T23:30:15.995Z] GC before operation: completed in 90.506 ms, heap usage 166.173 MB -> 85.161 MB.
[2025-06-11T23:30:18.432Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:30:20.287Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:30:22.079Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:30:23.848Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:30:25.105Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:30:26.355Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:30:27.609Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:30:28.373Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:30:28.733Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:30:28.733Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:30:28.733Z] Top recommended movies for user id 72:
[2025-06-11T23:30:28.733Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:30:28.733Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:30:28.733Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:30:28.733Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:30:28.733Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:30:28.733Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (12661.689 ms) ======
[2025-06-11T23:30:28.733Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-06-11T23:30:28.733Z] GC before operation: completed in 91.998 ms, heap usage 231.941 MB -> 87.099 MB.
[2025-06-11T23:30:31.199Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:30:32.973Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:30:34.751Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:30:36.546Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:30:37.306Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:30:38.064Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:30:39.320Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:30:40.572Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:30:40.572Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:30:40.988Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:30:40.988Z] Top recommended movies for user id 72:
[2025-06-11T23:30:40.988Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:30:40.988Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:30:40.988Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:30:40.988Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:30:40.988Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:30:40.988Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (11999.946 ms) ======
[2025-06-11T23:30:40.988Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-06-11T23:30:40.988Z] GC before operation: completed in 87.102 ms, heap usage 286.391 MB -> 87.856 MB.
[2025-06-11T23:30:43.384Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:30:45.199Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:30:47.625Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:30:48.874Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:30:50.100Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:30:51.332Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:30:52.588Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:30:53.858Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:30:53.858Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:30:53.858Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:30:53.858Z] Top recommended movies for user id 72:
[2025-06-11T23:30:53.858Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:30:53.858Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:30:53.858Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:30:53.858Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:30:53.858Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:30:53.858Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (12895.894 ms) ======
[2025-06-11T23:30:53.858Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-06-11T23:30:53.858Z] GC before operation: completed in 96.800 ms, heap usage 113.882 MB -> 88.121 MB.
[2025-06-11T23:30:55.637Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:30:57.424Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:30:59.265Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:31:01.039Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:31:02.327Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:31:03.620Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:31:04.963Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:31:05.843Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:31:05.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:31:06.215Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:31:06.215Z] Top recommended movies for user id 72:
[2025-06-11T23:31:06.215Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:31:06.215Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:31:06.215Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:31:06.215Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:31:06.215Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:31:06.215Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (12159.461 ms) ======
[2025-06-11T23:31:06.215Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-06-11T23:31:06.215Z] GC before operation: completed in 84.428 ms, heap usage 257.415 MB -> 88.089 MB.
[2025-06-11T23:31:08.023Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:31:09.815Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:31:11.653Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:31:13.448Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:31:14.701Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:31:15.925Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:31:17.180Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:31:18.455Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:31:18.455Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:31:18.455Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:31:18.455Z] Top recommended movies for user id 72:
[2025-06-11T23:31:18.455Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:31:18.455Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:31:18.455Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:31:18.455Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:31:18.455Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:31:18.455Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12317.824 ms) ======
[2025-06-11T23:31:18.455Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-06-11T23:31:18.455Z] GC before operation: completed in 87.735 ms, heap usage 213.298 MB -> 88.340 MB.
[2025-06-11T23:31:20.900Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:31:22.196Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:31:24.641Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:31:25.879Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:31:27.109Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:31:28.361Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:31:29.133Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:31:30.394Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:31:30.394Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:31:30.759Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:31:30.759Z] Top recommended movies for user id 72:
[2025-06-11T23:31:30.759Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:31:30.759Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:31:30.759Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:31:30.759Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:31:30.759Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:31:30.759Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12087.614 ms) ======
[2025-06-11T23:31:30.759Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-06-11T23:31:30.759Z] GC before operation: completed in 91.643 ms, heap usage 256.936 MB -> 88.314 MB.
[2025-06-11T23:31:32.545Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:31:34.366Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:31:36.154Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:31:38.557Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:31:39.323Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:31:40.117Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:31:41.355Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:31:42.155Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:31:42.537Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:31:42.537Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:31:42.537Z] Top recommended movies for user id 72:
[2025-06-11T23:31:42.537Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:31:42.537Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:31:42.538Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:31:42.538Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:31:42.538Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:31:42.538Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (11745.208 ms) ======
[2025-06-11T23:31:42.538Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-06-11T23:31:42.538Z] GC before operation: completed in 74.777 ms, heap usage 158.466 MB -> 88.442 MB.
[2025-06-11T23:31:44.319Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:31:46.105Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:31:47.871Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:31:49.655Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:31:50.894Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:31:52.151Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:31:53.421Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:31:54.195Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:31:54.560Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:31:54.560Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:31:54.560Z] Top recommended movies for user id 72:
[2025-06-11T23:31:54.560Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:31:54.560Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:31:54.560Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:31:54.560Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:31:54.560Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:31:54.560Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11976.577 ms) ======
[2025-06-11T23:31:54.560Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-06-11T23:31:54.560Z] GC before operation: completed in 88.439 ms, heap usage 107.795 MB -> 88.226 MB.
[2025-06-11T23:31:56.369Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:31:58.168Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:31:59.955Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:32:01.796Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:32:03.076Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:32:04.347Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:32:05.154Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:32:06.422Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:32:06.422Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:32:06.422Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:32:06.787Z] Top recommended movies for user id 72:
[2025-06-11T23:32:06.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:32:06.787Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:32:06.787Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:32:06.787Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:32:06.787Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:32:06.787Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11987.357 ms) ======
[2025-06-11T23:32:06.787Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-06-11T23:32:06.787Z] GC before operation: completed in 76.424 ms, heap usage 124.764 MB -> 88.443 MB.
[2025-06-11T23:32:08.587Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:32:10.390Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:32:12.185Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:32:13.969Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:32:15.217Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:32:15.993Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:32:17.343Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:32:18.617Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:32:18.617Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:32:18.617Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:32:18.617Z] Top recommended movies for user id 72:
[2025-06-11T23:32:18.617Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:32:18.617Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:32:18.617Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:32:18.617Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:32:18.617Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:32:18.617Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11910.837 ms) ======
[2025-06-11T23:32:18.617Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-06-11T23:32:18.617Z] GC before operation: completed in 84.323 ms, heap usage 158.491 MB -> 88.295 MB.
[2025-06-11T23:32:20.433Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:32:22.254Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:32:24.052Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:32:25.829Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:32:27.124Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:32:27.886Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:32:29.122Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:32:30.384Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:32:30.384Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:32:30.384Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:32:30.384Z] Top recommended movies for user id 72:
[2025-06-11T23:32:30.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:32:30.384Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:32:30.384Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:32:30.384Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:32:30.384Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:32:30.384Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11685.711 ms) ======
[2025-06-11T23:32:30.384Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-06-11T23:32:30.384Z] GC before operation: completed in 83.253 ms, heap usage 266.304 MB -> 88.549 MB.
[2025-06-11T23:32:32.804Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:32:34.053Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:32:35.863Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:32:37.663Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:32:38.942Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:32:39.713Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:32:41.039Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:32:42.299Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:32:42.299Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:32:42.299Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:32:42.299Z] Top recommended movies for user id 72:
[2025-06-11T23:32:42.299Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:32:42.299Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:32:42.299Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:32:42.299Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:32:42.299Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:32:42.299Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11824.091 ms) ======
[2025-06-11T23:32:42.299Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-06-11T23:32:42.299Z] GC before operation: completed in 89.545 ms, heap usage 158.453 MB -> 88.558 MB.
[2025-06-11T23:32:44.718Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:32:45.978Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:32:48.406Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:32:49.652Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:32:50.915Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:32:52.153Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:32:53.429Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:32:54.204Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:32:54.578Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:32:54.578Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:32:54.578Z] Top recommended movies for user id 72:
[2025-06-11T23:32:54.578Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:32:54.578Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:32:54.578Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:32:54.578Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:32:54.578Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:32:54.578Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12117.837 ms) ======
[2025-06-11T23:32:54.578Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-06-11T23:32:54.578Z] GC before operation: completed in 97.889 ms, heap usage 359.676 MB -> 88.658 MB.
[2025-06-11T23:32:56.405Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:32:58.204Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:32:59.993Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:33:01.787Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:33:03.107Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:33:03.910Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:33:05.283Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:33:06.067Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:33:06.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:33:06.438Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:33:06.438Z] Top recommended movies for user id 72:
[2025-06-11T23:33:06.438Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:33:06.438Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:33:06.438Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:33:06.438Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:33:06.438Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:33:06.438Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11720.582 ms) ======
[2025-06-11T23:33:06.438Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-06-11T23:33:06.438Z] GC before operation: completed in 77.057 ms, heap usage 109.846 MB -> 88.550 MB.
[2025-06-11T23:33:08.217Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:33:10.019Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:33:11.804Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:33:13.605Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:33:14.854Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:33:16.090Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:33:17.379Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:33:18.634Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:33:18.634Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:33:18.634Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:33:18.994Z] Top recommended movies for user id 72:
[2025-06-11T23:33:18.994Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:33:18.994Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:33:18.994Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:33:18.994Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:33:18.994Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:33:18.994Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12414.085 ms) ======
[2025-06-11T23:33:18.994Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-06-11T23:33:18.994Z] GC before operation: completed in 85.701 ms, heap usage 116.866 MB -> 88.324 MB.
[2025-06-11T23:33:20.810Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:33:22.602Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:33:24.435Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:33:26.226Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:33:27.515Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:33:28.336Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:33:29.581Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:33:30.813Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:33:30.813Z] 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.
[2025-06-11T23:33:30.813Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:33:31.169Z] Top recommended movies for user id 72:
[2025-06-11T23:33:31.169Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:33:31.169Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:33:31.169Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:33:31.169Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:33:31.169Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:33:31.169Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12117.380 ms) ======
[2025-06-11T23:33:31.169Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-06-11T23:33:31.169Z] GC before operation: completed in 80.333 ms, heap usage 393.559 MB -> 88.777 MB.
[2025-06-11T23:33:32.947Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:33:34.764Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:33:36.575Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:33:38.367Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:33:39.603Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:33:40.840Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:33:42.103Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:33:42.873Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:33:45.259Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:33:45.259Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:33:45.259Z] Top recommended movies for user id 72:
[2025-06-11T23:33:45.259Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:33:45.259Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:33:45.259Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:33:45.259Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:33:45.259Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:33:45.259Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12130.445 ms) ======
[2025-06-11T23:33:45.259Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-06-11T23:33:45.259Z] GC before operation: completed in 81.851 ms, heap usage 168.321 MB -> 88.380 MB.
[2025-06-11T23:33:45.259Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:33:47.064Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:33:49.489Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:33:51.270Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:33:52.499Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:33:53.261Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:33:54.568Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:33:55.339Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:33:55.702Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:33:55.702Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:33:55.702Z] Top recommended movies for user id 72:
[2025-06-11T23:33:55.702Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:33:55.702Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:33:55.702Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:33:55.702Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:33:55.702Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:33:55.702Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12370.003 ms) ======
[2025-06-11T23:33:55.702Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-06-11T23:33:55.702Z] GC before operation: completed in 72.285 ms, heap usage 221.482 MB -> 88.536 MB.
[2025-06-11T23:33:57.480Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:33:59.270Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:34:01.080Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:34:02.914Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:34:03.704Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:34:05.008Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:34:05.774Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:34:07.014Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:34:07.370Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T23:34:07.370Z] The best model improves the baseline by 14.52%.
[2025-06-11T23:34:07.370Z] Top recommended movies for user id 72:
[2025-06-11T23:34:07.370Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T23:34:07.370Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T23:34:07.370Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T23:34:07.370Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T23:34:07.370Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T23:34:07.370Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11496.178 ms) ======
[2025-06-11T23:34:07.731Z] -----------------------------------
[2025-06-11T23:34:07.731Z] renaissance-movie-lens_0_PASSED
[2025-06-11T23:34:07.731Z] -----------------------------------
[2025-06-11T23:34:07.731Z]
[2025-06-11T23:34:07.731Z] TEST TEARDOWN:
[2025-06-11T23:34:07.731Z] Nothing to be done for teardown.
[2025-06-11T23:34:07.731Z] renaissance-movie-lens_0 Finish Time: Wed Jun 11 19:34:07 2025 Epoch Time (ms): 1749684847340