renaissance-movie-lens_0
[2025-11-29T14:48:00.004Z] Running test renaissance-movie-lens_0 ...
[2025-11-29T14:48:00.004Z] ===============================================
[2025-11-29T14:48:00.004Z] renaissance-movie-lens_0 Start Time: Sat Nov 29 14:47:59 2025 Epoch Time (ms): 1764427679158
[2025-11-29T14:48:00.004Z] variation: NoOptions
[2025-11-29T14:48:00.004Z] JVM_OPTIONS:
[2025-11-29T14:48:00.004Z] { \
[2025-11-29T14:48:00.004Z] echo ""; echo "TEST SETUP:"; \
[2025-11-29T14:48:00.004Z] echo "Nothing to be done for setup."; \
[2025-11-29T14:48:00.004Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17644265017028/renaissance-movie-lens_0"; \
[2025-11-29T14:48:00.004Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17644265017028/renaissance-movie-lens_0"; \
[2025-11-29T14:48:00.004Z] echo ""; echo "TESTING:"; \
[2025-11-29T14:48:00.004Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/jdkbinary/j2sdk-image/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 "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17644265017028/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-29T14:48:00.004Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17644265017028/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-29T14:48:00.004Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-29T14:48:00.004Z] echo "Nothing to be done for teardown."; \
[2025-11-29T14:48:00.004Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17644265017028/TestTargetResult";
[2025-11-29T14:48:00.004Z]
[2025-11-29T14:48:00.004Z] TEST SETUP:
[2025-11-29T14:48:00.004Z] Nothing to be done for setup.
[2025-11-29T14:48:00.004Z]
[2025-11-29T14:48:00.004Z] TESTING:
[2025-11-29T14:48:00.004Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-11-29T14:48:00.004Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/output_17644265017028/renaissance-movie-lens_0/launcher-144759-3279203745878558223/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-11-29T14:48:00.004Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-11-29T14:48:00.004Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-11-29T14:48:05.428Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-29T14:48:12.158Z] 14:48:10.897 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-29T14:48:13.115Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-29T14:48:14.073Z] Training: 60056, validation: 20285, test: 19854
[2025-11-29T14:48:14.073Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-29T14:48:14.073Z] GC before operation: completed in 140.498 ms, heap usage 214.464 MB -> 75.683 MB.
[2025-11-29T14:48:19.479Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:48:22.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:48:25.728Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:48:28.766Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:48:29.728Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:48:31.699Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:48:33.672Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:48:35.636Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:48:35.636Z] 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.
[2025-11-29T14:48:35.636Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:48:36.593Z] Top recommended movies for user id 72:
[2025-11-29T14:48:36.593Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:48:36.593Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:48:36.593Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:48:36.593Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:48:36.594Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:48:36.594Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22254.358 ms) ======
[2025-11-29T14:48:36.594Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-29T14:48:36.594Z] GC before operation: completed in 152.981 ms, heap usage 299.789 MB -> 87.799 MB.
[2025-11-29T14:48:39.661Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:48:41.629Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:48:44.661Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:48:46.627Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:48:49.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:48:52.003Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:48:52.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:48:52.959Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:48:53.920Z] 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.
[2025-11-29T14:48:53.920Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:48:53.920Z] Top recommended movies for user id 72:
[2025-11-29T14:48:53.920Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:48:53.920Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:48:53.920Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:48:53.920Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:48:53.920Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:48:53.920Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17415.476 ms) ======
[2025-11-29T14:48:53.920Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-29T14:48:53.920Z] GC before operation: completed in 120.502 ms, heap usage 472.533 MB -> 88.976 MB.
[2025-11-29T14:48:56.955Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:48:58.929Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:49:01.964Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:49:03.933Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:49:05.898Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:49:06.916Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:49:08.889Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:49:09.848Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:49:10.807Z] 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.
[2025-11-29T14:49:10.807Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:49:10.807Z] Top recommended movies for user id 72:
[2025-11-29T14:49:10.807Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:49:10.807Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:49:10.807Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:49:10.807Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:49:10.807Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:49:10.807Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16641.469 ms) ======
[2025-11-29T14:49:10.807Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-29T14:49:10.807Z] GC before operation: completed in 151.374 ms, heap usage 428.199 MB -> 89.527 MB.
[2025-11-29T14:49:12.773Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:49:15.809Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:49:17.779Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:49:19.753Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:49:21.727Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:49:23.697Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:49:24.660Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:49:26.627Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:49:26.627Z] 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.
[2025-11-29T14:49:26.627Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:49:26.627Z] Top recommended movies for user id 72:
[2025-11-29T14:49:26.627Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:49:26.627Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:49:26.627Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:49:26.627Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:49:26.627Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:49:26.627Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16075.866 ms) ======
[2025-11-29T14:49:26.627Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-29T14:49:26.627Z] GC before operation: completed in 173.426 ms, heap usage 659.543 MB -> 93.294 MB.
[2025-11-29T14:49:29.675Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:49:31.669Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:49:34.706Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:49:36.679Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:49:38.648Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:49:39.608Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:49:41.584Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:49:42.544Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:49:42.544Z] 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.
[2025-11-29T14:49:42.544Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:49:43.506Z] Top recommended movies for user id 72:
[2025-11-29T14:49:43.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:49:43.506Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:49:43.506Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:49:43.506Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:49:43.506Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:49:43.506Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16181.136 ms) ======
[2025-11-29T14:49:43.506Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-29T14:49:43.506Z] GC before operation: completed in 119.826 ms, heap usage 278.920 MB -> 89.559 MB.
[2025-11-29T14:49:45.473Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:49:48.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:49:50.499Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:49:53.540Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:49:54.500Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:49:56.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:49:57.428Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:49:59.396Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:49:59.396Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-29T14:49:59.396Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:49:59.396Z] Top recommended movies for user id 72:
[2025-11-29T14:49:59.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:49:59.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:49:59.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:49:59.396Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:49:59.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:49:59.396Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16542.038 ms) ======
[2025-11-29T14:49:59.396Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-29T14:50:00.355Z] GC before operation: completed in 150.865 ms, heap usage 409.795 MB -> 90.077 MB.
[2025-11-29T14:50:04.699Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:50:05.660Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:50:06.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:50:09.764Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:50:10.723Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:50:11.683Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:50:13.660Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:50:14.621Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:50:14.621Z] 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.
[2025-11-29T14:50:14.621Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:50:15.595Z] Top recommended movies for user id 72:
[2025-11-29T14:50:15.595Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:50:15.595Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:50:15.595Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:50:15.595Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:50:15.595Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:50:15.595Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15194.942 ms) ======
[2025-11-29T14:50:15.595Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-29T14:50:15.595Z] GC before operation: completed in 169.228 ms, heap usage 447.306 MB -> 90.076 MB.
[2025-11-29T14:50:17.563Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:50:19.536Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:50:21.502Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:50:24.544Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:50:25.502Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:50:26.462Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:50:28.426Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:50:29.383Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:50:29.383Z] 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.
[2025-11-29T14:50:29.383Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:50:29.383Z] Top recommended movies for user id 72:
[2025-11-29T14:50:29.383Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:50:29.383Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:50:29.383Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:50:29.383Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:50:29.383Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:50:29.383Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14355.385 ms) ======
[2025-11-29T14:50:29.383Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-29T14:50:30.508Z] GC before operation: completed in 155.083 ms, heap usage 261.098 MB -> 90.150 MB.
[2025-11-29T14:50:32.476Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:50:34.442Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:50:36.410Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:50:38.483Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:50:39.473Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:50:40.432Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:50:42.398Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:50:43.356Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:50:43.356Z] 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.
[2025-11-29T14:50:43.356Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:50:43.356Z] Top recommended movies for user id 72:
[2025-11-29T14:50:43.356Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:50:43.356Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:50:43.356Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:50:43.356Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:50:43.356Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:50:43.356Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13739.880 ms) ======
[2025-11-29T14:50:43.356Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-29T14:50:43.356Z] GC before operation: completed in 120.994 ms, heap usage 203.063 MB -> 89.812 MB.
[2025-11-29T14:50:46.389Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:50:48.356Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:50:50.320Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:50:52.298Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:50:53.256Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:50:55.229Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:50:56.187Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:50:57.144Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:50:58.101Z] 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.
[2025-11-29T14:50:58.101Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:50:58.101Z] Top recommended movies for user id 72:
[2025-11-29T14:50:58.101Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:50:58.101Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:50:58.101Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:50:58.101Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:50:58.101Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:50:58.101Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14073.162 ms) ======
[2025-11-29T14:50:58.101Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-29T14:50:58.101Z] GC before operation: completed in 143.260 ms, heap usage 453.786 MB -> 90.410 MB.
[2025-11-29T14:51:00.067Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:51:02.031Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:51:04.001Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:51:09.130Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:51:09.130Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:51:09.130Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:51:11.104Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:51:12.062Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:51:12.062Z] 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.
[2025-11-29T14:51:12.062Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:51:13.029Z] Top recommended movies for user id 72:
[2025-11-29T14:51:13.029Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:51:13.029Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:51:13.029Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:51:13.029Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:51:13.029Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:51:13.029Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14626.126 ms) ======
[2025-11-29T14:51:13.029Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-29T14:51:13.029Z] GC before operation: completed in 158.123 ms, heap usage 313.891 MB -> 89.931 MB.
[2025-11-29T14:51:14.994Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:51:18.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:51:19.997Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:51:21.960Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:51:23.928Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:51:24.887Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:51:26.852Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:51:27.810Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:51:27.810Z] 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.
[2025-11-29T14:51:27.810Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:51:28.776Z] Top recommended movies for user id 72:
[2025-11-29T14:51:28.776Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:51:28.776Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:51:28.776Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:51:28.776Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:51:28.776Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:51:28.776Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15681.664 ms) ======
[2025-11-29T14:51:28.776Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-29T14:51:28.776Z] GC before operation: completed in 133.996 ms, heap usage 613.816 MB -> 93.656 MB.
[2025-11-29T14:51:30.751Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:51:32.723Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:51:35.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:51:37.727Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:51:39.692Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:51:40.649Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:51:42.612Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:51:43.570Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:51:43.570Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-29T14:51:43.570Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:51:44.527Z] Top recommended movies for user id 72:
[2025-11-29T14:51:44.527Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:51:44.527Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:51:44.527Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:51:44.527Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:51:44.527Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:51:44.527Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15573.654 ms) ======
[2025-11-29T14:51:44.527Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-29T14:51:44.527Z] GC before operation: completed in 147.135 ms, heap usage 182.380 MB -> 90.121 MB.
[2025-11-29T14:51:46.491Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:51:48.453Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:51:51.486Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:51:52.443Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:51:54.410Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:51:55.370Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:51:57.338Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:51:58.298Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:51:58.298Z] 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.
[2025-11-29T14:51:58.298Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:51:58.298Z] Top recommended movies for user id 72:
[2025-11-29T14:51:58.298Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:51:58.298Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:51:58.298Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:51:58.298Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:51:58.298Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:51:58.298Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14288.440 ms) ======
[2025-11-29T14:51:58.298Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-29T14:51:58.298Z] GC before operation: completed in 161.780 ms, heap usage 267.264 MB -> 90.108 MB.
[2025-11-29T14:52:01.334Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:52:03.305Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:52:05.290Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:52:07.256Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:52:08.214Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:52:10.178Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:52:11.136Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:52:13.104Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:52:13.104Z] 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.
[2025-11-29T14:52:13.104Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:52:13.104Z] Top recommended movies for user id 72:
[2025-11-29T14:52:13.104Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:52:13.104Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:52:13.104Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:52:13.104Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:52:13.104Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:52:13.104Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14547.534 ms) ======
[2025-11-29T14:52:13.104Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-29T14:52:13.104Z] GC before operation: completed in 169.767 ms, heap usage 553.556 MB -> 93.839 MB.
[2025-11-29T14:52:16.146Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:52:20.042Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:52:21.536Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:52:22.496Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:52:24.466Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:52:25.425Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:52:27.399Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:52:28.359Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:52:29.319Z] 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.
[2025-11-29T14:52:29.319Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:52:29.319Z] Top recommended movies for user id 72:
[2025-11-29T14:52:29.319Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:52:29.319Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:52:29.319Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:52:29.319Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:52:29.319Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:52:29.319Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15799.299 ms) ======
[2025-11-29T14:52:29.319Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-29T14:52:29.319Z] GC before operation: completed in 128.799 ms, heap usage 157.206 MB -> 89.915 MB.
[2025-11-29T14:52:31.297Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:52:33.266Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:52:36.303Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:52:38.279Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:52:40.247Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:52:41.205Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:52:43.173Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:52:44.133Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:52:45.092Z] 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.
[2025-11-29T14:52:45.092Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:52:45.092Z] Top recommended movies for user id 72:
[2025-11-29T14:52:45.092Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:52:45.092Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:52:45.092Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:52:45.092Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:52:45.092Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:52:45.092Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15511.338 ms) ======
[2025-11-29T14:52:45.092Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-29T14:52:45.092Z] GC before operation: completed in 183.022 ms, heap usage 144.629 MB -> 90.078 MB.
[2025-11-29T14:52:47.061Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:52:49.031Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:52:52.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:52:54.049Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:52:55.006Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:52:56.979Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:52:57.946Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:52:59.926Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:52:59.926Z] 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.
[2025-11-29T14:52:59.926Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:52:59.926Z] Top recommended movies for user id 72:
[2025-11-29T14:52:59.926Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:52:59.926Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:52:59.926Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:52:59.926Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:52:59.926Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:52:59.926Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14971.409 ms) ======
[2025-11-29T14:52:59.926Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-29T14:52:59.926Z] GC before operation: completed in 138.315 ms, heap usage 371.055 MB -> 90.274 MB.
[2025-11-29T14:53:02.969Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:53:04.939Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:53:07.071Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:53:09.043Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:53:11.014Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:53:11.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:53:13.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:53:14.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:53:14.901Z] 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.
[2025-11-29T14:53:14.901Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:53:15.862Z] Top recommended movies for user id 72:
[2025-11-29T14:53:15.862Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:53:15.862Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:53:15.862Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:53:15.862Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:53:15.862Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:53:15.862Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15267.571 ms) ======
[2025-11-29T14:53:15.862Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-29T14:53:15.862Z] GC before operation: completed in 152.830 ms, heap usage 118.174 MB -> 89.967 MB.
[2025-11-29T14:53:17.830Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-29T14:53:19.802Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-29T14:53:22.843Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-29T14:53:24.813Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-29T14:53:27.627Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-29T14:53:27.627Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-29T14:53:29.040Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-29T14:53:29.979Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-29T14:53:30.918Z] 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.
[2025-11-29T14:53:30.918Z] The best model improves the baseline by 14.52%.
[2025-11-29T14:53:30.918Z] Top recommended movies for user id 72:
[2025-11-29T14:53:30.918Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-29T14:53:30.918Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-29T14:53:30.918Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-29T14:53:30.918Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-29T14:53:30.918Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-29T14:53:30.918Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15315.244 ms) ======
[2025-11-29T14:53:31.858Z] -----------------------------------
[2025-11-29T14:53:31.858Z] renaissance-movie-lens_0_PASSED
[2025-11-29T14:53:31.858Z] -----------------------------------
[2025-11-29T14:53:31.858Z]
[2025-11-29T14:53:31.858Z] TEST TEARDOWN:
[2025-11-29T14:53:31.858Z] Nothing to be done for teardown.
[2025-11-29T14:53:31.858Z] renaissance-movie-lens_0 Finish Time: Sat Nov 29 14:53:30 2025 Epoch Time (ms): 1764428010902