renaissance-movie-lens_0
[2025-09-05T16:15:10.461Z] Running test renaissance-movie-lens_0 ...
[2025-09-05T16:15:10.461Z] ===============================================
[2025-09-05T16:15:10.461Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 16:15:09 2025 Epoch Time (ms): 1757088909932
[2025-09-05T16:15:10.461Z] variation: NoOptions
[2025-09-05T16:15:10.461Z] JVM_OPTIONS:
[2025-09-05T16:15:10.461Z] { \
[2025-09-05T16:15:10.461Z] echo ""; echo "TEST SETUP:"; \
[2025-09-05T16:15:10.461Z] echo "Nothing to be done for setup."; \
[2025-09-05T16:15:10.462Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17570874265764/renaissance-movie-lens_0"; \
[2025-09-05T16:15:10.462Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17570874265764/renaissance-movie-lens_0"; \
[2025-09-05T16:15:10.462Z] echo ""; echo "TESTING:"; \
[2025-09-05T16:15:10.462Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/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_aarch64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17570874265764/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-05T16:15:10.462Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17570874265764/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-05T16:15:10.462Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-05T16:15:10.462Z] echo "Nothing to be done for teardown."; \
[2025-09-05T16:15:10.462Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17570874265764/TestTargetResult";
[2025-09-05T16:15:10.462Z]
[2025-09-05T16:15:10.462Z] TEST SETUP:
[2025-09-05T16:15:10.462Z] Nothing to be done for setup.
[2025-09-05T16:15:10.462Z]
[2025-09-05T16:15:10.462Z] TESTING:
[2025-09-05T16:15:11.394Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-09-05T16:15:11.394Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/output_17570874265764/renaissance-movie-lens_0/launcher-161510-5576076268868770410/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-09-05T16:15:11.394Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-09-05T16:15:11.394Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-09-05T16:15:19.930Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-05T16:15:31.327Z] 16:15:30.038 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-05T16:15:33.426Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-05T16:15:33.426Z] Training: 60056, validation: 20285, test: 19854
[2025-09-05T16:15:33.426Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-05T16:15:34.363Z] GC before operation: completed in 141.585 ms, heap usage 146.992 MB -> 75.912 MB.
[2025-09-05T16:15:42.526Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:15:48.202Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:15:52.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:15:57.612Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:15:59.537Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:16:02.502Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:16:04.426Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:16:07.696Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:16:07.696Z] 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.
[2025-09-05T16:16:07.696Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:16:08.632Z] Top recommended movies for user id 72:
[2025-09-05T16:16:08.632Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:16:08.632Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:16:08.632Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:16:08.632Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:16:08.632Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:16:08.632Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (34293.236 ms) ======
[2025-09-05T16:16:08.632Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-05T16:16:08.632Z] GC before operation: completed in 187.138 ms, heap usage 163.417 MB -> 86.313 MB.
[2025-09-05T16:16:12.710Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:16:16.827Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:16:19.820Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:16:23.919Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:16:25.855Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:16:27.775Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:16:30.739Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:16:32.671Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:16:32.671Z] 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.
[2025-09-05T16:16:32.671Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:16:33.610Z] Top recommended movies for user id 72:
[2025-09-05T16:16:33.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:16:33.610Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:16:33.610Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:16:33.610Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:16:33.610Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:16:33.610Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24961.152 ms) ======
[2025-09-05T16:16:33.610Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-05T16:16:33.610Z] GC before operation: completed in 198.073 ms, heap usage 239.008 MB -> 88.515 MB.
[2025-09-05T16:16:37.693Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:16:40.688Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:16:43.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:16:47.767Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:16:49.688Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:16:51.613Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:16:53.538Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:16:55.471Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:16:56.410Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:16:56.410Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:16:56.410Z] Top recommended movies for user id 72:
[2025-09-05T16:16:56.410Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:16:56.410Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:16:56.410Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:16:56.410Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:16:56.410Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:16:56.410Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22631.671 ms) ======
[2025-09-05T16:16:56.410Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-05T16:16:56.410Z] GC before operation: completed in 194.222 ms, heap usage 115.262 MB -> 91.250 MB.
[2025-09-05T16:16:59.693Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:17:02.675Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:17:04.617Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:17:07.584Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:17:09.498Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:17:11.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:17:13.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:17:14.289Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:17:14.289Z] 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.
[2025-09-05T16:17:14.289Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:17:15.220Z] Top recommended movies for user id 72:
[2025-09-05T16:17:15.220Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:17:15.220Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:17:15.220Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:17:15.220Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:17:15.220Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:17:15.220Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18478.306 ms) ======
[2025-09-05T16:17:15.220Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-05T16:17:15.220Z] GC before operation: completed in 168.597 ms, heap usage 208.064 MB -> 89.487 MB.
[2025-09-05T16:17:18.181Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:17:21.145Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:17:24.106Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:17:26.028Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:17:27.953Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:17:29.877Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:17:30.811Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:17:32.731Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:17:32.731Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:17:33.665Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:17:33.665Z] Top recommended movies for user id 72:
[2025-09-05T16:17:33.665Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:17:33.665Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:17:33.665Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:17:33.665Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:17:33.665Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:17:33.665Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18362.815 ms) ======
[2025-09-05T16:17:33.665Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-05T16:17:33.665Z] GC before operation: completed in 153.562 ms, heap usage 240.706 MB -> 89.472 MB.
[2025-09-05T16:17:36.621Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:17:39.600Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:17:42.565Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:17:45.164Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:17:47.085Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:17:49.008Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:17:50.927Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:17:51.861Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:17:52.797Z] 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.
[2025-09-05T16:17:52.797Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:17:52.797Z] Top recommended movies for user id 72:
[2025-09-05T16:17:52.797Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:17:52.797Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:17:52.797Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:17:52.797Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:17:52.797Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:17:52.797Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19158.446 ms) ======
[2025-09-05T16:17:52.797Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-05T16:17:52.797Z] GC before operation: completed in 176.729 ms, heap usage 450.677 MB -> 90.108 MB.
[2025-09-05T16:17:55.757Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:17:58.722Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:18:01.690Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:18:04.768Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:18:06.686Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:18:08.606Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:18:10.525Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:18:12.442Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:18:12.442Z] 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.
[2025-09-05T16:18:12.442Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:18:12.442Z] Top recommended movies for user id 72:
[2025-09-05T16:18:12.442Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:18:12.442Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:18:12.442Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:18:12.442Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:18:12.442Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:18:12.442Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19520.000 ms) ======
[2025-09-05T16:18:12.442Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-05T16:18:12.442Z] GC before operation: completed in 149.649 ms, heap usage 193.190 MB -> 89.700 MB.
[2025-09-05T16:18:15.398Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:18:18.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:18:22.462Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:18:25.442Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:18:27.361Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:18:29.956Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:18:30.888Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:18:32.807Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:18:32.807Z] 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.
[2025-09-05T16:18:32.807Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:18:32.807Z] Top recommended movies for user id 72:
[2025-09-05T16:18:32.807Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:18:32.807Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:18:32.807Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:18:32.807Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:18:32.807Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:18:32.807Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20364.862 ms) ======
[2025-09-05T16:18:32.807Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-05T16:18:32.807Z] GC before operation: completed in 168.483 ms, heap usage 374.914 MB -> 90.204 MB.
[2025-09-05T16:18:35.770Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:18:38.730Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:18:41.689Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:18:44.670Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:18:46.660Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:18:48.590Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:18:51.566Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:18:53.495Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:18:53.495Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:18:53.495Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:18:53.495Z] Top recommended movies for user id 72:
[2025-09-05T16:18:53.495Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:18:53.496Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:18:53.496Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:18:53.496Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:18:53.496Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:18:53.496Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20586.728 ms) ======
[2025-09-05T16:18:53.496Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-05T16:18:53.496Z] GC before operation: completed in 177.732 ms, heap usage 150.150 MB -> 89.748 MB.
[2025-09-05T16:18:57.587Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:19:00.556Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:19:03.518Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:19:06.623Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:19:07.553Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:19:09.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:19:11.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:19:12.318Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:19:12.318Z] 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.
[2025-09-05T16:19:12.318Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:19:13.247Z] Top recommended movies for user id 72:
[2025-09-05T16:19:13.248Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:19:13.248Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:19:13.248Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:19:13.248Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:19:13.248Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:19:13.248Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18993.240 ms) ======
[2025-09-05T16:19:13.248Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-05T16:19:13.248Z] GC before operation: completed in 166.194 ms, heap usage 95.068 MB -> 90.357 MB.
[2025-09-05T16:19:15.851Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:19:18.821Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:19:20.737Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:19:23.698Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:19:24.629Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:19:26.543Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:19:28.459Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:19:30.384Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:19:30.384Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:19:30.384Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:19:30.384Z] Top recommended movies for user id 72:
[2025-09-05T16:19:30.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:19:30.384Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:19:30.384Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:19:30.384Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:19:30.384Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:19:30.384Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17334.138 ms) ======
[2025-09-05T16:19:30.384Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-05T16:19:30.384Z] GC before operation: completed in 150.379 ms, heap usage 371.617 MB -> 89.984 MB.
[2025-09-05T16:19:33.360Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:19:37.454Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:19:41.559Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:19:45.655Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:19:48.630Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:19:51.609Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:19:54.596Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:19:56.524Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:19:57.470Z] 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.
[2025-09-05T16:19:57.470Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:19:57.470Z] Top recommended movies for user id 72:
[2025-09-05T16:19:57.470Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:19:57.470Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:19:57.470Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:19:57.470Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:19:57.470Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:19:57.470Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (26946.001 ms) ======
[2025-09-05T16:19:57.470Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-05T16:19:57.470Z] GC before operation: completed in 270.740 ms, heap usage 375.079 MB -> 90.244 MB.
[2025-09-05T16:20:01.626Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:20:06.420Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:20:11.736Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:20:15.831Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:20:18.812Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:20:20.748Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:20:23.729Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:20:26.702Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:20:26.702Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:20:26.702Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:20:27.640Z] Top recommended movies for user id 72:
[2025-09-05T16:20:27.640Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:20:27.640Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:20:27.640Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:20:27.640Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:20:27.640Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:20:27.640Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (29452.188 ms) ======
[2025-09-05T16:20:27.640Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-05T16:20:27.640Z] GC before operation: completed in 237.608 ms, heap usage 472.979 MB -> 90.441 MB.
[2025-09-05T16:20:31.743Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:20:36.001Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:20:40.113Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:20:44.211Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:20:46.148Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:20:49.124Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:20:51.045Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:20:54.009Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:20:54.009Z] 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.
[2025-09-05T16:20:54.009Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:20:54.009Z] Top recommended movies for user id 72:
[2025-09-05T16:20:54.009Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:20:54.009Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:20:54.009Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:20:54.009Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:20:54.009Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:20:54.009Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (26791.078 ms) ======
[2025-09-05T16:20:54.009Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-05T16:20:54.953Z] GC before operation: completed in 249.953 ms, heap usage 214.673 MB -> 89.869 MB.
[2025-09-05T16:20:58.632Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:21:02.740Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:21:06.983Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:21:11.088Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:21:13.011Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:21:14.941Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:21:17.922Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:21:19.850Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:21:20.788Z] 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.
[2025-09-05T16:21:20.788Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:21:20.788Z] Top recommended movies for user id 72:
[2025-09-05T16:21:20.788Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:21:20.788Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:21:20.788Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:21:20.788Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:21:20.788Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:21:20.788Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (26327.223 ms) ======
[2025-09-05T16:21:20.788Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-05T16:21:20.788Z] GC before operation: completed in 211.037 ms, heap usage 119.038 MB -> 90.010 MB.
[2025-09-05T16:21:24.893Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:21:28.999Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:21:34.319Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:21:38.426Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:21:40.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:21:43.884Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:21:46.898Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:21:49.941Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:21:49.941Z] 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.
[2025-09-05T16:21:49.941Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:21:49.941Z] Top recommended movies for user id 72:
[2025-09-05T16:21:49.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:21:49.941Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:21:49.941Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:21:49.941Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:21:49.941Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:21:49.941Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (29223.591 ms) ======
[2025-09-05T16:21:49.941Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-05T16:21:50.890Z] GC before operation: completed in 298.929 ms, heap usage 282.152 MB -> 90.063 MB.
[2025-09-05T16:21:55.030Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:21:59.243Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:22:04.642Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:22:09.954Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:22:12.962Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:22:16.645Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:22:18.574Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:22:21.558Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:22:22.499Z] 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.
[2025-09-05T16:22:22.499Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:22:22.499Z] Top recommended movies for user id 72:
[2025-09-05T16:22:22.499Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:22:22.499Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:22:22.499Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:22:22.499Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:22:22.499Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:22:22.499Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (32019.678 ms) ======
[2025-09-05T16:22:22.499Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-05T16:22:22.499Z] GC before operation: completed in 365.130 ms, heap usage 783.905 MB -> 94.063 MB.
[2025-09-05T16:22:29.151Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:22:34.456Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:22:39.774Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:22:45.102Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:22:47.080Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:22:50.081Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:22:54.204Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:22:57.194Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:22:58.153Z] 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.
[2025-09-05T16:22:58.153Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:22:58.153Z] Top recommended movies for user id 72:
[2025-09-05T16:22:58.153Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:22:58.153Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:22:58.153Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:22:58.153Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:22:58.153Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:22:58.153Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (35158.744 ms) ======
[2025-09-05T16:22:58.153Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-05T16:22:58.153Z] GC before operation: completed in 295.593 ms, heap usage 266.397 MB -> 89.967 MB.
[2025-09-05T16:23:03.537Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:23:07.826Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:23:12.659Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:23:16.812Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:23:20.969Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:23:22.893Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:23:25.921Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:23:28.929Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:23:29.870Z] 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.
[2025-09-05T16:23:29.870Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:23:29.870Z] Top recommended movies for user id 72:
[2025-09-05T16:23:29.870Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:23:29.870Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:23:29.870Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:23:29.870Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:23:29.870Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:23:29.870Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (31840.367 ms) ======
[2025-09-05T16:23:29.870Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-05T16:23:30.809Z] GC before operation: completed in 312.301 ms, heap usage 130.246 MB -> 90.858 MB.
[2025-09-05T16:23:36.117Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:23:41.472Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:23:45.743Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:23:51.048Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:23:53.263Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:23:55.721Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:23:58.721Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:24:01.742Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:24:01.742Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:24:01.742Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:24:01.742Z] Top recommended movies for user id 72:
[2025-09-05T16:24:01.742Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:24:01.742Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:24:01.742Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:24:01.742Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:24:01.742Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:24:01.742Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (31642.338 ms) ======
[2025-09-05T16:24:03.695Z] -----------------------------------
[2025-09-05T16:24:03.695Z] renaissance-movie-lens_0_PASSED
[2025-09-05T16:24:03.695Z] -----------------------------------
[2025-09-05T16:24:03.695Z]
[2025-09-05T16:24:03.695Z] TEST TEARDOWN:
[2025-09-05T16:24:03.695Z] Nothing to be done for teardown.
[2025-09-05T16:24:03.695Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 16:24:03 2025 Epoch Time (ms): 1757089443026