renaissance-movie-lens_0
[2025-12-27T13:53:46.758Z] Running test renaissance-movie-lens_0 ...
[2025-12-27T13:53:46.758Z] ===============================================
[2025-12-27T13:53:46.758Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 13:53:46 2025 Epoch Time (ms): 1766843626199
[2025-12-27T13:53:46.758Z] variation: NoOptions
[2025-12-27T13:53:46.758Z] JVM_OPTIONS:
[2025-12-27T13:53:46.758Z] { \
[2025-12-27T13:53:46.758Z] echo ""; echo "TEST SETUP:"; \
[2025-12-27T13:53:46.758Z] echo "Nothing to be done for setup."; \
[2025-12-27T13:53:46.758Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668418055814/renaissance-movie-lens_0"; \
[2025-12-27T13:53:46.758Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668418055814/renaissance-movie-lens_0"; \
[2025-12-27T13:53:46.758Z] echo ""; echo "TESTING:"; \
[2025-12-27T13:53:46.758Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_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_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668418055814/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-27T13:53:46.758Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668418055814/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-27T13:53:46.758Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-27T13:53:46.758Z] echo "Nothing to be done for teardown."; \
[2025-12-27T13:53:46.758Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668418055814/TestTargetResult";
[2025-12-27T13:53:46.758Z]
[2025-12-27T13:53:46.758Z] TEST SETUP:
[2025-12-27T13:53:46.758Z] Nothing to be done for setup.
[2025-12-27T13:53:46.758Z]
[2025-12-27T13:53:46.758Z] TESTING:
[2025-12-27T13:53:46.758Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-27T13:53:46.758Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/output_17668418055814/renaissance-movie-lens_0/launcher-135346-16997752090660955889/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-27T13:53:46.758Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-27T13:53:46.758Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-27T13:53:52.318Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-27T13:53:59.143Z] 13:53:58.882 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-27T13:54:01.600Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-27T13:54:02.365Z] Training: 60056, validation: 20285, test: 19854
[2025-12-27T13:54:02.365Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-27T13:54:02.365Z] GC before operation: completed in 165.960 ms, heap usage 263.611 MB -> 75.674 MB.
[2025-12-27T13:54:11.105Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:54:14.527Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:54:18.964Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:54:23.436Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:54:25.024Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:54:27.571Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:54:30.028Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:54:31.729Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:54:31.729Z] 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.
[2025-12-27T13:54:31.729Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:54:32.497Z] Top recommended movies for user id 72:
[2025-12-27T13:54:32.497Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:54:32.497Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:54:32.497Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:54:32.497Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:54:32.497Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:54:32.497Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29960.529 ms) ======
[2025-12-27T13:54:32.497Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-27T13:54:32.497Z] GC before operation: completed in 153.782 ms, heap usage 136.706 MB -> 86.277 MB.
[2025-12-27T13:54:38.070Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:54:41.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:54:46.004Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:54:56.100Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:54:57.701Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:54:59.280Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:55:03.703Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:55:05.295Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:55:06.058Z] 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.
[2025-12-27T13:55:06.058Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:55:06.058Z] Top recommended movies for user id 72:
[2025-12-27T13:55:06.058Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:55:06.058Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:55:06.058Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:55:06.058Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:55:06.058Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:55:06.058Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (33594.590 ms) ======
[2025-12-27T13:55:06.058Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-27T13:55:06.058Z] GC before operation: completed in 141.464 ms, heap usage 129.653 MB -> 88.314 MB.
[2025-12-27T13:55:09.455Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:55:15.122Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:55:17.584Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:55:20.977Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:55:22.557Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:55:24.135Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:55:25.711Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:55:27.294Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:55:27.294Z] 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.
[2025-12-27T13:55:27.294Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:55:28.053Z] Top recommended movies for user id 72:
[2025-12-27T13:55:28.053Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:55:28.053Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:55:28.053Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:55:28.053Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:55:28.053Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:55:28.053Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21631.926 ms) ======
[2025-12-27T13:55:28.053Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-27T13:55:28.053Z] GC before operation: completed in 153.611 ms, heap usage 360.456 MB -> 89.404 MB.
[2025-12-27T13:55:31.478Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:55:33.951Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:55:37.403Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:55:42.986Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:55:43.749Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:55:45.329Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:55:50.992Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:55:51.764Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:55:52.535Z] 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.
[2025-12-27T13:55:52.535Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:55:52.535Z] Top recommended movies for user id 72:
[2025-12-27T13:55:52.535Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:55:52.535Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:55:52.535Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:55:52.535Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:55:52.535Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:55:52.535Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (24651.721 ms) ======
[2025-12-27T13:55:52.535Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-27T13:55:52.535Z] GC before operation: completed in 108.494 ms, heap usage 371.224 MB -> 89.662 MB.
[2025-12-27T13:55:56.523Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:55:58.977Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:56:01.458Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:56:03.946Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:56:05.527Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:56:07.121Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:56:08.710Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:56:10.295Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:56:11.061Z] 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.
[2025-12-27T13:56:11.061Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:56:11.061Z] Top recommended movies for user id 72:
[2025-12-27T13:56:11.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:56:11.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:56:11.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:56:11.061Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:56:11.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:56:11.061Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18121.171 ms) ======
[2025-12-27T13:56:11.061Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-27T13:56:11.061Z] GC before operation: completed in 129.133 ms, heap usage 401.510 MB -> 89.579 MB.
[2025-12-27T13:56:13.516Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:56:16.911Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:56:19.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:56:21.817Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:56:23.393Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:56:24.969Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:56:26.543Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:56:28.997Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:56:28.997Z] 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.
[2025-12-27T13:56:28.997Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:56:28.997Z] Top recommended movies for user id 72:
[2025-12-27T13:56:28.997Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:56:28.997Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:56:28.997Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:56:28.997Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:56:28.997Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:56:28.997Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17864.967 ms) ======
[2025-12-27T13:56:28.997Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-27T13:56:28.997Z] GC before operation: completed in 143.744 ms, heap usage 482.630 MB -> 90.117 MB.
[2025-12-27T13:56:31.449Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:56:34.404Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:56:36.860Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:56:39.316Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:56:40.892Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:56:42.464Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:56:44.043Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:56:45.622Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:56:45.622Z] 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.
[2025-12-27T13:56:45.622Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:56:45.622Z] Top recommended movies for user id 72:
[2025-12-27T13:56:45.622Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:56:45.622Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:56:45.622Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:56:45.622Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:56:45.622Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:56:45.622Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16679.677 ms) ======
[2025-12-27T13:56:45.622Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-27T13:56:45.622Z] GC before operation: completed in 114.060 ms, heap usage 454.858 MB -> 90.049 MB.
[2025-12-27T13:56:48.070Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:56:50.526Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:56:53.067Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:56:55.543Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:56:57.113Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:56:58.694Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:56:59.456Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:57:01.151Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:57:01.151Z] 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.
[2025-12-27T13:57:01.151Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:57:01.914Z] Top recommended movies for user id 72:
[2025-12-27T13:57:01.914Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:57:01.914Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:57:01.914Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:57:01.914Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:57:01.914Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:57:01.914Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15835.433 ms) ======
[2025-12-27T13:57:01.914Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-27T13:57:01.914Z] GC before operation: completed in 111.812 ms, heap usage 294.993 MB -> 90.005 MB.
[2025-12-27T13:57:04.369Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:57:05.946Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:57:08.888Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:57:10.462Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:57:12.042Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:57:13.623Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:57:14.388Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:57:15.966Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:57:15.966Z] 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.
[2025-12-27T13:57:15.966Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:57:16.727Z] Top recommended movies for user id 72:
[2025-12-27T13:57:16.727Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:57:16.727Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:57:16.727Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:57:16.727Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:57:16.727Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:57:16.727Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14759.862 ms) ======
[2025-12-27T13:57:16.727Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-27T13:57:16.727Z] GC before operation: completed in 126.754 ms, heap usage 226.905 MB -> 89.797 MB.
[2025-12-27T13:57:19.192Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:57:21.636Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:57:24.086Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:57:26.780Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:57:30.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:57:31.806Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:57:35.608Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:57:37.185Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:57:37.185Z] 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.
[2025-12-27T13:57:37.185Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:57:37.949Z] Top recommended movies for user id 72:
[2025-12-27T13:57:37.949Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:57:37.949Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:57:37.949Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:57:37.949Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:57:37.949Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:57:37.949Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21034.773 ms) ======
[2025-12-27T13:57:37.949Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-27T13:57:37.949Z] GC before operation: completed in 127.805 ms, heap usage 365.828 MB -> 90.316 MB.
[2025-12-27T13:57:40.388Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:57:42.832Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:57:46.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:57:49.510Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:57:51.081Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:57:52.655Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:57:54.229Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:57:55.825Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:57:56.582Z] 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.
[2025-12-27T13:57:56.582Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:57:56.582Z] Top recommended movies for user id 72:
[2025-12-27T13:57:56.582Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:57:56.582Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:57:56.582Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:57:56.582Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:57:56.582Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:57:56.582Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18578.531 ms) ======
[2025-12-27T13:57:56.582Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-27T13:57:56.582Z] GC before operation: completed in 112.237 ms, heap usage 101.963 MB -> 89.505 MB.
[2025-12-27T13:57:59.097Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:58:01.571Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:58:04.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:58:05.606Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:58:07.189Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:58:08.801Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:58:10.372Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:58:11.950Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:58:11.950Z] 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.
[2025-12-27T13:58:11.950Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:58:11.950Z] Top recommended movies for user id 72:
[2025-12-27T13:58:11.950Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:58:11.950Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:58:11.950Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:58:11.950Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:58:11.950Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:58:11.950Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15689.291 ms) ======
[2025-12-27T13:58:11.950Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-27T13:58:11.950Z] GC before operation: completed in 109.647 ms, heap usage 372.679 MB -> 90.114 MB.
[2025-12-27T13:58:14.400Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:58:17.784Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:58:20.237Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:58:21.810Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:58:23.895Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:58:24.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:58:27.113Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:58:27.876Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:58:28.636Z] 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.
[2025-12-27T13:58:28.637Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:58:28.637Z] Top recommended movies for user id 72:
[2025-12-27T13:58:28.637Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:58:28.637Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:58:28.637Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:58:28.637Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:58:28.637Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:58:28.637Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16078.600 ms) ======
[2025-12-27T13:58:28.637Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-27T13:58:28.637Z] GC before operation: completed in 119.930 ms, heap usage 353.264 MB -> 90.204 MB.
[2025-12-27T13:58:31.225Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:58:33.669Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:58:36.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:58:37.690Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:58:39.274Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:58:40.848Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:58:42.419Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:58:44.032Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:58:44.032Z] 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.
[2025-12-27T13:58:44.032Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:58:44.032Z] Top recommended movies for user id 72:
[2025-12-27T13:58:44.032Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:58:44.032Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:58:44.032Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:58:44.032Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:58:44.032Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:58:44.032Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15592.105 ms) ======
[2025-12-27T13:58:44.032Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-27T13:58:44.032Z] GC before operation: completed in 106.860 ms, heap usage 123.162 MB -> 89.798 MB.
[2025-12-27T13:58:46.487Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:58:48.936Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:58:51.385Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:58:53.832Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:58:57.224Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:58:57.988Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:58:59.562Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:59:01.505Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:59:01.505Z] 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.
[2025-12-27T13:59:01.505Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:59:02.263Z] Top recommended movies for user id 72:
[2025-12-27T13:59:02.263Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:59:02.263Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:59:02.263Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:59:02.263Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:59:02.263Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:59:02.263Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17693.954 ms) ======
[2025-12-27T13:59:02.263Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-27T13:59:02.263Z] GC before operation: completed in 108.274 ms, heap usage 99.104 MB -> 89.903 MB.
[2025-12-27T13:59:04.707Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:59:07.172Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:59:09.627Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:59:12.071Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:59:13.644Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:59:15.228Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:59:16.799Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:59:17.592Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:59:18.352Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T13:59:18.352Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:59:18.352Z] Top recommended movies for user id 72:
[2025-12-27T13:59:18.352Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:59:18.352Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:59:18.352Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:59:18.352Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:59:18.352Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:59:18.352Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16222.334 ms) ======
[2025-12-27T13:59:18.352Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-27T13:59:18.352Z] GC before operation: completed in 112.894 ms, heap usage 380.008 MB -> 90.209 MB.
[2025-12-27T13:59:20.813Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:59:23.263Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:59:25.707Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:59:29.236Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:59:30.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:59:31.578Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:59:33.156Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:59:34.739Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:59:34.739Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T13:59:34.739Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:59:34.739Z] Top recommended movies for user id 72:
[2025-12-27T13:59:34.739Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:59:34.739Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:59:34.739Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:59:34.739Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:59:34.739Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:59:34.739Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16436.376 ms) ======
[2025-12-27T13:59:34.739Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-27T13:59:34.739Z] GC before operation: completed in 128.479 ms, heap usage 768.427 MB -> 93.931 MB.
[2025-12-27T13:59:37.198Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:59:39.653Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:59:42.104Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:59:43.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:59:45.768Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:59:46.542Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:59:48.141Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:59:49.725Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:59:49.725Z] 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.
[2025-12-27T13:59:49.725Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:59:49.725Z] Top recommended movies for user id 72:
[2025-12-27T13:59:49.725Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:59:49.725Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:59:49.725Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:59:49.725Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:59:49.725Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:59:49.725Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15148.498 ms) ======
[2025-12-27T13:59:49.725Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-27T13:59:50.533Z] GC before operation: completed in 119.825 ms, heap usage 118.326 MB -> 89.718 MB.
[2025-12-27T13:59:52.999Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:59:54.578Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:59:57.034Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:59:59.478Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:00:01.128Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:00:02.876Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:00:05.349Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:00:06.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:00:06.879Z] 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.
[2025-12-27T14:00:06.879Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:00:06.879Z] Top recommended movies for user id 72:
[2025-12-27T14:00:06.879Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:00:06.879Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:00:06.879Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:00:06.879Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:00:06.879Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:00:06.879Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16889.503 ms) ======
[2025-12-27T14:00:06.879Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-27T14:00:06.879Z] GC before operation: completed in 117.284 ms, heap usage 109.888 MB -> 89.827 MB.
[2025-12-27T14:00:09.325Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T14:00:11.777Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T14:00:14.230Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T14:00:16.695Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T14:00:18.288Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T14:00:19.882Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T14:00:21.179Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T14:00:22.792Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T14:00:22.792Z] 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.
[2025-12-27T14:00:22.792Z] The best model improves the baseline by 14.52%.
[2025-12-27T14:00:22.792Z] Top recommended movies for user id 72:
[2025-12-27T14:00:22.792Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T14:00:22.792Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T14:00:22.792Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T14:00:22.792Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T14:00:22.792Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T14:00:22.792Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15971.367 ms) ======
[2025-12-27T14:00:23.561Z] -----------------------------------
[2025-12-27T14:00:23.561Z] renaissance-movie-lens_0_PASSED
[2025-12-27T14:00:23.561Z] -----------------------------------
[2025-12-27T14:00:23.561Z]
[2025-12-27T14:00:23.561Z] TEST TEARDOWN:
[2025-12-27T14:00:23.561Z] Nothing to be done for teardown.
[2025-12-27T14:00:23.561Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 14:00:23 2025 Epoch Time (ms): 1766844023177