renaissance-movie-lens_0
[2025-12-27T13:35:35.972Z] Running test renaissance-movie-lens_0 ...
[2025-12-27T13:35:35.972Z] ===============================================
[2025-12-27T13:35:35.972Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 13:35:35 2025 Epoch Time (ms): 1766842535816
[2025-12-27T13:35:35.972Z] variation: NoOptions
[2025-12-27T13:35:35.972Z] JVM_OPTIONS:
[2025-12-27T13:35:35.972Z] { \
[2025-12-27T13:35:35.972Z] echo ""; echo "TEST SETUP:"; \
[2025-12-27T13:35:35.972Z] echo "Nothing to be done for setup."; \
[2025-12-27T13:35:35.972Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_1766841184519/renaissance-movie-lens_0"; \
[2025-12-27T13:35:35.972Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_1766841184519/renaissance-movie-lens_0"; \
[2025-12-27T13:35:35.972Z] echo ""; echo "TESTING:"; \
[2025-12-27T13:35:35.972Z] "/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_1766841184519/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-27T13:35:35.972Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_1766841184519/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-27T13:35:35.972Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-27T13:35:35.972Z] echo "Nothing to be done for teardown."; \
[2025-12-27T13:35:35.972Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_1766841184519/TestTargetResult";
[2025-12-27T13:35:35.972Z]
[2025-12-27T13:35:35.972Z] TEST SETUP:
[2025-12-27T13:35:35.972Z] Nothing to be done for setup.
[2025-12-27T13:35:35.972Z]
[2025-12-27T13:35:35.972Z] TESTING:
[2025-12-27T13:35:36.939Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-27T13:35:36.939Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/output_1766841184519/renaissance-movie-lens_0/launcher-133535-13165319268721680789/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-27T13:35:36.939Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-27T13:35:36.939Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-27T13:35:43.717Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-27T13:35:53.579Z] 13:35:52.537 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.
[2025-12-27T13:35:55.567Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-27T13:35:55.567Z] Training: 60056, validation: 20285, test: 19854
[2025-12-27T13:35:55.567Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-27T13:35:55.567Z] GC before operation: completed in 115.319 ms, heap usage 220.341 MB -> 75.682 MB.
[2025-12-27T13:36:04.035Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:36:08.239Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:36:12.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:36:15.301Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:36:18.367Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:36:20.350Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:36:22.331Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:36:24.312Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:36:24.312Z] 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.
[2025-12-27T13:36:24.312Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:36:24.312Z] Top recommended movies for user id 72:
[2025-12-27T13:36:24.312Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:36:24.312Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:36:24.312Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:36:24.312Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:36:24.312Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:36:24.312Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28791.671 ms) ======
[2025-12-27T13:36:24.312Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-27T13:36:24.312Z] GC before operation: completed in 153.035 ms, heap usage 172.038 MB -> 98.638 MB.
[2025-12-27T13:36:28.529Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:36:31.598Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:36:34.657Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:36:37.720Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:36:38.685Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:36:40.671Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:36:42.652Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:36:44.645Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:36:44.645Z] 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.
[2025-12-27T13:36:44.645Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:36:44.645Z] Top recommended movies for user id 72:
[2025-12-27T13:36:44.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:36:44.645Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:36:44.645Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:36:44.645Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:36:44.645Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:36:44.645Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19803.996 ms) ======
[2025-12-27T13:36:44.645Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-27T13:36:44.645Z] GC before operation: completed in 147.477 ms, heap usage 253.921 MB -> 88.411 MB.
[2025-12-27T13:36:47.703Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:36:50.770Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:36:52.749Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:36:55.804Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:36:57.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:36:59.792Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:37:00.772Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:37:02.758Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:37:02.758Z] 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.
[2025-12-27T13:37:02.758Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:37:02.758Z] Top recommended movies for user id 72:
[2025-12-27T13:37:02.758Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:37:02.758Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:37:02.758Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:37:02.758Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:37:02.758Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:37:02.758Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18200.252 ms) ======
[2025-12-27T13:37:02.758Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-27T13:37:02.758Z] GC before operation: completed in 170.748 ms, heap usage 282.867 MB -> 89.283 MB.
[2025-12-27T13:37:06.178Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:37:08.517Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:37:11.576Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:37:13.564Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:37:15.548Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:37:16.519Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:37:18.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:37:20.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:37:20.486Z] 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.
[2025-12-27T13:37:20.486Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:37:20.486Z] Top recommended movies for user id 72:
[2025-12-27T13:37:20.486Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:37:20.486Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:37:20.486Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:37:20.486Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:37:20.486Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:37:20.486Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17503.689 ms) ======
[2025-12-27T13:37:20.486Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-27T13:37:20.486Z] GC before operation: completed in 141.429 ms, heap usage 472.717 MB -> 89.847 MB.
[2025-12-27T13:37:23.545Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:37:26.610Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:37:29.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:37:32.928Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:37:34.912Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:37:35.884Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:37:37.867Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:37:39.850Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:37:39.850Z] 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.
[2025-12-27T13:37:39.850Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:37:39.850Z] Top recommended movies for user id 72:
[2025-12-27T13:37:39.850Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:37:39.850Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:37:39.850Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:37:39.850Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:37:39.850Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:37:39.850Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19017.158 ms) ======
[2025-12-27T13:37:39.850Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-27T13:37:39.850Z] GC before operation: completed in 133.433 ms, heap usage 357.940 MB -> 89.621 MB.
[2025-12-27T13:37:42.906Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:37:45.974Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:37:47.960Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:37:51.018Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:37:52.612Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:37:53.762Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:37:55.748Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:37:56.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:37:57.689Z] 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.
[2025-12-27T13:37:57.689Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:37:57.689Z] Top recommended movies for user id 72:
[2025-12-27T13:37:57.689Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:37:57.689Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:37:57.689Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:37:57.689Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:37:57.689Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:37:57.689Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17486.923 ms) ======
[2025-12-27T13:37:57.689Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-27T13:37:57.689Z] GC before operation: completed in 127.440 ms, heap usage 255.537 MB -> 89.854 MB.
[2025-12-27T13:37:59.670Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:38:02.735Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:38:05.794Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:38:09.046Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:38:10.016Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:38:12.062Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:38:13.029Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:38:15.010Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:38:15.010Z] 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.
[2025-12-27T13:38:15.010Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:38:15.971Z] Top recommended movies for user id 72:
[2025-12-27T13:38:15.971Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:38:15.971Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:38:15.971Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:38:15.971Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:38:15.971Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:38:15.971Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17994.242 ms) ======
[2025-12-27T13:38:15.971Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-27T13:38:15.971Z] GC before operation: completed in 146.441 ms, heap usage 366.268 MB -> 89.962 MB.
[2025-12-27T13:38:17.953Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:38:19.935Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:38:23.000Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:38:24.994Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:38:27.039Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:38:29.057Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:38:31.040Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:38:32.010Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:38:32.010Z] 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.
[2025-12-27T13:38:32.010Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:38:32.010Z] Top recommended movies for user id 72:
[2025-12-27T13:38:32.010Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:38:32.010Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:38:32.010Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:38:32.010Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:38:32.010Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:38:32.010Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16807.802 ms) ======
[2025-12-27T13:38:32.010Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-27T13:38:32.971Z] GC before operation: completed in 132.747 ms, heap usage 359.516 MB -> 90.089 MB.
[2025-12-27T13:38:35.134Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:38:38.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:38:41.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:38:43.398Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:38:45.377Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:38:46.346Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:38:48.341Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:38:50.166Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:38:50.166Z] 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.
[2025-12-27T13:38:50.166Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:38:50.166Z] Top recommended movies for user id 72:
[2025-12-27T13:38:50.166Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:38:50.166Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:38:50.166Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:38:50.166Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:38:50.166Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:38:50.166Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17953.495 ms) ======
[2025-12-27T13:38:50.166Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-27T13:38:51.134Z] GC before operation: completed in 134.004 ms, heap usage 173.776 MB -> 89.774 MB.
[2025-12-27T13:38:53.220Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:38:56.274Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:38:59.342Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:39:01.372Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:39:03.466Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:39:04.441Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:39:06.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:39:08.489Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:39:08.489Z] 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.
[2025-12-27T13:39:08.489Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:39:08.489Z] Top recommended movies for user id 72:
[2025-12-27T13:39:08.489Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:39:08.489Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:39:08.489Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:39:08.489Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:39:08.489Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:39:08.489Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17739.486 ms) ======
[2025-12-27T13:39:08.489Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-27T13:39:08.489Z] GC before operation: completed in 127.964 ms, heap usage 253.716 MB -> 90.085 MB.
[2025-12-27T13:39:11.539Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:39:13.536Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:39:16.863Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:39:19.923Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:39:20.905Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:39:23.076Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:39:25.267Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:39:26.236Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:39:26.236Z] 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.
[2025-12-27T13:39:26.236Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:39:26.236Z] Top recommended movies for user id 72:
[2025-12-27T13:39:26.236Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:39:26.236Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:39:26.236Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:39:26.236Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:39:26.236Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:39:26.236Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18092.541 ms) ======
[2025-12-27T13:39:26.236Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-27T13:39:27.208Z] GC before operation: completed in 202.872 ms, heap usage 361.428 MB -> 89.907 MB.
[2025-12-27T13:39:29.197Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:39:32.539Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:39:34.563Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:39:38.482Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:39:39.497Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:39:40.632Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:39:42.921Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:39:44.910Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:39:44.910Z] 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.
[2025-12-27T13:39:44.910Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:39:44.910Z] Top recommended movies for user id 72:
[2025-12-27T13:39:44.911Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:39:44.911Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:39:44.911Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:39:44.911Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:39:44.911Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:39:44.911Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18038.822 ms) ======
[2025-12-27T13:39:44.911Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-27T13:39:44.911Z] GC before operation: completed in 127.725 ms, heap usage 293.178 MB -> 90.070 MB.
[2025-12-27T13:39:48.025Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:39:50.081Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:39:53.380Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:39:55.583Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:39:57.585Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:39:59.584Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:40:00.663Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:40:02.709Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:40:02.709Z] 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.
[2025-12-27T13:40:02.709Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:40:02.709Z] Top recommended movies for user id 72:
[2025-12-27T13:40:02.709Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:40:02.709Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:40:02.709Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:40:02.709Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:40:02.709Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:40:02.709Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17964.993 ms) ======
[2025-12-27T13:40:02.709Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-27T13:40:02.709Z] GC before operation: completed in 179.590 ms, heap usage 245.710 MB -> 90.058 MB.
[2025-12-27T13:40:05.872Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:40:08.989Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:40:10.991Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:40:14.104Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:40:15.133Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:40:17.161Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:40:18.130Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:40:20.171Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:40:20.171Z] 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.
[2025-12-27T13:40:20.171Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:40:20.171Z] Top recommended movies for user id 72:
[2025-12-27T13:40:20.171Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:40:20.171Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:40:20.171Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:40:20.171Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:40:20.171Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:40:20.171Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17034.139 ms) ======
[2025-12-27T13:40:20.171Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-27T13:40:20.171Z] GC before operation: completed in 186.088 ms, heap usage 503.144 MB -> 90.362 MB.
[2025-12-27T13:40:23.354Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:40:25.523Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:40:27.627Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:40:30.741Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:40:32.431Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:40:33.401Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:40:34.375Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:40:36.397Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:40:36.397Z] 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.
[2025-12-27T13:40:36.397Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:40:36.397Z] Top recommended movies for user id 72:
[2025-12-27T13:40:36.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:40:36.397Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:40:36.397Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:40:36.397Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:40:36.397Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:40:36.397Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15953.872 ms) ======
[2025-12-27T13:40:36.397Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-27T13:40:36.397Z] GC before operation: completed in 285.528 ms, heap usage 209.777 MB -> 90.106 MB.
[2025-12-27T13:40:39.595Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:40:41.586Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:40:43.582Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:40:46.669Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:40:47.639Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:40:49.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:40:50.748Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:40:52.739Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:40:52.739Z] 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.
[2025-12-27T13:40:52.739Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:40:52.739Z] Top recommended movies for user id 72:
[2025-12-27T13:40:52.739Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:40:52.739Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:40:52.739Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:40:52.739Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:40:52.739Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:40:52.739Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16272.077 ms) ======
[2025-12-27T13:40:52.739Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-27T13:40:52.739Z] GC before operation: completed in 157.769 ms, heap usage 425.946 MB -> 90.268 MB.
[2025-12-27T13:40:55.819Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:40:57.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:40:59.852Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:41:02.942Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:41:04.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:41:06.006Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:41:07.999Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:41:08.972Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:41:08.972Z] 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.
[2025-12-27T13:41:08.972Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:41:08.972Z] Top recommended movies for user id 72:
[2025-12-27T13:41:08.972Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:41:08.972Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:41:08.972Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:41:08.972Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:41:08.972Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:41:08.972Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16330.785 ms) ======
[2025-12-27T13:41:08.972Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-27T13:41:09.937Z] GC before operation: completed in 139.036 ms, heap usage 382.118 MB -> 90.284 MB.
[2025-12-27T13:41:11.928Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:41:15.013Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:41:17.244Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:41:19.228Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:41:21.220Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:41:22.187Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:41:24.223Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:41:25.191Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:41:26.162Z] 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.
[2025-12-27T13:41:26.162Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:41:26.162Z] Top recommended movies for user id 72:
[2025-12-27T13:41:26.162Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:41:26.162Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:41:26.162Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:41:26.162Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:41:26.162Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:41:26.162Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16448.936 ms) ======
[2025-12-27T13:41:26.162Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-27T13:41:26.162Z] GC before operation: completed in 144.197 ms, heap usage 104.750 MB -> 90.059 MB.
[2025-12-27T13:41:28.147Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:41:31.202Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:41:33.186Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:41:35.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:41:37.159Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:41:38.125Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:41:39.094Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:41:41.077Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:41:41.077Z] 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.
[2025-12-27T13:41:41.077Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:41:41.077Z] Top recommended movies for user id 72:
[2025-12-27T13:41:41.077Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:41:41.077Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:41:41.077Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:41:41.077Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:41:41.077Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:41:41.077Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15024.669 ms) ======
[2025-12-27T13:41:41.077Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-27T13:41:41.077Z] GC before operation: completed in 134.739 ms, heap usage 173.727 MB -> 89.936 MB.
[2025-12-27T13:41:44.145Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T13:41:46.124Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T13:41:48.108Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T13:41:51.170Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T13:41:52.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T13:41:54.122Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T13:41:55.084Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T13:41:57.064Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T13:41:57.064Z] 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.
[2025-12-27T13:41:57.064Z] The best model improves the baseline by 14.52%.
[2025-12-27T13:41:57.064Z] Top recommended movies for user id 72:
[2025-12-27T13:41:57.064Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T13:41:57.064Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T13:41:57.064Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T13:41:57.064Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T13:41:57.064Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T13:41:57.064Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15918.504 ms) ======
[2025-12-27T13:41:58.027Z] -----------------------------------
[2025-12-27T13:41:58.027Z] renaissance-movie-lens_0_PASSED
[2025-12-27T13:41:58.027Z] -----------------------------------
[2025-12-27T13:41:58.027Z]
[2025-12-27T13:41:58.027Z] TEST TEARDOWN:
[2025-12-27T13:41:58.027Z] Nothing to be done for teardown.
[2025-12-27T13:41:58.027Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 13:41:57 2025 Epoch Time (ms): 1766842917663