renaissance-movie-lens_0
[2025-12-16T09:11:48.422Z] Running test renaissance-movie-lens_0 ...
[2025-12-16T09:11:48.422Z] ===============================================
[2025-12-16T09:11:48.422Z] renaissance-movie-lens_0 Start Time: Tue Dec 16 09:11:47 2025 Epoch Time (ms): 1765876307909
[2025-12-16T09:11:48.422Z] variation: NoOptions
[2025-12-16T09:11:48.422Z] JVM_OPTIONS:
[2025-12-16T09:11:48.422Z] { \
[2025-12-16T09:11:48.422Z] echo ""; echo "TEST SETUP:"; \
[2025-12-16T09:11:48.422Z] echo "Nothing to be done for setup."; \
[2025-12-16T09:11:48.422Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17658747417873/renaissance-movie-lens_0"; \
[2025-12-16T09:11:48.422Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17658747417873/renaissance-movie-lens_0"; \
[2025-12-16T09:11:48.422Z] echo ""; echo "TESTING:"; \
[2025-12-16T09:11:48.422Z] "/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_17658747417873/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-16T09:11:48.422Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17658747417873/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-16T09:11:48.422Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-16T09:11:48.422Z] echo "Nothing to be done for teardown."; \
[2025-12-16T09:11:48.422Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17658747417873/TestTargetResult";
[2025-12-16T09:11:48.422Z]
[2025-12-16T09:11:48.422Z] TEST SETUP:
[2025-12-16T09:11:48.422Z] Nothing to be done for setup.
[2025-12-16T09:11:48.422Z]
[2025-12-16T09:11:48.422Z] TESTING:
[2025-12-16T09:11:49.169Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-16T09:11:49.169Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/output_17658747417873/renaissance-movie-lens_0/launcher-091148-18074702954028098591/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-16T09:11:49.169Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-16T09:11:49.169Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-16T09:11:54.033Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-16T09:12:03.763Z] 09:12:03.560 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-16T09:12:07.149Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-16T09:12:07.149Z] Training: 60056, validation: 20285, test: 19854
[2025-12-16T09:12:07.149Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-16T09:12:11.080Z] GC before operation: completed in 186.150 ms, heap usage 284.050 MB -> 75.847 MB.
[2025-12-16T09:12:19.337Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:12:33.833Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:12:40.590Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:12:49.442Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:12:52.838Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:12:55.781Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:12:59.184Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:13:07.383Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:13:07.383Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-16T09:13:07.383Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:13:07.383Z] Top recommended movies for user id 72:
[2025-12-16T09:13:07.383Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:13:07.383Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:13:07.383Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:13:07.383Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:13:07.383Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:13:07.383Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (59787.210 ms) ======
[2025-12-16T09:13:07.383Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-16T09:13:07.383Z] GC before operation: completed in 184.701 ms, heap usage 496.700 MB -> 86.774 MB.
[2025-12-16T09:13:12.361Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:13:18.132Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:13:21.716Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:13:26.895Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:13:26.895Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:13:29.172Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:13:29.967Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:13:31.547Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:13:32.328Z] 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.
[2025-12-16T09:13:32.328Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:13:32.328Z] Top recommended movies for user id 72:
[2025-12-16T09:13:32.328Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:13:32.328Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:13:32.328Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:13:32.328Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:13:32.328Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:13:32.328Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24603.878 ms) ======
[2025-12-16T09:13:32.328Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-16T09:13:32.328Z] GC before operation: completed in 211.527 ms, heap usage 505.180 MB -> 88.934 MB.
[2025-12-16T09:13:36.842Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:13:39.342Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:13:42.710Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:13:46.089Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:13:48.255Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:13:49.820Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:13:52.249Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:13:53.920Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:13:54.672Z] 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.
[2025-12-16T09:13:54.672Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:13:54.672Z] Top recommended movies for user id 72:
[2025-12-16T09:13:54.672Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:13:54.672Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:13:54.672Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:13:54.672Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:13:54.672Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:13:54.672Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22247.850 ms) ======
[2025-12-16T09:13:54.672Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-16T09:13:54.672Z] GC before operation: completed in 179.998 ms, heap usage 217.354 MB -> 89.158 MB.
[2025-12-16T09:13:58.040Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:14:02.461Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:14:07.071Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:14:09.541Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:14:12.075Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:14:14.526Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:14:16.991Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:14:19.433Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:14:19.433Z] 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.
[2025-12-16T09:14:19.433Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:14:19.433Z] Top recommended movies for user id 72:
[2025-12-16T09:14:19.433Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:14:19.433Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:14:19.433Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:14:19.433Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:14:19.433Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:14:19.433Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (24594.330 ms) ======
[2025-12-16T09:14:19.433Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-16T09:14:19.433Z] GC before operation: completed in 149.306 ms, heap usage 480.347 MB -> 89.915 MB.
[2025-12-16T09:14:22.894Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:14:26.251Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:14:30.200Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:14:33.553Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:14:35.974Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:14:38.390Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:14:39.947Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:14:42.370Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:14:42.370Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-16T09:14:42.370Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:14:43.127Z] Top recommended movies for user id 72:
[2025-12-16T09:14:43.127Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:14:43.127Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:14:43.127Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:14:43.127Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:14:43.127Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:14:43.127Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (23123.467 ms) ======
[2025-12-16T09:14:43.127Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-16T09:14:43.127Z] GC before operation: completed in 176.755 ms, heap usage 119.903 MB -> 90.688 MB.
[2025-12-16T09:14:46.499Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:14:49.842Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:14:53.207Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:14:57.636Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:14:59.190Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:15:00.751Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:15:03.879Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:15:05.438Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:15:05.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-16T09:15:05.438Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:15:06.204Z] Top recommended movies for user id 72:
[2025-12-16T09:15:06.204Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:15:06.204Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:15:06.204Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:15:06.204Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:15:06.204Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:15:06.204Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (22969.142 ms) ======
[2025-12-16T09:15:06.204Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-16T09:15:06.204Z] GC before operation: completed in 171.635 ms, heap usage 524.732 MB -> 90.181 MB.
[2025-12-16T09:15:11.685Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:15:14.306Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:15:19.799Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:15:23.143Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:15:25.571Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:15:27.140Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:15:29.568Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:15:31.123Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:15:31.875Z] 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.
[2025-12-16T09:15:31.875Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:15:31.875Z] Top recommended movies for user id 72:
[2025-12-16T09:15:31.875Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:15:31.875Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:15:31.875Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:15:31.875Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:15:31.875Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:15:31.875Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (25670.494 ms) ======
[2025-12-16T09:15:31.875Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-16T09:15:31.875Z] GC before operation: completed in 148.569 ms, heap usage 393.759 MB -> 89.895 MB.
[2025-12-16T09:15:35.232Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:15:38.598Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:15:41.959Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:15:45.342Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:15:46.906Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:15:48.604Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:15:51.037Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:15:52.718Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:15:53.469Z] 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.
[2025-12-16T09:15:53.469Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:15:53.469Z] Top recommended movies for user id 72:
[2025-12-16T09:15:53.469Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:15:53.469Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:15:53.469Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:15:53.469Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:15:53.469Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:15:53.469Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21373.044 ms) ======
[2025-12-16T09:15:53.469Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-16T09:15:53.469Z] GC before operation: completed in 175.068 ms, heap usage 492.731 MB -> 90.770 MB.
[2025-12-16T09:15:56.476Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:15:59.831Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:16:03.178Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:16:05.628Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:16:08.046Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:16:09.594Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:16:11.145Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:16:12.702Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:16:13.456Z] 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.
[2025-12-16T09:16:13.456Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:16:13.456Z] Top recommended movies for user id 72:
[2025-12-16T09:16:13.456Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:16:13.456Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:16:13.456Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:16:13.456Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:16:13.456Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:16:13.456Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20129.424 ms) ======
[2025-12-16T09:16:13.456Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-16T09:16:13.456Z] GC before operation: completed in 182.382 ms, heap usage 233.799 MB -> 89.797 MB.
[2025-12-16T09:16:16.808Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:16:20.168Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:16:23.567Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:16:26.006Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:16:27.572Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:16:29.996Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:16:31.565Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:16:33.134Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:16:33.134Z] 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.
[2025-12-16T09:16:33.134Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:16:33.883Z] Top recommended movies for user id 72:
[2025-12-16T09:16:33.883Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:16:33.883Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:16:33.883Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:16:33.883Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:16:33.883Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:16:33.883Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19880.500 ms) ======
[2025-12-16T09:16:33.883Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-16T09:16:33.883Z] GC before operation: completed in 159.328 ms, heap usage 249.119 MB -> 90.051 MB.
[2025-12-16T09:16:37.236Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:16:40.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:16:43.509Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:16:45.936Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:16:47.497Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:16:49.921Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:16:51.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:16:53.074Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:16:53.831Z] 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.
[2025-12-16T09:16:53.831Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:16:53.831Z] Top recommended movies for user id 72:
[2025-12-16T09:16:53.831Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:16:53.831Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:16:53.831Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:16:53.831Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:16:53.831Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:16:53.831Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20063.770 ms) ======
[2025-12-16T09:16:53.831Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-16T09:16:53.831Z] GC before operation: completed in 164.198 ms, heap usage 198.863 MB -> 89.704 MB.
[2025-12-16T09:16:57.221Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:16:59.700Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:17:03.121Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:17:06.487Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:17:08.040Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:17:10.471Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:17:12.143Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:17:14.573Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:17:14.573Z] 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.
[2025-12-16T09:17:14.573Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:17:14.573Z] Top recommended movies for user id 72:
[2025-12-16T09:17:14.573Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:17:14.573Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:17:14.573Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:17:14.573Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:17:14.573Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:17:14.573Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20762.299 ms) ======
[2025-12-16T09:17:14.573Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-16T09:17:14.573Z] GC before operation: completed in 144.746 ms, heap usage 134.608 MB -> 89.891 MB.
[2025-12-16T09:17:18.953Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:17:22.825Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:17:26.179Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:17:28.613Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:17:31.065Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:17:33.489Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:17:35.053Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:17:37.471Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:17:37.471Z] 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.
[2025-12-16T09:17:37.471Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:17:38.268Z] Top recommended movies for user id 72:
[2025-12-16T09:17:38.268Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:17:38.268Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:17:38.268Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:17:38.268Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:17:38.268Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:17:38.268Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22926.366 ms) ======
[2025-12-16T09:17:38.268Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-16T09:17:38.268Z] GC before operation: completed in 177.177 ms, heap usage 383.235 MB -> 90.278 MB.
[2025-12-16T09:17:41.634Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:17:45.027Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:17:48.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:17:50.933Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:17:53.395Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:17:54.952Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:17:57.382Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:17:58.946Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:17:58.946Z] 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.
[2025-12-16T09:17:58.946Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:17:59.712Z] Top recommended movies for user id 72:
[2025-12-16T09:17:59.712Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:17:59.712Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:17:59.712Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:17:59.712Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:17:59.712Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:17:59.712Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (21444.853 ms) ======
[2025-12-16T09:17:59.712Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-16T09:17:59.712Z] GC before operation: completed in 195.765 ms, heap usage 182.339 MB -> 89.957 MB.
[2025-12-16T09:18:03.588Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:18:06.018Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:18:10.408Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:18:12.825Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:18:15.256Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:18:16.822Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:18:19.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:18:20.809Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:18:21.560Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-16T09:18:21.560Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:18:21.560Z] Top recommended movies for user id 72:
[2025-12-16T09:18:21.560Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:18:21.560Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:18:21.560Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:18:21.560Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:18:21.560Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:18:21.560Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (21939.622 ms) ======
[2025-12-16T09:18:21.560Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-16T09:18:21.560Z] GC before operation: completed in 151.776 ms, heap usage 384.658 MB -> 90.390 MB.
[2025-12-16T09:18:24.934Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:18:28.297Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:18:31.698Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:18:35.079Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:18:36.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:18:39.063Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:18:40.625Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:18:43.055Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:18:43.055Z] 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.
[2025-12-16T09:18:43.055Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:18:43.055Z] Top recommended movies for user id 72:
[2025-12-16T09:18:43.055Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:18:43.055Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:18:43.055Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:18:43.055Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:18:43.055Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:18:43.055Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21604.675 ms) ======
[2025-12-16T09:18:43.055Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-16T09:18:43.802Z] GC before operation: completed in 166.722 ms, heap usage 132.798 MB -> 89.859 MB.
[2025-12-16T09:18:46.725Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:18:50.097Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:18:53.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:18:56.826Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:18:58.395Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:19:00.807Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:19:03.218Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:19:04.787Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:19:05.540Z] 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.
[2025-12-16T09:19:05.540Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:19:05.540Z] Top recommended movies for user id 72:
[2025-12-16T09:19:05.540Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:19:05.540Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:19:05.540Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:19:05.540Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:19:05.540Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:19:05.540Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (21941.891 ms) ======
[2025-12-16T09:19:05.540Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-16T09:19:05.540Z] GC before operation: completed in 174.436 ms, heap usage 104.505 MB -> 89.868 MB.
[2025-12-16T09:19:08.908Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:19:12.377Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:19:14.807Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:19:18.199Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:19:19.759Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:19:21.313Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:19:23.739Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:19:25.307Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:19:25.307Z] 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.
[2025-12-16T09:19:25.307Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:19:25.307Z] Top recommended movies for user id 72:
[2025-12-16T09:19:25.307Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:19:25.307Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:19:25.307Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:19:25.307Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:19:25.307Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:19:25.307Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19900.162 ms) ======
[2025-12-16T09:19:25.307Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-16T09:19:26.057Z] GC before operation: completed in 191.732 ms, heap usage 693.316 MB -> 93.692 MB.
[2025-12-16T09:19:28.474Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:19:32.104Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:19:35.465Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:19:38.839Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:19:40.405Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:19:42.820Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:19:44.391Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:19:46.819Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:19:46.819Z] 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.
[2025-12-16T09:19:46.819Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:19:46.819Z] Top recommended movies for user id 72:
[2025-12-16T09:19:46.819Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:19:46.819Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:19:46.819Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:19:46.819Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:19:46.819Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:19:46.819Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (21211.842 ms) ======
[2025-12-16T09:19:46.819Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-16T09:19:46.819Z] GC before operation: completed in 192.587 ms, heap usage 123.565 MB -> 89.791 MB.
[2025-12-16T09:19:50.213Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-16T09:19:53.571Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-16T09:19:56.967Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-16T09:20:00.313Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-16T09:20:02.740Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-16T09:20:04.298Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-16T09:20:05.871Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-16T09:20:08.289Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-16T09:20:08.289Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-16T09:20:08.289Z] The best model improves the baseline by 14.52%.
[2025-12-16T09:20:09.039Z] Top recommended movies for user id 72:
[2025-12-16T09:20:09.039Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-16T09:20:09.039Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-16T09:20:09.039Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-16T09:20:09.039Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-16T09:20:09.039Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-16T09:20:09.039Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (21526.413 ms) ======
[2025-12-16T09:20:09.039Z] -----------------------------------
[2025-12-16T09:20:09.039Z] renaissance-movie-lens_0_PASSED
[2025-12-16T09:20:09.039Z] -----------------------------------
[2025-12-16T09:20:09.039Z]
[2025-12-16T09:20:09.039Z] TEST TEARDOWN:
[2025-12-16T09:20:09.039Z] Nothing to be done for teardown.
[2025-12-16T09:20:09.039Z] renaissance-movie-lens_0 Finish Time: Tue Dec 16 09:20:08 2025 Epoch Time (ms): 1765876808937