renaissance-movie-lens_0
[2025-09-05T16:22:37.513Z] Running test renaissance-movie-lens_0 ...
[2025-09-05T16:22:37.513Z] ===============================================
[2025-09-05T16:22:37.513Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 16:22:36 2025 Epoch Time (ms): 1757089356716
[2025-09-05T16:22:37.513Z] variation: NoOptions
[2025-09-05T16:22:37.513Z] JVM_OPTIONS:
[2025-09-05T16:22:37.513Z] { \
[2025-09-05T16:22:37.513Z] echo ""; echo "TEST SETUP:"; \
[2025-09-05T16:22:37.513Z] echo "Nothing to be done for setup."; \
[2025-09-05T16:22:37.513Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17570872854519/renaissance-movie-lens_0"; \
[2025-09-05T16:22:37.513Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17570872854519/renaissance-movie-lens_0"; \
[2025-09-05T16:22:37.513Z] echo ""; echo "TESTING:"; \
[2025-09-05T16:22:37.513Z] "/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_17570872854519/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-05T16:22:37.513Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17570872854519/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-05T16:22:37.513Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-05T16:22:37.513Z] echo "Nothing to be done for teardown."; \
[2025-09-05T16:22:37.513Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17570872854519/TestTargetResult";
[2025-09-05T16:22:37.513Z]
[2025-09-05T16:22:37.513Z] TEST SETUP:
[2025-09-05T16:22:37.513Z] Nothing to be done for setup.
[2025-09-05T16:22:37.513Z]
[2025-09-05T16:22:37.513Z] TESTING:
[2025-09-05T16:22:38.262Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-09-05T16:22:38.262Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/output_17570872854519/renaissance-movie-lens_0/launcher-162236-2762885996022978947/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-09-05T16:22:38.262Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-09-05T16:22:38.262Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-09-05T16:22:46.465Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-05T16:22:58.090Z] 16:22:57.565 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.
[2025-09-05T16:23:01.520Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-05T16:23:02.286Z] Training: 60056, validation: 20285, test: 19854
[2025-09-05T16:23:02.286Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-05T16:23:02.286Z] GC before operation: completed in 260.299 ms, heap usage 298.456 MB -> 75.670 MB.
[2025-09-05T16:23:14.633Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:23:21.450Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:23:28.266Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:23:35.054Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:23:38.452Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:23:41.831Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:23:45.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:23:47.636Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:23:48.399Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:23:48.399Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:23:48.399Z] Top recommended movies for user id 72:
[2025-09-05T16:23:48.399Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:23:48.399Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:23:48.399Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:23:48.399Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:23:48.399Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:23:48.399Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (45989.021 ms) ======
[2025-09-05T16:23:48.399Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-05T16:23:48.399Z] GC before operation: completed in 184.182 ms, heap usage 702.611 MB -> 96.631 MB.
[2025-09-05T16:23:53.944Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:23:58.353Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:24:06.572Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:24:12.117Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:24:14.554Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:24:20.070Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:24:24.469Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:24:27.841Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:24:27.841Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:24:28.597Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:24:28.597Z] Top recommended movies for user id 72:
[2025-09-05T16:24:28.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:24:28.597Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:24:28.597Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:24:28.597Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:24:28.597Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:24:28.597Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (39701.335 ms) ======
[2025-09-05T16:24:28.597Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-05T16:24:28.597Z] GC before operation: completed in 273.015 ms, heap usage 465.495 MB -> 88.564 MB.
[2025-09-05T16:24:35.428Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:24:40.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:24:45.914Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:24:50.326Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:24:52.759Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:24:56.121Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:24:58.587Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:25:01.015Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:25:01.793Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:25:01.793Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:25:02.550Z] Top recommended movies for user id 72:
[2025-09-05T16:25:02.550Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:25:02.550Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:25:02.550Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:25:02.550Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:25:02.551Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:25:02.551Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (33595.239 ms) ======
[2025-09-05T16:25:02.551Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-05T16:25:02.551Z] GC before operation: completed in 301.872 ms, heap usage 367.525 MB -> 89.094 MB.
[2025-09-05T16:25:08.072Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:25:12.465Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:25:18.035Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:25:22.955Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:25:24.522Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:25:27.930Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:25:33.443Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:25:36.754Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:25:37.506Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:25:37.506Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:25:37.506Z] Top recommended movies for user id 72:
[2025-09-05T16:25:37.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:25:37.506Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:25:37.506Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:25:37.506Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:25:37.506Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:25:37.506Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (35121.838 ms) ======
[2025-09-05T16:25:37.506Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-05T16:25:38.262Z] GC before operation: completed in 214.019 ms, heap usage 102.538 MB -> 92.791 MB.
[2025-09-05T16:25:45.028Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:25:50.577Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:25:54.972Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:25:59.365Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:26:02.771Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:26:05.286Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:26:07.906Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:26:11.278Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:26:11.278Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:26:11.278Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:26:11.278Z] Top recommended movies for user id 72:
[2025-09-05T16:26:11.278Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:26:11.278Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:26:11.278Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:26:11.278Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:26:11.278Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:26:11.278Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (33588.263 ms) ======
[2025-09-05T16:26:11.278Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-05T16:26:12.042Z] GC before operation: completed in 221.927 ms, heap usage 448.757 MB -> 89.350 MB.
[2025-09-05T16:26:16.453Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:26:20.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:26:25.271Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:26:29.695Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:26:33.072Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:26:35.504Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:26:37.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:26:40.426Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:26:40.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:26:41.188Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:26:41.188Z] Top recommended movies for user id 72:
[2025-09-05T16:26:41.188Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:26:41.188Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:26:41.188Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:26:41.188Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:26:41.188Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:26:41.188Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (29302.158 ms) ======
[2025-09-05T16:26:41.188Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-05T16:26:41.188Z] GC before operation: completed in 339.186 ms, heap usage 280.516 MB -> 89.527 MB.
[2025-09-05T16:26:46.735Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:26:51.152Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:26:55.971Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:27:00.372Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:27:03.832Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:27:06.335Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:27:08.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:27:12.230Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:27:12.988Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:27:12.988Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:27:12.988Z] Top recommended movies for user id 72:
[2025-09-05T16:27:12.988Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:27:12.988Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:27:12.988Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:27:12.988Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:27:12.988Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:27:12.988Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (31519.115 ms) ======
[2025-09-05T16:27:12.988Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-05T16:27:12.988Z] GC before operation: completed in 218.213 ms, heap usage 148.946 MB -> 89.201 MB.
[2025-09-05T16:27:18.508Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:27:22.910Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:27:28.451Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:27:32.840Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:27:36.218Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:27:39.163Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:27:41.593Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:27:44.038Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:27:44.797Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:27:44.797Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:27:45.556Z] Top recommended movies for user id 72:
[2025-09-05T16:27:45.556Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:27:45.556Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:27:45.556Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:27:45.556Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:27:45.556Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:27:45.556Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (32175.582 ms) ======
[2025-09-05T16:27:45.556Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-05T16:27:45.556Z] GC before operation: completed in 237.659 ms, heap usage 121.282 MB -> 89.444 MB.
[2025-09-05T16:27:51.066Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:27:57.227Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:28:01.635Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:28:09.790Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:28:13.305Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:28:15.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:28:24.687Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:28:27.120Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:28:27.120Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:28:27.877Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:28:27.877Z] Top recommended movies for user id 72:
[2025-09-05T16:28:27.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:28:27.877Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:28:27.877Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:28:27.877Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:28:27.877Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:28:27.877Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42193.073 ms) ======
[2025-09-05T16:28:27.877Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-05T16:28:27.877Z] GC before operation: completed in 217.580 ms, heap usage 483.242 MB -> 89.912 MB.
[2025-09-05T16:28:35.117Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:28:39.541Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:28:43.945Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:28:48.348Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:28:50.803Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:28:53.246Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:28:55.684Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:28:59.061Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:28:59.061Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:28:59.061Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:28:59.061Z] Top recommended movies for user id 72:
[2025-09-05T16:28:59.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:28:59.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:28:59.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:28:59.061Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:28:59.062Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:28:59.062Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (31238.285 ms) ======
[2025-09-05T16:28:59.062Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-05T16:28:59.821Z] GC before operation: completed in 232.851 ms, heap usage 418.498 MB -> 90.024 MB.
[2025-09-05T16:29:04.225Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:29:07.602Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:29:13.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:29:16.994Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:29:19.437Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:29:21.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:29:24.294Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:29:26.723Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:29:26.723Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:29:27.478Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:29:27.478Z] Top recommended movies for user id 72:
[2025-09-05T16:29:27.478Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:29:27.478Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:29:27.478Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:29:27.478Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:29:27.478Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:29:27.478Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27909.083 ms) ======
[2025-09-05T16:29:27.478Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-05T16:29:27.478Z] GC before operation: completed in 232.505 ms, heap usage 690.490 MB -> 93.321 MB.
[2025-09-05T16:29:31.877Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:29:36.275Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:29:40.724Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:29:44.117Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:29:47.486Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:29:49.909Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:29:52.331Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:29:54.766Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:29:55.521Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:29:55.521Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:29:55.521Z] Top recommended movies for user id 72:
[2025-09-05T16:29:55.521Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:29:55.521Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:29:55.521Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:29:55.521Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:29:55.521Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:29:55.521Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (28183.153 ms) ======
[2025-09-05T16:29:55.521Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-05T16:29:56.273Z] GC before operation: completed in 207.264 ms, heap usage 193.662 MB -> 89.666 MB.
[2025-09-05T16:30:00.667Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:30:04.693Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:30:10.212Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:30:13.600Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:30:16.037Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:30:18.510Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:30:20.955Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:30:23.394Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:30:24.163Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:30:24.163Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:30:24.163Z] Top recommended movies for user id 72:
[2025-09-05T16:30:24.163Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:30:24.163Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:30:24.163Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:30:24.163Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:30:24.163Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:30:24.163Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (28103.252 ms) ======
[2025-09-05T16:30:24.163Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-05T16:30:24.163Z] GC before operation: completed in 217.799 ms, heap usage 186.030 MB -> 89.707 MB.
[2025-09-05T16:30:28.543Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:30:32.944Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:30:37.350Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:30:41.737Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:30:43.304Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:30:45.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:30:48.768Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:30:50.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:30:51.087Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:30:51.087Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:30:51.087Z] Top recommended movies for user id 72:
[2025-09-05T16:30:51.087Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:30:51.087Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:30:51.087Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:30:51.087Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:30:51.087Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:30:51.087Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (26920.792 ms) ======
[2025-09-05T16:30:51.087Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-05T16:30:51.840Z] GC before operation: completed in 249.850 ms, heap usage 545.771 MB -> 93.220 MB.
[2025-09-05T16:30:56.233Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:30:59.609Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:31:04.014Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:31:08.413Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:31:10.873Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:31:12.436Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:31:15.803Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:31:17.370Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:31:18.166Z] 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.
[2025-09-05T16:31:18.166Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:31:18.166Z] Top recommended movies for user id 72:
[2025-09-05T16:31:18.166Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:31:18.166Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:31:18.166Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:31:18.166Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:31:18.166Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:31:18.166Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (26764.464 ms) ======
[2025-09-05T16:31:18.166Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-05T16:31:18.166Z] GC before operation: completed in 218.749 ms, heap usage 169.945 MB -> 89.792 MB.
[2025-09-05T16:31:22.545Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:31:26.967Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:31:30.346Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:31:34.233Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:31:36.676Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:31:39.107Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:31:42.482Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:31:44.919Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:31:44.919Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:31:44.919Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:31:44.919Z] Top recommended movies for user id 72:
[2025-09-05T16:31:44.919Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:31:44.919Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:31:44.919Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:31:44.919Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:31:44.919Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:31:44.919Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (26617.043 ms) ======
[2025-09-05T16:31:44.919Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-05T16:31:44.919Z] GC before operation: completed in 215.435 ms, heap usage 323.588 MB -> 89.780 MB.
[2025-09-05T16:31:49.300Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:31:53.715Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:31:57.087Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:32:01.465Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:32:03.904Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:32:05.483Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:32:07.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:32:10.350Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:32:11.102Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:32:11.102Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:32:11.102Z] Top recommended movies for user id 72:
[2025-09-05T16:32:11.102Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:32:11.102Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:32:11.102Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:32:11.102Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:32:11.102Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:32:11.102Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (25787.965 ms) ======
[2025-09-05T16:32:11.102Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-05T16:32:11.102Z] GC before operation: completed in 217.805 ms, heap usage 375.885 MB -> 90.003 MB.
[2025-09-05T16:32:15.514Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:32:19.383Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:32:23.781Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:32:27.165Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:32:29.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:32:32.481Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:32:34.914Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:32:37.358Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:32:37.358Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:32:37.358Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:32:37.358Z] Top recommended movies for user id 72:
[2025-09-05T16:32:37.358Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:32:37.358Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:32:37.358Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:32:37.358Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:32:37.358Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:32:37.358Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26283.637 ms) ======
[2025-09-05T16:32:37.358Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-05T16:32:38.115Z] GC before operation: completed in 213.404 ms, heap usage 126.011 MB -> 90.139 MB.
[2025-09-05T16:32:41.481Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:32:45.892Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:32:50.314Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:32:54.694Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:32:58.058Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:33:00.497Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:33:03.876Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:33:06.337Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:33:07.086Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:33:07.086Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:33:07.086Z] Top recommended movies for user id 72:
[2025-09-05T16:33:07.086Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:33:07.086Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:33:07.086Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:33:07.086Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:33:07.086Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:33:07.086Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (29617.718 ms) ======
[2025-09-05T16:33:07.086Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-05T16:33:07.854Z] GC before operation: completed in 297.073 ms, heap usage 618.719 MB -> 93.449 MB.
[2025-09-05T16:33:12.373Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T16:33:16.769Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T16:33:21.178Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T16:33:25.573Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T16:33:27.135Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T16:33:29.572Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T16:33:32.525Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T16:33:34.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T16:33:34.862Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T16:33:34.862Z] The best model improves the baseline by 14.52%.
[2025-09-05T16:33:34.862Z] Top recommended movies for user id 72:
[2025-09-05T16:33:34.862Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T16:33:34.862Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T16:33:34.862Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T16:33:34.862Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T16:33:34.862Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T16:33:34.862Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27256.722 ms) ======
[2025-09-05T16:33:35.616Z] -----------------------------------
[2025-09-05T16:33:35.616Z] renaissance-movie-lens_0_PASSED
[2025-09-05T16:33:35.616Z] -----------------------------------
[2025-09-05T16:33:35.616Z]
[2025-09-05T16:33:35.616Z] TEST TEARDOWN:
[2025-09-05T16:33:35.616Z] Nothing to be done for teardown.
[2025-09-05T16:33:35.616Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 16:33:35 2025 Epoch Time (ms): 1757090015200