renaissance-movie-lens_0
[2025-12-13T13:25:10.062Z] Running test renaissance-movie-lens_0 ...
[2025-12-13T13:25:10.062Z] ===============================================
[2025-12-13T13:25:10.062Z] renaissance-movie-lens_0 Start Time: Sat Dec 13 08:25:10 2025 Epoch Time (ms): 1765632310028
[2025-12-13T13:25:10.424Z] variation: NoOptions
[2025-12-13T13:25:10.424Z] JVM_OPTIONS:
[2025-12-13T13:25:10.424Z] { \
[2025-12-13T13:25:10.424Z] echo ""; echo "TEST SETUP:"; \
[2025-12-13T13:25:10.424Z] echo "Nothing to be done for setup."; \
[2025-12-13T13:25:10.424Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17656316961245/renaissance-movie-lens_0"; \
[2025-12-13T13:25:10.424Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17656316961245/renaissance-movie-lens_0"; \
[2025-12-13T13:25:10.424Z] echo ""; echo "TESTING:"; \
[2025-12-13T13:25:10.424Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17656316961245/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-13T13:25:10.424Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17656316961245/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-13T13:25:10.424Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-13T13:25:10.424Z] echo "Nothing to be done for teardown."; \
[2025-12-13T13:25:10.424Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17656316961245/TestTargetResult";
[2025-12-13T13:25:10.424Z]
[2025-12-13T13:25:10.424Z] TEST SETUP:
[2025-12-13T13:25:10.424Z] Nothing to be done for setup.
[2025-12-13T13:25:10.424Z]
[2025-12-13T13:25:10.424Z] TESTING:
[2025-12-13T13:25:10.424Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-13T13:25:10.424Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/output_17656316961245/renaissance-movie-lens_0/launcher-082510-18310222771640338169/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-13T13:25:10.424Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-13T13:25:10.424Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-13T13:25:13.609Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-13T13:25:17.700Z] 08:25:16.954 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-13T13:25:18.078Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-13T13:25:18.456Z] Training: 60056, validation: 20285, test: 19854
[2025-12-13T13:25:18.456Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-13T13:25:18.456Z] GC before operation: completed in 67.331 ms, heap usage 342.467 MB -> 75.992 MB.
[2025-12-13T13:25:21.772Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:25:23.028Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:25:24.842Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:25:26.354Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:25:27.640Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:25:27.995Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:25:29.255Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:25:29.611Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:25:30.012Z] 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.
[2025-12-13T13:25:30.012Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:25:30.012Z] Top recommended movies for user id 72:
[2025-12-13T13:25:30.012Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:25:30.012Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:25:30.012Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:25:30.012Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:25:30.012Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:25:30.012Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11497.914 ms) ======
[2025-12-13T13:25:30.012Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-13T13:25:30.012Z] GC before operation: completed in 68.786 ms, heap usage 298.384 MB -> 97.844 MB.
[2025-12-13T13:25:31.807Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:25:33.082Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:25:34.320Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:25:35.578Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:25:36.351Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:25:37.125Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:25:37.919Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:25:38.723Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:25:39.095Z] 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.
[2025-12-13T13:25:39.095Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:25:39.095Z] Top recommended movies for user id 72:
[2025-12-13T13:25:39.095Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:25:39.095Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:25:39.095Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:25:39.095Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:25:39.095Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:25:39.095Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9017.785 ms) ======
[2025-12-13T13:25:39.095Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-13T13:25:39.095Z] GC before operation: completed in 51.383 ms, heap usage 157.586 MB -> 88.675 MB.
[2025-12-13T13:25:40.382Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:25:42.216Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:25:43.454Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:25:44.706Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:25:45.863Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:25:46.232Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:25:46.999Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:25:47.814Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:25:48.169Z] 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.
[2025-12-13T13:25:48.169Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:25:48.169Z] Top recommended movies for user id 72:
[2025-12-13T13:25:48.169Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:25:48.169Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:25:48.169Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:25:48.169Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:25:48.169Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:25:48.169Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9002.161 ms) ======
[2025-12-13T13:25:48.169Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-13T13:25:48.169Z] GC before operation: completed in 62.447 ms, heap usage 316.909 MB -> 89.558 MB.
[2025-12-13T13:25:49.395Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:25:50.652Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:25:52.477Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:25:53.712Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:25:54.504Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:25:55.284Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:25:56.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:25:57.300Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:25:57.300Z] 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.
[2025-12-13T13:25:57.300Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:25:57.300Z] Top recommended movies for user id 72:
[2025-12-13T13:25:57.300Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:25:57.300Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:25:57.300Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:25:57.300Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:25:57.300Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:25:57.300Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9070.105 ms) ======
[2025-12-13T13:25:57.300Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-13T13:25:57.300Z] GC before operation: completed in 58.539 ms, heap usage 104.818 MB -> 89.542 MB.
[2025-12-13T13:25:58.560Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:25:59.816Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:26:01.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:26:02.334Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:26:03.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:26:03.919Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:26:20.922Z] 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.
[2025-12-13T13:26:20.922Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:26:20.922Z] Top recommended movies for user id 72:
[2025-12-13T13:26:20.922Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:26:20.922Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:26:20.922Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:26:20.922Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:26:20.922Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:26:20.922Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8421.832 ms) ======
[2025-12-13T13:26:20.922Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-13T13:26:20.922Z] GC before operation: completed in 46.816 ms, heap usage 191.467 MB -> 89.683 MB.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:26:20.922Z] 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.
[2025-12-13T13:26:20.922Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:26:20.922Z] Top recommended movies for user id 72:
[2025-12-13T13:26:20.922Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:26:20.922Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:26:20.922Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:26:20.922Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:26:20.922Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:26:20.922Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8563.545 ms) ======
[2025-12-13T13:26:20.922Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-13T13:26:20.922Z] GC before operation: completed in 62.789 ms, heap usage 362.548 MB -> 90.287 MB.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:26:20.922Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:26:21.287Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:26:22.539Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:26:23.303Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:26:24.546Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:26:24.546Z] 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.
[2025-12-13T13:26:24.546Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:26:24.906Z] Top recommended movies for user id 72:
[2025-12-13T13:26:24.906Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:26:24.906Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:26:24.906Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:26:24.906Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:26:24.906Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:26:24.906Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (10300.522 ms) ======
[2025-12-13T13:26:24.906Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-13T13:26:24.906Z] GC before operation: completed in 71.714 ms, heap usage 444.594 MB -> 90.306 MB.
[2025-12-13T13:26:26.161Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:26:27.945Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:26:29.772Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:26:31.037Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:26:31.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:26:33.071Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:26:33.844Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:26:35.148Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:26:35.148Z] 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.
[2025-12-13T13:26:35.148Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:26:35.148Z] Top recommended movies for user id 72:
[2025-12-13T13:26:35.148Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:26:35.148Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:26:35.148Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:26:35.148Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:26:35.148Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:26:35.148Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (10344.884 ms) ======
[2025-12-13T13:26:35.148Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-13T13:26:35.148Z] GC before operation: completed in 72.881 ms, heap usage 132.305 MB -> 90.049 MB.
[2025-12-13T13:26:36.948Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:26:38.207Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:26:40.096Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:26:41.380Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:26:42.200Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:26:43.487Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:26:44.258Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:26:45.506Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:26:45.506Z] 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.
[2025-12-13T13:26:45.506Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:26:45.506Z] Top recommended movies for user id 72:
[2025-12-13T13:26:45.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:26:45.506Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:26:45.506Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:26:45.506Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:26:45.506Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:26:45.506Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (10342.135 ms) ======
[2025-12-13T13:26:45.506Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-13T13:26:45.506Z] GC before operation: completed in 76.582 ms, heap usage 288.877 MB -> 90.290 MB.
[2025-12-13T13:26:47.464Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:26:48.753Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:26:50.095Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:26:51.917Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:26:52.708Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:26:53.542Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:26:54.843Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:26:55.686Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:26:55.686Z] 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.
[2025-12-13T13:26:55.686Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:26:55.686Z] Top recommended movies for user id 72:
[2025-12-13T13:26:55.686Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:26:55.686Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:26:55.686Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:26:55.686Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:26:55.686Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:26:55.686Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (10077.526 ms) ======
[2025-12-13T13:26:55.686Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-13T13:26:55.686Z] GC before operation: completed in 74.051 ms, heap usage 306.247 MB -> 90.503 MB.
[2025-12-13T13:26:57.565Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:26:58.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:27:00.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:27:02.048Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:27:02.849Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:27:03.661Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:27:04.991Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:27:05.784Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:27:05.784Z] 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.
[2025-12-13T13:27:05.784Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:27:06.153Z] Top recommended movies for user id 72:
[2025-12-13T13:27:06.153Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:27:06.153Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:27:06.153Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:27:06.153Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:27:06.153Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:27:06.153Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (10203.844 ms) ======
[2025-12-13T13:27:06.153Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-13T13:27:06.153Z] GC before operation: completed in 63.131 ms, heap usage 364.169 MB -> 90.335 MB.
[2025-12-13T13:27:07.463Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:27:09.322Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:27:10.593Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:27:12.429Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:27:13.216Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:27:14.547Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:27:15.413Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:27:16.248Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:27:16.248Z] 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.
[2025-12-13T13:27:16.248Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:27:16.636Z] Top recommended movies for user id 72:
[2025-12-13T13:27:16.636Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:27:16.636Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:27:16.636Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:27:16.636Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:27:16.636Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:27:16.636Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (10398.880 ms) ======
[2025-12-13T13:27:16.636Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-13T13:27:16.636Z] GC before operation: completed in 62.630 ms, heap usage 107.382 MB -> 90.518 MB.
[2025-12-13T13:27:17.936Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:27:19.788Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:27:21.050Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:27:22.948Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:27:23.307Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:27:24.565Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:27:25.362Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:27:26.141Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:27:26.524Z] 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.
[2025-12-13T13:27:26.524Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:27:26.524Z] Top recommended movies for user id 72:
[2025-12-13T13:27:26.524Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:27:26.524Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:27:26.524Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:27:26.524Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:27:26.524Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:27:26.524Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (10042.611 ms) ======
[2025-12-13T13:27:26.524Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-13T13:27:26.524Z] GC before operation: completed in 62.141 ms, heap usage 424.607 MB -> 90.738 MB.
[2025-12-13T13:27:28.376Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:27:29.647Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:27:31.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:27:32.816Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:27:33.630Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:27:34.407Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:27:35.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:27:36.021Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:27:36.493Z] 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.
[2025-12-13T13:27:36.493Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:27:36.493Z] Top recommended movies for user id 72:
[2025-12-13T13:27:36.493Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:27:36.493Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:27:36.493Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:27:36.493Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:27:36.493Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:27:36.493Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (9730.321 ms) ======
[2025-12-13T13:27:36.493Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-13T13:27:36.493Z] GC before operation: completed in 72.020 ms, heap usage 464.492 MB -> 90.552 MB.
[2025-12-13T13:27:37.781Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:27:39.612Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:27:40.897Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:27:42.198Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:27:42.556Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:27:43.329Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:27:44.113Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:27:44.879Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:27:44.879Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T13:27:44.879Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:27:45.237Z] Top recommended movies for user id 72:
[2025-12-13T13:27:45.237Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:27:45.237Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:27:45.237Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:27:45.237Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:27:45.237Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:27:45.237Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8695.655 ms) ======
[2025-12-13T13:27:45.237Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-13T13:27:45.237Z] GC before operation: completed in 49.031 ms, heap usage 126.720 MB -> 90.799 MB.
[2025-12-13T13:27:46.479Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:27:47.724Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:27:49.015Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:27:50.258Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:27:51.019Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:27:51.783Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:27:52.555Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:27:52.928Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:27:53.292Z] 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.
[2025-12-13T13:27:53.292Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:27:53.292Z] Top recommended movies for user id 72:
[2025-12-13T13:27:53.292Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:27:53.292Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:27:53.292Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:27:53.292Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:27:53.292Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:27:53.292Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8116.870 ms) ======
[2025-12-13T13:27:53.292Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-13T13:27:53.292Z] GC before operation: completed in 58.272 ms, heap usage 365.224 MB -> 90.474 MB.
[2025-12-13T13:27:54.556Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:27:55.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:27:57.039Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:27:58.283Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:27:59.092Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:27:59.866Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:28:00.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:28:01.490Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:28:01.490Z] 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.
[2025-12-13T13:28:01.490Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:28:01.855Z] Top recommended movies for user id 72:
[2025-12-13T13:28:01.855Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:28:01.855Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:28:01.855Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:28:01.855Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:28:01.855Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:28:01.855Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8406.792 ms) ======
[2025-12-13T13:28:01.855Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-13T13:28:01.855Z] GC before operation: completed in 53.388 ms, heap usage 175.502 MB -> 90.256 MB.
[2025-12-13T13:28:03.096Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:28:04.350Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:28:05.585Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:28:06.822Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:28:07.595Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:28:08.356Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:28:09.116Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:28:09.893Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:28:09.893Z] 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.
[2025-12-13T13:28:09.893Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:28:09.893Z] Top recommended movies for user id 72:
[2025-12-13T13:28:09.893Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:28:09.893Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:28:09.893Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:28:09.893Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:28:09.893Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:28:09.893Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8194.605 ms) ======
[2025-12-13T13:28:09.893Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-13T13:28:09.893Z] GC before operation: completed in 54.561 ms, heap usage 351.379 MB -> 90.377 MB.
[2025-12-13T13:28:11.156Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:28:12.950Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:28:14.275Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:28:16.078Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:28:16.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:28:17.668Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:28:18.433Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:28:19.238Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:28:19.238Z] 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.
[2025-12-13T13:28:19.238Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:28:19.603Z] Top recommended movies for user id 72:
[2025-12-13T13:28:19.603Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:28:19.603Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:28:19.603Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:28:19.603Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:28:19.603Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:28:19.603Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (9440.526 ms) ======
[2025-12-13T13:28:19.603Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-13T13:28:19.603Z] GC before operation: completed in 73.479 ms, heap usage 352.077 MB -> 90.436 MB.
[2025-12-13T13:28:21.446Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T13:28:22.719Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T13:28:24.004Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T13:28:25.325Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T13:28:26.652Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T13:28:27.030Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T13:28:27.803Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T13:28:28.602Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T13:28:28.602Z] 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.
[2025-12-13T13:28:28.602Z] The best model improves the baseline by 14.52%.
[2025-12-13T13:28:28.967Z] Top recommended movies for user id 72:
[2025-12-13T13:28:28.967Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T13:28:28.967Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T13:28:28.967Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T13:28:28.967Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T13:28:28.967Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T13:28:28.967Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (9261.346 ms) ======
[2025-12-13T13:28:28.967Z] -----------------------------------
[2025-12-13T13:28:28.967Z] renaissance-movie-lens_0_PASSED
[2025-12-13T13:28:28.967Z] -----------------------------------
[2025-12-13T13:28:28.967Z]
[2025-12-13T13:28:28.967Z] TEST TEARDOWN:
[2025-12-13T13:28:28.967Z] Nothing to be done for teardown.
[2025-12-13T13:28:28.967Z] renaissance-movie-lens_0 Finish Time: Sat Dec 13 08:28:28 2025 Epoch Time (ms): 1765632508830