renaissance-movie-lens_0
[2025-11-26T22:13:20.578Z] Running test renaissance-movie-lens_0 ...
[2025-11-26T22:13:20.578Z] ===============================================
[2025-11-26T22:13:20.578Z] renaissance-movie-lens_0 Start Time: Wed Nov 26 17:13:20 2025 Epoch Time (ms): 1764195200029
[2025-11-26T22:13:20.578Z] variation: NoOptions
[2025-11-26T22:13:20.578Z] JVM_OPTIONS:
[2025-11-26T22:13:20.578Z] { \
[2025-11-26T22:13:20.578Z] echo ""; echo "TEST SETUP:"; \
[2025-11-26T22:13:20.578Z] echo "Nothing to be done for setup."; \
[2025-11-26T22:13:20.578Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17641944799804/renaissance-movie-lens_0"; \
[2025-11-26T22:13:20.578Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17641944799804/renaissance-movie-lens_0"; \
[2025-11-26T22:13:20.578Z] echo ""; echo "TESTING:"; \
[2025-11-26T22:13:20.578Z] "/Users/admin/workspace/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17641944799804/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-26T22:13:20.578Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17641944799804/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-26T22:13:20.578Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-26T22:13:20.578Z] echo "Nothing to be done for teardown."; \
[2025-11-26T22:13:20.578Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17641944799804/TestTargetResult";
[2025-11-26T22:13:20.578Z]
[2025-11-26T22:13:20.578Z] TEST SETUP:
[2025-11-26T22:13:20.578Z] Nothing to be done for setup.
[2025-11-26T22:13:20.578Z]
[2025-11-26T22:13:20.578Z] TESTING:
[2025-11-26T22:13:23.068Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-26T22:13:27.292Z] 17:13:26.728 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-26T22:13:28.655Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-26T22:13:28.655Z] Training: 60056, validation: 20285, test: 19854
[2025-11-26T22:13:28.655Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-26T22:13:28.655Z] GC before operation: completed in 82.440 ms, heap usage 494.941 MB -> 76.266 MB.
[2025-11-26T22:13:31.174Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:13:33.718Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:13:35.679Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:13:37.674Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:13:38.579Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:13:39.472Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:13:40.340Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:13:41.651Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:13:41.651Z] 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.
[2025-11-26T22:13:41.651Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:13:41.651Z] Top recommended movies for user id 72:
[2025-11-26T22:13:41.651Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:13:41.651Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:13:41.651Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:13:41.651Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:13:41.651Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:13:41.651Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (13377.694 ms) ======
[2025-11-26T22:13:41.651Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-26T22:13:41.651Z] GC before operation: completed in 77.901 ms, heap usage 203.268 MB -> 87.825 MB.
[2025-11-26T22:13:43.560Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:13:45.407Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:13:47.382Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:13:48.721Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:13:50.034Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:13:50.859Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:13:52.146Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:13:52.965Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:13:52.965Z] 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.
[2025-11-26T22:13:52.965Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:13:53.365Z] Top recommended movies for user id 72:
[2025-11-26T22:13:53.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:13:53.365Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:13:53.365Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:13:53.365Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:13:53.365Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:13:53.365Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (11398.945 ms) ======
[2025-11-26T22:13:53.365Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-26T22:13:53.365Z] GC before operation: completed in 71.927 ms, heap usage 472.523 MB -> 89.207 MB.
[2025-11-26T22:13:55.322Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:13:56.963Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:13:58.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:14:00.248Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:14:01.616Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:14:02.531Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:14:03.374Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:14:04.719Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:14:04.719Z] 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.
[2025-11-26T22:14:04.719Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:14:04.719Z] Top recommended movies for user id 72:
[2025-11-26T22:14:04.719Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:14:04.719Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:14:04.719Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:14:04.719Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:14:04.719Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:14:04.719Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (11592.296 ms) ======
[2025-11-26T22:14:04.719Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-26T22:14:05.094Z] GC before operation: completed in 70.037 ms, heap usage 110.920 MB -> 89.435 MB.
[2025-11-26T22:14:07.112Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:14:08.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:14:10.358Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:14:12.266Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:14:13.145Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:14:14.014Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:14:15.372Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:14:16.248Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:14:16.248Z] 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.
[2025-11-26T22:14:16.740Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:14:16.740Z] Top recommended movies for user id 72:
[2025-11-26T22:14:16.740Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:14:16.740Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:14:16.740Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:14:16.740Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:14:16.740Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:14:16.740Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (11591.582 ms) ======
[2025-11-26T22:14:16.740Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-26T22:14:16.740Z] GC before operation: completed in 85.031 ms, heap usage 126.627 MB -> 90.505 MB.
[2025-11-26T22:14:18.671Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:14:20.294Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:14:22.409Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:14:23.919Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:14:25.485Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:14:26.458Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:14:27.386Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:14:28.746Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:14:28.746Z] 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.
[2025-11-26T22:14:28.746Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:14:28.746Z] Top recommended movies for user id 72:
[2025-11-26T22:14:28.746Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:14:28.746Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:14:28.746Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:14:28.746Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:14:28.746Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:14:28.746Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (12265.932 ms) ======
[2025-11-26T22:14:28.746Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-26T22:14:29.182Z] GC before operation: completed in 72.258 ms, heap usage 122.629 MB -> 89.690 MB.
[2025-11-26T22:14:30.711Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:14:32.710Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:14:34.638Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:14:36.557Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:14:36.973Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:14:37.806Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:14:39.140Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:14:39.579Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:14:39.970Z] 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.
[2025-11-26T22:14:39.970Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:14:39.970Z] Top recommended movies for user id 72:
[2025-11-26T22:14:39.970Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:14:39.970Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:14:39.970Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:14:39.970Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:14:39.970Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:14:39.970Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (11014.350 ms) ======
[2025-11-26T22:14:39.970Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-26T22:14:39.970Z] GC before operation: completed in 64.931 ms, heap usage 354.160 MB -> 90.307 MB.
[2025-11-26T22:14:41.912Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:14:43.224Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:14:46.363Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:14:46.363Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:14:46.823Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:14:47.632Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:14:48.468Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:14:49.340Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:14:49.340Z] 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.
[2025-11-26T22:14:49.340Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:14:49.340Z] Top recommended movies for user id 72:
[2025-11-26T22:14:49.340Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:14:49.340Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:14:49.340Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:14:49.340Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:14:49.341Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:14:49.341Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (9338.588 ms) ======
[2025-11-26T22:14:49.341Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-26T22:14:49.341Z] GC before operation: completed in 63.017 ms, heap usage 473.329 MB -> 90.550 MB.
[2025-11-26T22:14:50.687Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:14:52.611Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:14:53.909Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:14:55.225Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:14:56.073Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:14:57.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:14:58.300Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:14:59.165Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:14:59.611Z] 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.
[2025-11-26T22:14:59.611Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:14:59.611Z] Top recommended movies for user id 72:
[2025-11-26T22:14:59.611Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:14:59.611Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:14:59.611Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:14:59.611Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:14:59.611Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:14:59.611Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9974.144 ms) ======
[2025-11-26T22:14:59.611Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-26T22:14:59.611Z] GC before operation: completed in 46.683 ms, heap usage 308.856 MB -> 90.493 MB.
[2025-11-26T22:15:00.435Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:01.871Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:02.858Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:03.726Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:04.140Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:05.035Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:05.417Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:05.826Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:06.253Z] 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.
[2025-11-26T22:15:06.253Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:06.253Z] Top recommended movies for user id 72:
[2025-11-26T22:15:06.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:06.253Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:06.253Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:06.253Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:06.253Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:06.253Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (6663.890 ms) ======
[2025-11-26T22:15:06.253Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-26T22:15:06.253Z] GC before operation: completed in 45.185 ms, heap usage 183.766 MB -> 90.237 MB.
[2025-11-26T22:15:07.067Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:08.520Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:09.590Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:09.998Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:10.838Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:11.214Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:12.025Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:12.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:12.836Z] 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.
[2025-11-26T22:15:12.836Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:12.836Z] Top recommended movies for user id 72:
[2025-11-26T22:15:12.836Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:12.836Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:12.836Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:12.836Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:12.836Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:12.836Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (6572.729 ms) ======
[2025-11-26T22:15:12.836Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-26T22:15:12.836Z] GC before operation: completed in 47.641 ms, heap usage 277.200 MB -> 90.481 MB.
[2025-11-26T22:15:13.628Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:15.009Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:15.864Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:17.209Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:17.607Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:18.947Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:20.392Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:21.239Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:21.239Z] 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.
[2025-11-26T22:15:21.239Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:21.239Z] Top recommended movies for user id 72:
[2025-11-26T22:15:21.239Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:21.239Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:21.239Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:21.239Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:21.239Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:21.239Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8520.511 ms) ======
[2025-11-26T22:15:21.239Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-26T22:15:21.239Z] GC before operation: completed in 69.703 ms, heap usage 245.768 MB -> 90.143 MB.
[2025-11-26T22:15:22.555Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:23.978Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:24.796Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:25.611Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:26.404Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:27.224Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:28.025Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:28.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:28.836Z] 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.
[2025-11-26T22:15:28.836Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:29.252Z] Top recommended movies for user id 72:
[2025-11-26T22:15:29.252Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:29.252Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:29.252Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:29.252Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:29.252Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:29.252Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (7685.192 ms) ======
[2025-11-26T22:15:29.252Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-26T22:15:29.252Z] GC before operation: completed in 57.668 ms, heap usage 118.103 MB -> 90.352 MB.
[2025-11-26T22:15:30.531Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:31.891Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:33.363Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:34.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:34.537Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:35.359Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:35.764Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:36.616Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:36.616Z] 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.
[2025-11-26T22:15:36.616Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:36.616Z] Top recommended movies for user id 72:
[2025-11-26T22:15:36.616Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:36.616Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:36.616Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:36.616Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:36.616Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:36.616Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7395.318 ms) ======
[2025-11-26T22:15:36.616Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-26T22:15:36.616Z] GC before operation: completed in 52.292 ms, heap usage 443.770 MB -> 90.857 MB.
[2025-11-26T22:15:37.435Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:38.822Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:39.671Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:40.531Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:41.541Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:41.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:43.048Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:43.428Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:43.428Z] 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.
[2025-11-26T22:15:43.428Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:43.428Z] Top recommended movies for user id 72:
[2025-11-26T22:15:43.428Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:43.428Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:43.428Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:43.428Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:43.428Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:43.428Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (6925.517 ms) ======
[2025-11-26T22:15:43.428Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-26T22:15:43.429Z] GC before operation: completed in 50.052 ms, heap usage 365.984 MB -> 90.515 MB.
[2025-11-26T22:15:44.859Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:45.704Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:46.530Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:47.492Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:48.372Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:48.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:49.303Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:50.317Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:50.317Z] 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.
[2025-11-26T22:15:50.317Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:50.317Z] Top recommended movies for user id 72:
[2025-11-26T22:15:50.317Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:50.317Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:50.317Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:50.317Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:50.317Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:50.317Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (6554.037 ms) ======
[2025-11-26T22:15:50.317Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-26T22:15:50.317Z] GC before operation: completed in 46.333 ms, heap usage 299.993 MB -> 90.611 MB.
[2025-11-26T22:15:51.169Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:15:52.010Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:15:54.183Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:15:55.235Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:15:55.628Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:15:56.570Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:15:57.489Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:15:58.351Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:15:58.352Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-26T22:15:58.352Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:15:58.352Z] Top recommended movies for user id 72:
[2025-11-26T22:15:58.352Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:15:58.352Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:15:58.352Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:15:58.352Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:15:58.352Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:15:58.352Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (7900.982 ms) ======
[2025-11-26T22:15:58.352Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-26T22:15:59.376Z] GC before operation: completed in 49.548 ms, heap usage 361.518 MB -> 90.701 MB.
[2025-11-26T22:15:59.376Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:16:01.077Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:16:02.970Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:16:04.526Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:16:05.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:16:06.322Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:16:07.195Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:16:08.137Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:16:08.137Z] 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.
[2025-11-26T22:16:08.547Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:16:08.547Z] Top recommended movies for user id 72:
[2025-11-26T22:16:08.547Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:16:08.547Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:16:08.547Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:16:08.547Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:16:08.547Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:16:08.547Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (10294.165 ms) ======
[2025-11-26T22:16:08.547Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-26T22:16:08.547Z] GC before operation: completed in 74.443 ms, heap usage 424.229 MB -> 90.791 MB.
[2025-11-26T22:16:09.996Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:16:11.466Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:16:12.905Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:16:14.552Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:16:14.973Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:16:15.408Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:16:16.454Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:16:16.844Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:16:17.257Z] 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.
[2025-11-26T22:16:17.257Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:16:17.257Z] Top recommended movies for user id 72:
[2025-11-26T22:16:17.257Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:16:17.257Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:16:17.257Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:16:17.257Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:16:17.257Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:16:17.257Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8642.905 ms) ======
[2025-11-26T22:16:17.257Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-26T22:16:17.257Z] GC before operation: completed in 52.064 ms, heap usage 303.418 MB -> 90.486 MB.
[2025-11-26T22:16:18.225Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:16:19.263Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:16:20.782Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:16:21.659Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:16:22.370Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:16:22.739Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:16:23.689Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:16:24.127Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:16:24.127Z] 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.
[2025-11-26T22:16:24.127Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:16:24.127Z] Top recommended movies for user id 72:
[2025-11-26T22:16:24.127Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:16:24.127Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:16:24.127Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:16:24.127Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:16:24.127Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:16:24.127Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (6962.198 ms) ======
[2025-11-26T22:16:24.127Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-26T22:16:24.127Z] GC before operation: completed in 47.107 ms, heap usage 200.192 MB -> 90.438 MB.
[2025-11-26T22:16:25.294Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-26T22:16:26.852Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-26T22:16:27.322Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-26T22:16:31.798Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-26T22:16:31.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-26T22:16:31.798Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-26T22:16:31.798Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-26T22:16:32.158Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-26T22:16:32.158Z] 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.
[2025-11-26T22:16:32.158Z] The best model improves the baseline by 14.52%.
[2025-11-26T22:16:32.158Z] Top recommended movies for user id 72:
[2025-11-26T22:16:32.158Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-26T22:16:32.158Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-26T22:16:32.158Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-26T22:16:32.158Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-26T22:16:32.158Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-26T22:16:32.158Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8115.259 ms) ======
[2025-11-26T22:16:32.554Z] -----------------------------------
[2025-11-26T22:16:32.554Z] renaissance-movie-lens_0_PASSED
[2025-11-26T22:16:32.554Z] -----------------------------------
[2025-11-26T22:16:32.554Z]
[2025-11-26T22:16:32.554Z] TEST TEARDOWN:
[2025-11-26T22:16:32.554Z] Nothing to be done for teardown.
[2025-11-26T22:16:32.554Z] renaissance-movie-lens_0 Finish Time: Wed Nov 26 17:16:32 2025 Epoch Time (ms): 1764195392403