[2025-12-24T23:54:21.464Z] Running test renaissance-movie-lens_0 ... [2025-12-24T23:54:21.464Z] =============================================== [2025-12-24T23:54:21.464Z] renaissance-movie-lens_0 Start Time: Wed Dec 24 23:54:19 2025 Epoch Time (ms): 1766620459942 [2025-12-24T23:54:21.464Z] variation: NoOptions [2025-12-24T23:54:21.464Z] JVM_OPTIONS: [2025-12-24T23:54:21.464Z] { \ [2025-12-24T23:54:21.464Z] echo ""; echo "TEST SETUP:"; \ [2025-12-24T23:54:21.464Z] echo "Nothing to be done for setup."; \ [2025-12-24T23:54:21.464Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17666147635981/renaissance-movie-lens_0"; \ [2025-12-24T23:54:21.464Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17666147635981/renaissance-movie-lens_0"; \ [2025-12-24T23:54:21.464Z] echo ""; echo "TESTING:"; \ [2025-12-24T23:54:21.465Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17666147635981/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-24T23:54:21.465Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17666147635981/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-24T23:54:21.465Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-24T23:54:21.465Z] echo "Nothing to be done for teardown."; \ [2025-12-24T23:54:21.465Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17666147635981/TestTargetResult"; [2025-12-24T23:54:21.465Z] [2025-12-24T23:54:21.465Z] TEST SETUP: [2025-12-24T23:54:21.465Z] Nothing to be done for setup. [2025-12-24T23:54:21.465Z] [2025-12-24T23:54:21.465Z] TESTING: [2025-12-24T23:54:44.676Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-24T23:55:18.127Z] 23:55:15.447 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-24T23:55:27.092Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-24T23:55:28.789Z] Training: 60056, validation: 20285, test: 19854 [2025-12-24T23:55:28.789Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-24T23:55:29.127Z] GC before operation: completed in 590.154 ms, heap usage 279.888 MB -> 75.988 MB. [2025-12-24T23:55:57.063Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:56:16.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:56:29.553Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:56:42.867Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:56:50.195Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:56:57.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:57:04.880Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:57:12.224Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:57:12.558Z] 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. [2025-12-24T23:57:12.894Z] The best model improves the baseline by 14.52%. [2025-12-24T23:57:14.068Z] Top recommended movies for user id 72: [2025-12-24T23:57:14.068Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-24T23:57:14.068Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-24T23:57:14.068Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-24T23:57:14.068Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-24T23:57:14.068Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-24T23:57:14.068Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (105104.786 ms) ====== [2025-12-24T23:57:14.068Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-24T23:57:15.270Z] GC before operation: completed in 891.683 ms, heap usage 184.422 MB -> 87.533 MB. [2025-12-24T23:57:28.522Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:57:37.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:57:50.694Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:58:01.648Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:58:07.608Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:58:13.566Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:58:19.514Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:58:25.513Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:58:26.693Z] 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. [2025-12-24T23:58:26.693Z] The best model improves the baseline by 14.52%. [2025-12-24T23:58:27.410Z] Top recommended movies for user id 72: [2025-12-24T23:58:27.410Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-24T23:58:27.410Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-24T23:58:27.410Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-24T23:58:27.410Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-24T23:58:27.410Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-24T23:58:27.410Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (72338.158 ms) ====== [2025-12-24T23:58:27.410Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-24T23:58:28.604Z] GC before operation: completed in 985.070 ms, heap usage 255.336 MB -> 88.995 MB. [2025-12-24T23:58:39.621Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:58:48.583Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:58:59.496Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:59:08.472Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:59:13.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:59:19.253Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:59:25.207Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:59:30.004Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:59:30.722Z] 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. [2025-12-24T23:59:31.058Z] The best model improves the baseline by 14.52%. [2025-12-24T23:59:31.784Z] Top recommended movies for user id 72: [2025-12-24T23:59:31.784Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-24T23:59:31.784Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-24T23:59:31.784Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-24T23:59:31.784Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-24T23:59:31.784Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-24T23:59:31.784Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63283.792 ms) ====== [2025-12-24T23:59:31.784Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-24T23:59:32.962Z] GC before operation: completed in 1032.369 ms, heap usage 376.200 MB -> 89.858 MB. [2025-12-24T23:59:41.910Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:59:52.901Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:00:01.886Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:00:10.878Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:00:16.833Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:00:22.777Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:00:28.834Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:00:34.789Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:00:35.505Z] 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. [2025-12-25T00:00:35.838Z] The best model improves the baseline by 14.52%. [2025-12-25T00:00:36.570Z] Top recommended movies for user id 72: [2025-12-25T00:00:36.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:00:36.570Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:00:36.570Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:00:36.570Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:00:36.570Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:00:36.570Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (63726.388 ms) ====== [2025-12-25T00:00:36.570Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-25T00:00:37.316Z] GC before operation: completed in 971.242 ms, heap usage 410.798 MB -> 90.041 MB. [2025-12-25T00:00:48.210Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:00:57.154Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:01:08.110Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:01:15.493Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:01:21.473Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:01:27.427Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:01:33.382Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:01:39.341Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:01:40.059Z] 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. [2025-12-25T00:01:40.059Z] The best model improves the baseline by 14.52%. [2025-12-25T00:01:40.824Z] Top recommended movies for user id 72: [2025-12-25T00:01:40.824Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:01:40.824Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:01:40.824Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:01:40.824Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:01:40.824Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:01:40.824Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (63230.543 ms) ====== [2025-12-25T00:01:40.824Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-25T00:01:41.596Z] GC before operation: completed in 984.370 ms, heap usage 430.063 MB -> 89.991 MB. [2025-12-25T00:01:52.500Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:01:59.855Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:02:10.801Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:02:18.208Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:02:24.315Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:02:29.114Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:02:36.486Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:02:41.312Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:02:42.475Z] 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. [2025-12-25T00:02:42.475Z] The best model improves the baseline by 14.52%. [2025-12-25T00:02:43.195Z] Top recommended movies for user id 72: [2025-12-25T00:02:43.195Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:02:43.195Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:02:43.195Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:02:43.195Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:02:43.195Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:02:43.195Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (61519.936 ms) ====== [2025-12-25T00:02:43.195Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-25T00:02:44.371Z] GC before operation: completed in 966.842 ms, heap usage 431.190 MB -> 90.343 MB. [2025-12-25T00:02:53.380Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:03:02.465Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:03:11.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:03:20.357Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:03:25.185Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:03:31.147Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:03:37.104Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:03:41.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:03:43.073Z] 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. [2025-12-25T00:03:43.073Z] The best model improves the baseline by 14.52%. [2025-12-25T00:03:43.797Z] Top recommended movies for user id 72: [2025-12-25T00:03:43.797Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:03:43.797Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:03:43.797Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:03:43.797Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:03:43.797Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:03:43.797Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (59568.082 ms) ====== [2025-12-25T00:03:43.797Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-25T00:03:44.538Z] GC before operation: completed in 951.870 ms, heap usage 399.680 MB -> 90.284 MB. [2025-12-25T00:03:53.476Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:04:04.357Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:04:11.761Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:04:20.699Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:04:25.495Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:04:31.494Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:04:36.305Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:04:42.275Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:04:42.275Z] 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. [2025-12-25T00:04:42.635Z] The best model improves the baseline by 14.52%. [2025-12-25T00:04:43.037Z] Top recommended movies for user id 72: [2025-12-25T00:04:43.037Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:04:43.037Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:04:43.037Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:04:43.037Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:04:43.037Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:04:43.037Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (58504.152 ms) ====== [2025-12-25T00:04:43.037Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-25T00:04:44.263Z] GC before operation: completed in 1006.214 ms, heap usage 463.772 MB -> 90.598 MB. [2025-12-25T00:04:53.220Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:05:00.539Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:05:09.503Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:05:18.440Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:05:23.332Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:05:29.264Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:05:35.207Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:05:39.996Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:05:40.726Z] 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. [2025-12-25T00:05:41.061Z] The best model improves the baseline by 14.52%. [2025-12-25T00:05:41.789Z] Top recommended movies for user id 72: [2025-12-25T00:05:41.789Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:05:41.789Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:05:41.789Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:05:41.789Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:05:41.789Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:05:41.789Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (57508.509 ms) ====== [2025-12-25T00:05:41.789Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-25T00:05:42.520Z] GC before operation: completed in 976.575 ms, heap usage 532.048 MB -> 90.562 MB. [2025-12-25T00:05:51.472Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:06:00.415Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:06:09.408Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:06:18.493Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:06:24.448Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:06:29.234Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:06:35.340Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:06:41.291Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:06:41.291Z] 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. [2025-12-25T00:06:41.630Z] The best model improves the baseline by 14.52%. [2025-12-25T00:06:42.397Z] Top recommended movies for user id 72: [2025-12-25T00:06:42.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:06:42.397Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:06:42.397Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:06:42.397Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:06:42.397Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:06:42.397Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (59616.576 ms) ====== [2025-12-25T00:06:42.397Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-25T00:06:43.132Z] GC before operation: completed in 966.159 ms, heap usage 210.012 MB -> 90.327 MB. [2025-12-25T00:06:52.070Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:07:01.019Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:07:09.956Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:07:19.042Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:07:23.853Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:07:29.802Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:07:34.613Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:07:40.584Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:07:40.920Z] 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. [2025-12-25T00:07:41.255Z] The best model improves the baseline by 14.52%. [2025-12-25T00:07:41.987Z] Top recommended movies for user id 72: [2025-12-25T00:07:41.987Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:07:41.987Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:07:41.987Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:07:41.987Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:07:41.987Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:07:41.987Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (58540.434 ms) ====== [2025-12-25T00:07:41.987Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-25T00:07:42.735Z] GC before operation: completed in 966.087 ms, heap usage 422.972 MB -> 90.305 MB. [2025-12-25T00:07:51.750Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:08:00.694Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:08:08.049Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:08:15.378Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:08:20.198Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:08:25.114Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:08:29.897Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:08:34.701Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:08:35.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-25T00:08:35.762Z] The best model improves the baseline by 14.52%. [2025-12-25T00:08:36.502Z] Top recommended movies for user id 72: [2025-12-25T00:08:36.502Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:08:36.502Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:08:36.502Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:08:36.502Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:08:36.502Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:08:36.502Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53645.925 ms) ====== [2025-12-25T00:08:36.502Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-25T00:08:37.244Z] GC before operation: completed in 973.046 ms, heap usage 208.086 MB -> 90.289 MB. [2025-12-25T00:08:46.206Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:08:53.956Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:09:02.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:09:10.286Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:09:15.098Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:09:21.034Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:09:25.818Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:09:30.606Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:09:31.324Z] 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. [2025-12-25T00:09:31.324Z] The best model improves the baseline by 14.52%. [2025-12-25T00:09:32.044Z] Top recommended movies for user id 72: [2025-12-25T00:09:32.044Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:09:32.044Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:09:32.044Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:09:32.044Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:09:32.044Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:09:32.044Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (54668.093 ms) ====== [2025-12-25T00:09:32.044Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-25T00:09:33.326Z] GC before operation: completed in 1036.125 ms, heap usage 253.617 MB -> 90.489 MB. [2025-12-25T00:09:42.342Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:09:49.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:09:58.720Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:10:06.028Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:10:10.871Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:10:15.795Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:10:20.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:10:25.446Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:10:25.446Z] 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. [2025-12-25T00:10:25.781Z] The best model improves the baseline by 14.52%. [2025-12-25T00:10:26.497Z] Top recommended movies for user id 72: [2025-12-25T00:10:26.497Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:10:26.497Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:10:26.497Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:10:26.497Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:10:26.497Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:10:26.497Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (53209.769 ms) ====== [2025-12-25T00:10:26.497Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-25T00:10:27.238Z] GC before operation: completed in 1021.701 ms, heap usage 790.255 MB -> 94.195 MB. [2025-12-25T00:10:36.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:10:43.506Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:10:52.611Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:10:59.929Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:11:04.712Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:11:09.533Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:11:14.331Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:11:19.141Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:11:20.301Z] 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. [2025-12-25T00:11:20.301Z] The best model improves the baseline by 14.52%. [2025-12-25T00:11:21.019Z] Top recommended movies for user id 72: [2025-12-25T00:11:21.019Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:11:21.019Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:11:21.019Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:11:21.019Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:11:21.019Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:11:21.019Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53624.057 ms) ====== [2025-12-25T00:11:21.019Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-25T00:11:22.241Z] GC before operation: completed in 1012.314 ms, heap usage 548.934 MB -> 90.948 MB. [2025-12-25T00:11:31.247Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:11:38.636Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:11:46.010Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:11:54.951Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:11:58.772Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:12:03.651Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:12:09.667Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:12:14.633Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:12:14.968Z] 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. [2025-12-25T00:12:14.968Z] The best model improves the baseline by 14.52%. [2025-12-25T00:12:15.397Z] Top recommended movies for user id 72: [2025-12-25T00:12:15.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:12:15.397Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:12:15.397Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:12:15.397Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:12:15.397Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:12:15.397Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (53566.516 ms) ====== [2025-12-25T00:12:15.397Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-25T00:12:16.595Z] GC before operation: completed in 1022.351 ms, heap usage 839.135 MB -> 94.554 MB. [2025-12-25T00:12:25.522Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:12:32.842Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:12:41.808Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:12:49.231Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:12:54.022Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:12:58.808Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:13:03.595Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:13:08.380Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:13:09.111Z] 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. [2025-12-25T00:13:09.111Z] The best model improves the baseline by 14.52%. [2025-12-25T00:13:09.831Z] Top recommended movies for user id 72: [2025-12-25T00:13:09.831Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:13:09.831Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:13:09.831Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:13:09.831Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:13:09.831Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:13:09.831Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (53217.474 ms) ====== [2025-12-25T00:13:09.831Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-25T00:13:11.013Z] GC before operation: completed in 993.197 ms, heap usage 204.896 MB -> 90.428 MB. [2025-12-25T00:13:20.131Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:13:27.505Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:13:34.821Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:13:43.761Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:13:47.567Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:13:52.370Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:13:57.402Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:14:02.196Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:14:02.915Z] 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. [2025-12-25T00:14:03.248Z] The best model improves the baseline by 14.52%. [2025-12-25T00:14:03.973Z] Top recommended movies for user id 72: [2025-12-25T00:14:03.973Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:14:03.974Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:14:03.974Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:14:03.974Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:14:03.974Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:14:03.974Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (53031.247 ms) ====== [2025-12-25T00:14:03.974Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-25T00:14:04.699Z] GC before operation: completed in 1055.552 ms, heap usage 769.594 MB -> 94.200 MB. [2025-12-25T00:14:13.661Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:14:21.066Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:14:30.009Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:14:37.388Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:14:41.203Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:14:46.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:14:51.968Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:14:56.764Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:14:57.102Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-25T00:14:57.102Z] The best model improves the baseline by 14.52%. [2025-12-25T00:14:58.277Z] Top recommended movies for user id 72: [2025-12-25T00:14:58.277Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:14:58.277Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:14:58.277Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:14:58.277Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:14:58.277Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:14:58.277Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53160.656 ms) ====== [2025-12-25T00:14:58.277Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-25T00:14:59.016Z] GC before operation: completed in 965.997 ms, heap usage 234.370 MB -> 90.374 MB. [2025-12-25T00:15:07.969Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:15:17.014Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:15:25.978Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:15:33.296Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:15:38.091Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:15:42.903Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:15:48.861Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:15:52.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:15:54.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-25T00:15:54.426Z] The best model improves the baseline by 14.52%. [2025-12-25T00:15:55.161Z] Top recommended movies for user id 72: [2025-12-25T00:15:55.161Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-25T00:15:55.161Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-25T00:15:55.161Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-25T00:15:55.161Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-25T00:15:55.161Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-25T00:15:55.161Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (56118.046 ms) ====== [2025-12-25T00:15:58.153Z] ----------------------------------- [2025-12-25T00:15:58.153Z] renaissance-movie-lens_0_PASSED [2025-12-25T00:15:58.153Z] ----------------------------------- [2025-12-25T00:15:58.153Z] [2025-12-25T00:15:58.153Z] TEST TEARDOWN: [2025-12-25T00:15:58.153Z] Nothing to be done for teardown. [2025-12-25T00:15:58.153Z] renaissance-movie-lens_0 Finish Time: Thu Dec 25 00:15:58 2025 Epoch Time (ms): 1766621758040