[2025-05-28T23:51:30.460Z] Running test renaissance-movie-lens_0 ... [2025-05-28T23:51:30.460Z] =============================================== [2025-05-28T23:51:30.460Z] renaissance-movie-lens_0 Start Time: Wed May 28 23:51:29 2025 Epoch Time (ms): 1748476289476 [2025-05-28T23:51:30.460Z] variation: NoOptions [2025-05-28T23:51:30.460Z] JVM_OPTIONS: [2025-05-28T23:51:30.460Z] { \ [2025-05-28T23:51:30.460Z] echo ""; echo "TEST SETUP:"; \ [2025-05-28T23:51:30.460Z] echo "Nothing to be done for setup."; \ [2025-05-28T23:51:30.460Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17484748485130/renaissance-movie-lens_0"; \ [2025-05-28T23:51:30.460Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17484748485130/renaissance-movie-lens_0"; \ [2025-05-28T23:51:30.460Z] echo ""; echo "TESTING:"; \ [2025-05-28T23:51:30.460Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_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_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17484748485130/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-28T23:51:30.460Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17484748485130/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-28T23:51:30.460Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-28T23:51:30.460Z] echo "Nothing to be done for teardown."; \ [2025-05-28T23:51:30.460Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17484748485130/TestTargetResult"; [2025-05-28T23:51:30.460Z] [2025-05-28T23:51:30.460Z] TEST SETUP: [2025-05-28T23:51:30.460Z] Nothing to be done for setup. [2025-05-28T23:51:30.460Z] [2025-05-28T23:51:30.460Z] TESTING: [2025-05-28T23:51:36.801Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-05-28T23:51:48.267Z] 23:51:46.383 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-05-28T23:51:50.240Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-28T23:51:50.628Z] Training: 60056, validation: 20285, test: 19854 [2025-05-28T23:51:50.628Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-28T23:51:50.628Z] GC before operation: completed in 131.275 ms, heap usage 356.916 MB -> 75.970 MB. [2025-05-28T23:52:00.454Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:52:05.843Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:52:10.174Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:52:14.353Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:52:16.273Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:52:18.858Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:52:20.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:52:23.274Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:52:23.274Z] 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. [2025-05-28T23:52:23.274Z] The best model improves the baseline by 14.52%. [2025-05-28T23:52:23.660Z] Top recommended movies for user id 72: [2025-05-28T23:52:23.660Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:52:23.660Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:52:23.660Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:52:23.660Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:52:23.660Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:52:23.660Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (32823.212 ms) ====== [2025-05-28T23:52:23.660Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-28T23:52:23.660Z] GC before operation: completed in 155.551 ms, heap usage 293.106 MB -> 97.837 MB. [2025-05-28T23:52:27.859Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:52:31.164Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:52:35.373Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:52:37.961Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:52:40.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:52:42.574Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:52:45.202Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:52:47.122Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:52:47.122Z] 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. [2025-05-28T23:52:47.122Z] The best model improves the baseline by 14.52%. [2025-05-28T23:52:47.515Z] Top recommended movies for user id 72: [2025-05-28T23:52:47.515Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:52:47.515Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:52:47.515Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:52:47.515Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:52:47.515Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:52:47.515Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23698.410 ms) ====== [2025-05-28T23:52:47.515Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-28T23:52:47.515Z] GC before operation: completed in 152.871 ms, heap usage 374.814 MB -> 88.911 MB. [2025-05-28T23:52:50.830Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:52:54.191Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:52:57.480Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:53:00.797Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:53:02.703Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:53:04.084Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:53:06.607Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:53:08.667Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:53:08.667Z] 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. [2025-05-28T23:53:08.667Z] The best model improves the baseline by 14.52%. [2025-05-28T23:53:09.049Z] Top recommended movies for user id 72: [2025-05-28T23:53:09.049Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:53:09.049Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:53:09.049Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:53:09.049Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:53:09.049Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:53:09.049Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21445.504 ms) ====== [2025-05-28T23:53:09.049Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-28T23:53:09.049Z] GC before operation: completed in 134.354 ms, heap usage 288.998 MB -> 89.587 MB. [2025-05-28T23:53:12.360Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:53:15.637Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:53:18.985Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:53:22.318Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:53:24.210Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:53:26.113Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:53:28.683Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:53:30.558Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:53:30.558Z] 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. [2025-05-28T23:53:30.558Z] The best model improves the baseline by 14.52%. [2025-05-28T23:53:30.936Z] Top recommended movies for user id 72: [2025-05-28T23:53:30.936Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:53:30.936Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:53:30.936Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:53:30.936Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:53:30.936Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:53:30.936Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21653.110 ms) ====== [2025-05-28T23:53:30.936Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-28T23:53:30.936Z] GC before operation: completed in 130.588 ms, heap usage 414.352 MB -> 89.877 MB. [2025-05-28T23:53:34.237Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:53:37.594Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:53:41.066Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:53:44.402Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:53:46.341Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:53:48.268Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:53:50.195Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:53:52.120Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:53:52.510Z] 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. [2025-05-28T23:53:52.510Z] The best model improves the baseline by 14.52%. [2025-05-28T23:53:52.926Z] Top recommended movies for user id 72: [2025-05-28T23:53:52.926Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:53:52.926Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:53:52.926Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:53:52.926Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:53:52.926Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:53:52.926Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21776.580 ms) ====== [2025-05-28T23:53:52.926Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-28T23:53:52.926Z] GC before operation: completed in 126.773 ms, heap usage 131.122 MB -> 89.541 MB. [2025-05-28T23:53:56.243Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:53:58.792Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:54:02.166Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:54:04.734Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:54:06.799Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:54:08.124Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:54:10.021Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:54:11.941Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:54:11.942Z] 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. [2025-05-28T23:54:11.942Z] The best model improves the baseline by 14.52%. [2025-05-28T23:54:12.346Z] Top recommended movies for user id 72: [2025-05-28T23:54:12.346Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:54:12.346Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:54:12.346Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:54:12.346Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:54:12.346Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:54:12.346Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19256.302 ms) ====== [2025-05-28T23:54:12.346Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-28T23:54:12.346Z] GC before operation: completed in 131.586 ms, heap usage 210.796 MB -> 89.981 MB. [2025-05-28T23:54:15.744Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:54:18.270Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:54:20.880Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:54:24.207Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:54:25.526Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:54:27.440Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:54:28.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:54:30.732Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:54:30.732Z] 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. [2025-05-28T23:54:31.127Z] The best model improves the baseline by 14.52%. [2025-05-28T23:54:31.127Z] Top recommended movies for user id 72: [2025-05-28T23:54:31.127Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:54:31.127Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:54:31.127Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:54:31.127Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:54:31.127Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:54:31.127Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18849.629 ms) ====== [2025-05-28T23:54:31.127Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-28T23:54:31.127Z] GC before operation: completed in 139.428 ms, heap usage 774.149 MB -> 94.010 MB. [2025-05-28T23:54:34.427Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:54:37.364Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:54:40.646Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:54:43.243Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:54:44.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:54:46.462Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:54:48.370Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:54:50.928Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:54:50.928Z] 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. [2025-05-28T23:54:50.928Z] The best model improves the baseline by 14.52%. [2025-05-28T23:54:50.928Z] Top recommended movies for user id 72: [2025-05-28T23:54:50.929Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:54:50.929Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:54:50.929Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:54:50.929Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:54:50.929Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:54:50.929Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19747.910 ms) ====== [2025-05-28T23:54:50.929Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-28T23:54:51.313Z] GC before operation: completed in 126.587 ms, heap usage 339.355 MB -> 90.249 MB. [2025-05-28T23:54:54.709Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:54:57.271Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:55:00.556Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:55:03.093Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:55:04.981Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:55:07.006Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:55:08.880Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:55:10.801Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:55:10.801Z] 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. [2025-05-28T23:55:11.190Z] The best model improves the baseline by 14.52%. [2025-05-28T23:55:11.190Z] Top recommended movies for user id 72: [2025-05-28T23:55:11.190Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:55:11.190Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:55:11.190Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:55:11.190Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:55:11.190Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:55:11.190Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20204.080 ms) ====== [2025-05-28T23:55:11.190Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-28T23:55:11.583Z] GC before operation: completed in 131.141 ms, heap usage 249.240 MB -> 90.023 MB. [2025-05-28T23:55:14.892Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:55:17.453Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:55:20.780Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:55:23.364Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:55:25.227Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:55:27.140Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:55:29.024Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:55:31.030Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:55:31.453Z] 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. [2025-05-28T23:55:31.453Z] The best model improves the baseline by 14.52%. [2025-05-28T23:55:31.453Z] Top recommended movies for user id 72: [2025-05-28T23:55:31.453Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:55:31.453Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:55:31.453Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:55:31.453Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:55:31.453Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:55:31.453Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20055.141 ms) ====== [2025-05-28T23:55:31.453Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-28T23:55:31.830Z] GC before operation: completed in 131.237 ms, heap usage 386.244 MB -> 90.434 MB. [2025-05-28T23:55:35.106Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:55:37.769Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:55:41.062Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:55:43.637Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:55:45.552Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:55:48.084Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:55:49.396Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:55:51.347Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:55:51.737Z] 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. [2025-05-28T23:55:51.737Z] The best model improves the baseline by 14.52%. [2025-05-28T23:55:52.126Z] Top recommended movies for user id 72: [2025-05-28T23:55:52.126Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:55:52.126Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:55:52.126Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:55:52.126Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:55:52.126Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:55:52.126Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20320.323 ms) ====== [2025-05-28T23:55:52.126Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-28T23:55:52.126Z] GC before operation: completed in 142.155 ms, heap usage 509.990 MB -> 90.363 MB. [2025-05-28T23:55:55.425Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:55:58.013Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:56:01.326Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:56:04.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:56:06.014Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:56:07.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:56:09.847Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:56:11.782Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:56:12.200Z] 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. [2025-05-28T23:56:12.200Z] The best model improves the baseline by 14.52%. [2025-05-28T23:56:12.200Z] Top recommended movies for user id 72: [2025-05-28T23:56:12.200Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:56:12.200Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:56:12.200Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:56:12.200Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:56:12.200Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:56:12.200Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20154.577 ms) ====== [2025-05-28T23:56:12.200Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-28T23:56:12.599Z] GC before operation: completed in 133.031 ms, heap usage 142.795 MB -> 89.985 MB. [2025-05-28T23:56:15.976Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:56:18.540Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:56:21.826Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:56:24.413Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:56:26.385Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:56:28.288Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:56:30.200Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:56:32.160Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:56:32.553Z] 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. [2025-05-28T23:56:32.553Z] The best model improves the baseline by 14.52%. [2025-05-28T23:56:32.553Z] Top recommended movies for user id 72: [2025-05-28T23:56:32.553Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:56:32.553Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:56:32.553Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:56:32.553Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:56:32.553Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:56:32.553Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20251.501 ms) ====== [2025-05-28T23:56:32.553Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-28T23:56:32.950Z] GC before operation: completed in 134.895 ms, heap usage 288.527 MB -> 90.367 MB. [2025-05-28T23:56:36.294Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:56:38.834Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:56:42.099Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:56:44.651Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:56:46.572Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:56:47.949Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:56:49.808Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:56:51.730Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:56:51.730Z] 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. [2025-05-28T23:56:51.730Z] The best model improves the baseline by 14.52%. [2025-05-28T23:56:52.135Z] Top recommended movies for user id 72: [2025-05-28T23:56:52.135Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:56:52.135Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:56:52.135Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:56:52.135Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:56:52.135Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:56:52.135Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19131.044 ms) ====== [2025-05-28T23:56:52.135Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-28T23:56:52.135Z] GC before operation: completed in 134.702 ms, heap usage 201.548 MB -> 90.039 MB. [2025-05-28T23:56:55.467Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:56:58.003Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:57:00.579Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:57:03.918Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:57:05.249Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:57:07.129Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:57:09.021Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:57:10.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:57:11.309Z] 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. [2025-05-28T23:57:11.309Z] The best model improves the baseline by 14.52%. [2025-05-28T23:57:11.309Z] Top recommended movies for user id 72: [2025-05-28T23:57:11.309Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:57:11.309Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:57:11.309Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:57:11.309Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:57:11.309Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:57:11.309Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19363.366 ms) ====== [2025-05-28T23:57:11.309Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-28T23:57:11.696Z] GC before operation: completed in 126.621 ms, heap usage 380.018 MB -> 90.546 MB. [2025-05-28T23:57:14.264Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:57:17.588Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:57:20.298Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:57:23.590Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:57:25.477Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:57:26.822Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:57:29.394Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:57:30.814Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:57:31.198Z] 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. [2025-05-28T23:57:31.199Z] The best model improves the baseline by 14.52%. [2025-05-28T23:57:31.199Z] Top recommended movies for user id 72: [2025-05-28T23:57:31.199Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:57:31.199Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:57:31.199Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:57:31.199Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:57:31.199Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:57:31.199Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19801.653 ms) ====== [2025-05-28T23:57:31.199Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-28T23:57:31.639Z] GC before operation: completed in 142.277 ms, heap usage 294.200 MB -> 90.323 MB. [2025-05-28T23:57:34.926Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:57:37.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:57:40.907Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:57:43.443Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:57:45.367Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:57:47.268Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:57:49.244Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:57:51.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:57:51.176Z] 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. [2025-05-28T23:57:51.176Z] The best model improves the baseline by 14.52%. [2025-05-28T23:57:51.176Z] Top recommended movies for user id 72: [2025-05-28T23:57:51.176Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:57:51.176Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:57:51.176Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:57:51.176Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:57:51.176Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:57:51.176Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19787.178 ms) ====== [2025-05-28T23:57:51.176Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-28T23:57:51.571Z] GC before operation: completed in 133.529 ms, heap usage 445.980 MB -> 90.550 MB. [2025-05-28T23:57:54.092Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:57:57.422Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:58:00.851Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:58:03.377Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:58:05.249Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:58:07.177Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:58:09.100Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:58:10.431Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:58:10.826Z] 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. [2025-05-28T23:58:10.826Z] The best model improves the baseline by 14.52%. [2025-05-28T23:58:11.204Z] Top recommended movies for user id 72: [2025-05-28T23:58:11.204Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:58:11.204Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:58:11.204Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:58:11.204Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:58:11.204Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:58:11.204Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19691.506 ms) ====== [2025-05-28T23:58:11.204Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-28T23:58:11.204Z] GC before operation: completed in 138.348 ms, heap usage 505.030 MB -> 90.509 MB. [2025-05-28T23:58:14.637Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:58:17.218Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:58:20.566Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:58:23.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:58:25.047Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:58:26.958Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:58:28.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:58:30.789Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:58:30.789Z] 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. [2025-05-28T23:58:30.789Z] The best model improves the baseline by 14.52%. [2025-05-28T23:58:31.167Z] Top recommended movies for user id 72: [2025-05-28T23:58:31.167Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:58:31.167Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:58:31.167Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:58:31.167Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:58:31.167Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:58:31.167Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19860.455 ms) ====== [2025-05-28T23:58:31.167Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-28T23:58:31.167Z] GC before operation: completed in 131.215 ms, heap usage 371.354 MB -> 90.459 MB. [2025-05-28T23:58:34.500Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:58:37.823Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:58:40.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:58:43.776Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:58:45.096Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:58:47.120Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:58:48.990Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:58:50.892Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:58:50.893Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:58:51.274Z] The best model improves the baseline by 14.52%. [2025-05-28T23:58:51.274Z] Top recommended movies for user id 72: [2025-05-28T23:58:51.274Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:58:51.274Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:58:51.274Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:58:51.274Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:58:51.274Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:58:51.274Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (20076.109 ms) ====== [2025-05-28T23:58:52.117Z] ----------------------------------- [2025-05-28T23:58:52.117Z] renaissance-movie-lens_0_PASSED [2025-05-28T23:58:52.117Z] ----------------------------------- [2025-05-28T23:58:52.117Z] [2025-05-28T23:58:52.117Z] TEST TEARDOWN: [2025-05-28T23:58:52.117Z] Nothing to be done for teardown. [2025-05-28T23:58:52.118Z] renaissance-movie-lens_0 Finish Time: Wed May 28 23:58:51 2025 Epoch Time (ms): 1748476731874