[2025-06-12T20:14:37.325Z] Running test renaissance-movie-lens_0 ... [2025-06-12T20:14:37.325Z] =============================================== [2025-06-12T20:14:37.325Z] renaissance-movie-lens_0 Start Time: Thu Jun 12 20:14:35 2025 Epoch Time (ms): 1749759275381 [2025-06-12T20:14:37.325Z] variation: NoOptions [2025-06-12T20:14:37.325Z] JVM_OPTIONS: [2025-06-12T20:14:37.325Z] { \ [2025-06-12T20:14:37.325Z] echo ""; echo "TEST SETUP:"; \ [2025-06-12T20:14:37.325Z] echo "Nothing to be done for setup."; \ [2025-06-12T20:14:37.325Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17497568542689/renaissance-movie-lens_0"; \ [2025-06-12T20:14:37.325Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17497568542689/renaissance-movie-lens_0"; \ [2025-06-12T20:14:37.325Z] echo ""; echo "TESTING:"; \ [2025-06-12T20:14:37.325Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17497568542689/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-12T20:14:37.325Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17497568542689/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-12T20:14:37.325Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-12T20:14:37.325Z] echo "Nothing to be done for teardown."; \ [2025-06-12T20:14:37.325Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17497568542689/TestTargetResult"; [2025-06-12T20:14:37.325Z] [2025-06-12T20:14:37.325Z] TEST SETUP: [2025-06-12T20:14:37.325Z] Nothing to be done for setup. [2025-06-12T20:14:37.325Z] [2025-06-12T20:14:37.325Z] TESTING: [2025-06-12T20:14:49.157Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-12T20:15:08.167Z] 20:15:06.720 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-12T20:15:15.137Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-12T20:15:16.756Z] Training: 60056, validation: 20285, test: 19854 [2025-06-12T20:15:16.756Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-12T20:15:16.756Z] GC before operation: completed in 433.880 ms, heap usage 248.041 MB -> 75.649 MB. [2025-06-12T20:15:46.643Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:16:01.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:16:11.820Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:16:22.265Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:16:27.055Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:16:30.749Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:16:36.115Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:16:39.797Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:16:39.797Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-12T20:16:39.797Z] The best model improves the baseline by 14.52%. [2025-06-12T20:16:40.623Z] Top recommended movies for user id 72: [2025-06-12T20:16:40.624Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:16:40.624Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:16:40.624Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:16:40.624Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:16:40.624Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:16:40.624Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (83899.389 ms) ====== [2025-06-12T20:16:40.624Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-12T20:16:41.457Z] GC before operation: completed in 345.663 ms, heap usage 686.490 MB -> 97.739 MB. [2025-06-12T20:16:48.709Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:16:56.023Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:17:03.305Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:17:09.297Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:17:11.955Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:17:16.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:17:20.404Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:17:23.608Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:17:24.437Z] 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. [2025-06-12T20:17:24.437Z] The best model improves the baseline by 14.52%. [2025-06-12T20:17:24.437Z] Top recommended movies for user id 72: [2025-06-12T20:17:24.437Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:17:24.437Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:17:24.437Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:17:24.437Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:17:24.437Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:17:24.437Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (43392.448 ms) ====== [2025-06-12T20:17:24.437Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-12T20:17:24.437Z] GC before operation: completed in 261.017 ms, heap usage 424.389 MB -> 90.892 MB. [2025-06-12T20:17:31.757Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:17:39.011Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:17:44.971Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:17:50.951Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:17:53.586Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:17:57.229Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:18:02.028Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:18:05.676Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:18:06.505Z] 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. [2025-06-12T20:18:06.505Z] The best model improves the baseline by 14.52%. [2025-06-12T20:18:07.340Z] Top recommended movies for user id 72: [2025-06-12T20:18:07.340Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:18:07.340Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:18:07.340Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:18:07.340Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:18:07.340Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:18:07.340Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (42223.745 ms) ====== [2025-06-12T20:18:07.340Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-12T20:18:07.340Z] GC before operation: completed in 281.826 ms, heap usage 361.572 MB -> 91.539 MB. [2025-06-12T20:18:16.717Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:18:23.985Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:18:29.934Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:18:37.218Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:18:40.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:18:44.462Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:18:48.085Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:18:51.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:18:52.561Z] 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. [2025-06-12T20:18:52.561Z] The best model improves the baseline by 14.52%. [2025-06-12T20:18:53.385Z] Top recommended movies for user id 72: [2025-06-12T20:18:53.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:18:53.385Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:18:53.385Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:18:53.385Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:18:53.385Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:18:53.385Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (45743.846 ms) ====== [2025-06-12T20:18:53.385Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-12T20:18:53.385Z] GC before operation: completed in 366.293 ms, heap usage 176.363 MB -> 92.976 MB. [2025-06-12T20:19:00.624Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:19:05.949Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:19:13.202Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:19:19.186Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:19:22.981Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:19:26.625Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:19:30.267Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:19:32.908Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:19:33.735Z] 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. [2025-06-12T20:19:33.735Z] The best model improves the baseline by 14.52%. [2025-06-12T20:19:33.735Z] Top recommended movies for user id 72: [2025-06-12T20:19:33.735Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:19:33.735Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:19:33.735Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:19:33.735Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:19:33.735Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:19:33.735Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (40630.404 ms) ====== [2025-06-12T20:19:33.735Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-12T20:19:34.564Z] GC before operation: completed in 281.399 ms, heap usage 272.005 MB -> 89.474 MB. [2025-06-12T20:19:40.526Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:19:46.449Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:19:52.940Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:19:58.898Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:20:01.540Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:20:05.189Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:20:08.875Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:20:12.513Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:20:13.339Z] 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. [2025-06-12T20:20:13.339Z] The best model improves the baseline by 14.52%. [2025-06-12T20:20:14.178Z] Top recommended movies for user id 72: [2025-06-12T20:20:14.178Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:20:14.178Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:20:14.178Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:20:14.178Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:20:14.178Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:20:14.178Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (39620.329 ms) ====== [2025-06-12T20:20:14.178Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-12T20:20:14.178Z] GC before operation: completed in 360.866 ms, heap usage 238.183 MB -> 89.632 MB. [2025-06-12T20:20:20.170Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:20:26.133Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:20:32.061Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:20:38.037Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:20:41.172Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:20:45.644Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:20:50.103Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:20:54.554Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:20:54.554Z] 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. [2025-06-12T20:20:54.554Z] The best model improves the baseline by 14.52%. [2025-06-12T20:20:55.317Z] Top recommended movies for user id 72: [2025-06-12T20:20:55.317Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:20:55.317Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:20:55.317Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:20:55.317Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:20:55.317Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:20:55.317Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (40962.979 ms) ====== [2025-06-12T20:20:55.317Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-12T20:20:55.318Z] GC before operation: completed in 350.817 ms, heap usage 492.638 MB -> 90.036 MB. [2025-06-12T20:21:02.171Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:21:07.732Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:21:14.588Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:21:21.414Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:21:24.823Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:21:28.736Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:21:32.161Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:21:35.539Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:21:36.302Z] 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. [2025-06-12T20:21:36.302Z] The best model improves the baseline by 14.52%. [2025-06-12T20:21:36.302Z] Top recommended movies for user id 72: [2025-06-12T20:21:36.302Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:21:36.302Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:21:36.302Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:21:36.302Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:21:36.302Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:21:36.302Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (40884.704 ms) ====== [2025-06-12T20:21:36.302Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-12T20:21:37.091Z] GC before operation: completed in 343.858 ms, heap usage 430.692 MB -> 90.235 MB. [2025-06-12T20:21:42.653Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:21:50.882Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:21:56.449Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:22:02.082Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:22:06.534Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:22:09.945Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:22:14.358Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:22:19.339Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:22:19.339Z] 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. [2025-06-12T20:22:19.339Z] The best model improves the baseline by 14.52%. [2025-06-12T20:22:20.111Z] Top recommended movies for user id 72: [2025-06-12T20:22:20.111Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:22:20.111Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:22:20.111Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:22:20.111Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:22:20.111Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:22:20.111Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (43149.067 ms) ====== [2025-06-12T20:22:20.111Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-12T20:22:20.111Z] GC before operation: completed in 322.393 ms, heap usage 678.302 MB -> 93.586 MB. [2025-06-12T20:22:26.962Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:22:32.590Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:22:39.441Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:22:45.069Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:22:49.542Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:22:52.960Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:22:57.462Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:23:01.055Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:23:01.825Z] 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. [2025-06-12T20:23:01.825Z] The best model improves the baseline by 14.52%. [2025-06-12T20:23:01.825Z] Top recommended movies for user id 72: [2025-06-12T20:23:01.825Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:23:01.825Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:23:01.825Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:23:01.825Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:23:01.825Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:23:01.825Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (41802.153 ms) ====== [2025-06-12T20:23:01.825Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-12T20:23:02.593Z] GC before operation: completed in 309.729 ms, heap usage 301.852 MB -> 92.352 MB. [2025-06-12T20:23:10.871Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:23:19.111Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:23:27.427Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:23:39.403Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:23:43.853Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:23:47.261Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:23:51.728Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:23:55.652Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:23:56.419Z] 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. [2025-06-12T20:23:56.419Z] The best model improves the baseline by 14.52%. [2025-06-12T20:23:56.419Z] Top recommended movies for user id 72: [2025-06-12T20:23:56.419Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:23:56.419Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:23:56.419Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:23:56.419Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:23:56.419Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:23:56.419Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54114.940 ms) ====== [2025-06-12T20:23:56.419Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-12T20:23:56.419Z] GC before operation: completed in 229.396 ms, heap usage 289.768 MB -> 95.305 MB. [2025-06-12T20:24:08.017Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:24:14.846Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:24:21.808Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:24:28.778Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:24:33.233Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:24:37.715Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:24:42.701Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:24:46.098Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:24:46.861Z] 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. [2025-06-12T20:24:46.861Z] The best model improves the baseline by 14.52%. [2025-06-12T20:24:47.632Z] Top recommended movies for user id 72: [2025-06-12T20:24:47.633Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:24:47.633Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:24:47.633Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:24:47.633Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:24:47.633Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:24:47.633Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (50791.469 ms) ====== [2025-06-12T20:24:47.633Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-12T20:24:47.633Z] GC before operation: completed in 372.583 ms, heap usage 203.197 MB -> 95.571 MB. [2025-06-12T20:24:54.488Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:25:01.370Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:25:06.957Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:25:12.525Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:25:15.947Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:25:20.421Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:25:24.930Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:25:28.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:25:29.680Z] 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. [2025-06-12T20:25:29.680Z] The best model improves the baseline by 14.52%. [2025-06-12T20:25:29.680Z] Top recommended movies for user id 72: [2025-06-12T20:25:29.680Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:25:29.680Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:25:29.680Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:25:29.680Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:25:29.680Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:25:29.680Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42024.980 ms) ====== [2025-06-12T20:25:29.680Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-12T20:25:30.445Z] GC before operation: completed in 409.708 ms, heap usage 221.999 MB -> 93.376 MB. [2025-06-12T20:25:38.668Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:25:45.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:25:52.328Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:25:59.187Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:26:03.703Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:26:07.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:26:11.583Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:26:16.059Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:26:16.060Z] 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. [2025-06-12T20:26:16.060Z] The best model improves the baseline by 14.52%. [2025-06-12T20:26:16.822Z] Top recommended movies for user id 72: [2025-06-12T20:26:16.822Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:26:16.822Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:26:16.822Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:26:16.822Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:26:16.822Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:26:16.822Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (46325.036 ms) ====== [2025-06-12T20:26:16.822Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-12T20:26:16.822Z] GC before operation: completed in 367.248 ms, heap usage 437.752 MB -> 90.226 MB. [2025-06-12T20:26:24.200Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:26:31.071Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:26:36.644Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:26:43.507Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:26:46.927Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:26:50.333Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:26:53.714Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:26:57.112Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:26:57.876Z] 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. [2025-06-12T20:26:57.876Z] The best model improves the baseline by 14.52%. [2025-06-12T20:26:57.876Z] Top recommended movies for user id 72: [2025-06-12T20:26:57.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:26:57.877Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:26:57.877Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:26:57.877Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:26:57.877Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:26:57.877Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (41168.535 ms) ====== [2025-06-12T20:26:57.877Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-12T20:26:58.634Z] GC before operation: completed in 286.750 ms, heap usage 253.979 MB -> 90.150 MB. [2025-06-12T20:27:05.688Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:27:10.400Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:27:17.190Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:27:22.787Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:27:27.485Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:27:29.944Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:27:34.396Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:27:37.815Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:27:38.571Z] 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. [2025-06-12T20:27:39.349Z] The best model improves the baseline by 14.52%. [2025-06-12T20:27:39.349Z] Top recommended movies for user id 72: [2025-06-12T20:27:39.349Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:27:39.349Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:27:39.349Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:27:39.349Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:27:39.349Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:27:39.349Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (40818.877 ms) ====== [2025-06-12T20:27:39.349Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-12T20:27:39.349Z] GC before operation: completed in 321.443 ms, heap usage 357.382 MB -> 90.204 MB. [2025-06-12T20:27:46.191Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:27:50.674Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:27:56.882Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:28:02.450Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:28:04.992Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:28:08.404Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:28:11.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:28:15.326Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:28:16.104Z] 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. [2025-06-12T20:28:16.104Z] The best model improves the baseline by 14.52%. [2025-06-12T20:28:16.104Z] Top recommended movies for user id 72: [2025-06-12T20:28:16.104Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:28:16.104Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:28:16.104Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:28:16.104Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:28:16.104Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:28:16.104Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (36350.332 ms) ====== [2025-06-12T20:28:16.104Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-12T20:28:16.104Z] GC before operation: completed in 286.851 ms, heap usage 396.704 MB -> 92.820 MB. [2025-06-12T20:28:24.371Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:28:29.967Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:28:36.844Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:28:41.787Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:28:45.184Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:28:48.567Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:28:53.015Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:28:55.465Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:28:56.223Z] 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. [2025-06-12T20:28:56.223Z] The best model improves the baseline by 14.52%. [2025-06-12T20:28:56.223Z] Top recommended movies for user id 72: [2025-06-12T20:28:56.223Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:28:56.223Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:28:56.223Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:28:56.223Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:28:56.223Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:28:56.223Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (40244.972 ms) ====== [2025-06-12T20:28:56.223Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-12T20:28:56.991Z] GC before operation: completed in 357.503 ms, heap usage 376.523 MB -> 93.657 MB. [2025-06-12T20:29:02.562Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:29:07.006Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:29:12.612Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:29:18.237Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:29:20.703Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:29:23.801Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:29:27.180Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:29:30.579Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:29:31.355Z] 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. [2025-06-12T20:29:31.355Z] The best model improves the baseline by 14.52%. [2025-06-12T20:29:31.355Z] Top recommended movies for user id 72: [2025-06-12T20:29:31.355Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:29:31.355Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:29:31.355Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:29:31.355Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:29:31.355Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:29:31.355Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (34367.417 ms) ====== [2025-06-12T20:29:31.355Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-12T20:29:31.355Z] GC before operation: completed in 296.112 ms, heap usage 243.409 MB -> 91.890 MB. [2025-06-12T20:29:38.160Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T20:29:42.640Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T20:29:48.169Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T20:29:52.595Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T20:29:56.002Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T20:29:58.471Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T20:30:01.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T20:30:04.336Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T20:30:05.103Z] 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. [2025-06-12T20:30:05.103Z] The best model improves the baseline by 14.52%. [2025-06-12T20:30:05.859Z] Top recommended movies for user id 72: [2025-06-12T20:30:05.859Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T20:30:05.859Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T20:30:05.859Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T20:30:05.859Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T20:30:05.859Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T20:30:05.859Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (33902.691 ms) ====== [2025-06-12T20:30:06.623Z] ----------------------------------- [2025-06-12T20:30:06.623Z] renaissance-movie-lens_0_PASSED [2025-06-12T20:30:06.623Z] ----------------------------------- [2025-06-12T20:30:06.623Z] [2025-06-12T20:30:06.623Z] TEST TEARDOWN: [2025-06-12T20:30:06.623Z] Nothing to be done for teardown. [2025-06-12T20:30:06.623Z] renaissance-movie-lens_0 Finish Time: Thu Jun 12 20:30:06 2025 Epoch Time (ms): 1749760206090