[2025-08-29T12:27:25.233Z] Running test renaissance-movie-lens_0 ... [2025-08-29T12:27:25.233Z] =============================================== [2025-08-29T12:27:25.233Z] renaissance-movie-lens_0 Start Time: Fri Aug 29 12:27:24 2025 Epoch Time (ms): 1756470444532 [2025-08-29T12:27:25.233Z] variation: NoOptions [2025-08-29T12:27:25.233Z] JVM_OPTIONS: [2025-08-29T12:27:25.233Z] { \ [2025-08-29T12:27:25.233Z] echo ""; echo "TEST SETUP:"; \ [2025-08-29T12:27:25.233Z] echo "Nothing to be done for setup."; \ [2025-08-29T12:27:25.233Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1756468806605/renaissance-movie-lens_0"; \ [2025-08-29T12:27:25.233Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1756468806605/renaissance-movie-lens_0"; \ [2025-08-29T12:27:25.233Z] echo ""; echo "TESTING:"; \ [2025-08-29T12:27:25.233Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_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_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1756468806605/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-08-29T12:27:25.233Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1756468806605/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-08-29T12:27:25.233Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-08-29T12:27:25.233Z] echo "Nothing to be done for teardown."; \ [2025-08-29T12:27:25.233Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1756468806605/TestTargetResult"; [2025-08-29T12:27:25.233Z] [2025-08-29T12:27:25.233Z] TEST SETUP: [2025-08-29T12:27:25.233Z] Nothing to be done for setup. [2025-08-29T12:27:25.233Z] [2025-08-29T12:27:25.233Z] TESTING: [2025-08-29T12:27:30.633Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-08-29T12:27:38.819Z] 12:27:38.469 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-08-29T12:27:40.782Z] Got 100004 ratings from 671 users on 9066 movies. [2025-08-29T12:27:41.741Z] Training: 60056, validation: 20285, test: 19854 [2025-08-29T12:27:41.741Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-08-29T12:27:41.741Z] GC before operation: completed in 154.663 ms, heap usage 257.268 MB -> 74.394 MB. [2025-08-29T12:27:47.870Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:27:52.042Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:27:55.077Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:27:58.110Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:28:00.084Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:28:02.046Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:28:04.017Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:28:05.990Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:28:06.946Z] 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. [2025-08-29T12:28:06.946Z] The best model improves the baseline by 14.52%. [2025-08-29T12:28:06.946Z] Top recommended movies for user id 72: [2025-08-29T12:28:06.946Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:28:06.946Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:28:06.946Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:28:06.946Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:28:06.946Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:28:06.946Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25131.382 ms) ====== [2025-08-29T12:28:06.946Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-08-29T12:28:06.946Z] GC before operation: completed in 168.535 ms, heap usage 410.584 MB -> 85.626 MB. [2025-08-29T12:28:09.989Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:28:14.157Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:28:17.189Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:28:20.223Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:28:22.191Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:28:24.242Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:28:26.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:28:28.175Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:28:28.175Z] 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. [2025-08-29T12:28:28.175Z] The best model improves the baseline by 14.52%. [2025-08-29T12:28:28.175Z] Top recommended movies for user id 72: [2025-08-29T12:28:28.175Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:28:28.175Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:28:28.175Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:28:28.175Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:28:28.175Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:28:28.175Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21309.795 ms) ====== [2025-08-29T12:28:28.175Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-08-29T12:28:28.175Z] GC before operation: completed in 182.992 ms, heap usage 337.323 MB -> 87.637 MB. [2025-08-29T12:28:32.351Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:28:35.379Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:28:38.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:28:42.155Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:28:43.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:28:45.082Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:28:47.068Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:28:49.032Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:28:49.033Z] 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. [2025-08-29T12:28:49.033Z] The best model improves the baseline by 14.52%. [2025-08-29T12:28:49.033Z] Top recommended movies for user id 72: [2025-08-29T12:28:49.033Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:28:49.033Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:28:49.033Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:28:49.033Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:28:49.033Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:28:49.033Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20666.225 ms) ====== [2025-08-29T12:28:49.033Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-08-29T12:28:49.033Z] GC before operation: completed in 167.561 ms, heap usage 462.771 MB -> 88.458 MB. [2025-08-29T12:28:52.064Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:28:55.096Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:28:58.129Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:29:01.164Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:29:03.131Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:29:05.096Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:29:07.057Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:29:09.021Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:29:09.021Z] 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. [2025-08-29T12:29:09.021Z] The best model improves the baseline by 14.52%. [2025-08-29T12:29:09.021Z] Top recommended movies for user id 72: [2025-08-29T12:29:09.021Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:29:09.021Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:29:09.021Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:29:09.021Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:29:09.021Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:29:09.021Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19815.069 ms) ====== [2025-08-29T12:29:09.021Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-08-29T12:29:09.021Z] GC before operation: completed in 156.722 ms, heap usage 455.958 MB -> 88.740 MB. [2025-08-29T12:29:12.058Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:29:15.095Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:29:18.150Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:29:21.177Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:29:23.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:29:25.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:29:27.217Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:29:28.174Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:29:29.134Z] 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. [2025-08-29T12:29:29.134Z] The best model improves the baseline by 14.52%. [2025-08-29T12:29:29.134Z] Top recommended movies for user id 72: [2025-08-29T12:29:29.134Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:29:29.134Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:29:29.134Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:29:29.134Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:29:29.134Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:29:29.134Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19426.570 ms) ====== [2025-08-29T12:29:29.134Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-08-29T12:29:29.134Z] GC before operation: completed in 159.120 ms, heap usage 321.138 MB -> 88.481 MB. [2025-08-29T12:29:32.170Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:29:34.136Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:29:37.867Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:29:39.831Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:29:41.795Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:29:43.759Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:29:45.728Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:29:46.686Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:29:47.643Z] 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. [2025-08-29T12:29:47.643Z] The best model improves the baseline by 14.52%. [2025-08-29T12:29:47.643Z] Top recommended movies for user id 72: [2025-08-29T12:29:47.643Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:29:47.643Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:29:47.643Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:29:47.643Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:29:47.643Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:29:47.643Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18444.689 ms) ====== [2025-08-29T12:29:47.643Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-08-29T12:29:47.643Z] GC before operation: completed in 163.533 ms, heap usage 399.052 MB -> 88.901 MB. [2025-08-29T12:29:50.679Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:29:53.713Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:29:56.754Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:29:58.721Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:30:00.686Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:30:02.670Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:30:04.647Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:30:05.602Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:30:06.557Z] 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. [2025-08-29T12:30:06.557Z] The best model improves the baseline by 14.52%. [2025-08-29T12:30:06.557Z] Top recommended movies for user id 72: [2025-08-29T12:30:06.557Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:30:06.557Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:30:06.557Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:30:06.557Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:30:06.557Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:30:06.557Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18916.723 ms) ====== [2025-08-29T12:30:06.557Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-08-29T12:30:06.557Z] GC before operation: completed in 176.765 ms, heap usage 388.728 MB -> 88.835 MB. [2025-08-29T12:30:09.762Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:30:12.787Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:30:14.758Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:30:17.789Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:30:19.751Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:30:21.721Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:30:23.681Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:30:24.657Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:30:25.626Z] 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. [2025-08-29T12:30:25.626Z] The best model improves the baseline by 14.52%. [2025-08-29T12:30:25.626Z] Top recommended movies for user id 72: [2025-08-29T12:30:25.626Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:30:25.626Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:30:25.626Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:30:25.626Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:30:25.626Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:30:25.626Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18873.293 ms) ====== [2025-08-29T12:30:25.626Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-08-29T12:30:25.626Z] GC before operation: completed in 155.887 ms, heap usage 399.093 MB -> 89.047 MB. [2025-08-29T12:30:28.664Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:30:32.059Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:30:34.024Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:30:37.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:30:39.071Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:30:40.029Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:30:41.997Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:30:43.966Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:30:43.966Z] 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. [2025-08-29T12:30:43.966Z] The best model improves the baseline by 14.52%. [2025-08-29T12:30:43.966Z] Top recommended movies for user id 72: [2025-08-29T12:30:43.966Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:30:43.966Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:30:43.966Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:30:43.966Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:30:43.966Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:30:43.966Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18655.736 ms) ====== [2025-08-29T12:30:43.966Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-08-29T12:30:44.922Z] GC before operation: completed in 154.125 ms, heap usage 404.729 MB -> 88.898 MB. [2025-08-29T12:30:46.886Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:30:49.915Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:30:52.955Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:30:54.920Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:30:56.885Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:30:58.846Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:31:00.806Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:31:02.767Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:31:02.767Z] 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. [2025-08-29T12:31:02.767Z] The best model improves the baseline by 14.52%. [2025-08-29T12:31:02.767Z] Top recommended movies for user id 72: [2025-08-29T12:31:02.767Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:31:02.767Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:31:02.767Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:31:02.767Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:31:02.767Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:31:02.767Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18138.583 ms) ====== [2025-08-29T12:31:02.767Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-08-29T12:31:02.767Z] GC before operation: completed in 149.035 ms, heap usage 424.948 MB -> 89.085 MB. [2025-08-29T12:31:05.795Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:31:08.831Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:31:11.864Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:31:13.837Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:31:15.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:31:17.763Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:31:18.719Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:31:20.680Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:31:20.680Z] 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. [2025-08-29T12:31:20.680Z] The best model improves the baseline by 14.52%. [2025-08-29T12:31:21.642Z] Top recommended movies for user id 72: [2025-08-29T12:31:21.643Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:31:21.643Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:31:21.643Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:31:21.643Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:31:21.643Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:31:21.643Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18481.341 ms) ====== [2025-08-29T12:31:21.643Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-08-29T12:31:21.643Z] GC before operation: completed in 161.068 ms, heap usage 205.320 MB -> 88.614 MB. [2025-08-29T12:31:23.615Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:31:27.218Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:31:30.249Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:31:33.282Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:31:34.273Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:31:36.235Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:31:38.196Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:31:39.158Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:31:40.114Z] 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. [2025-08-29T12:31:40.114Z] The best model improves the baseline by 14.52%. [2025-08-29T12:31:40.114Z] Top recommended movies for user id 72: [2025-08-29T12:31:40.114Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:31:40.114Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:31:40.114Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:31:40.114Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:31:40.114Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:31:40.115Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18496.909 ms) ====== [2025-08-29T12:31:40.115Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-08-29T12:31:40.115Z] GC before operation: completed in 170.849 ms, heap usage 512.138 MB -> 89.244 MB. [2025-08-29T12:31:43.142Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:31:46.177Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:31:49.209Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:31:51.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:31:53.138Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:31:55.101Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:31:57.066Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:31:58.024Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:31:58.981Z] 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. [2025-08-29T12:31:58.981Z] The best model improves the baseline by 14.52%. [2025-08-29T12:31:58.981Z] Top recommended movies for user id 72: [2025-08-29T12:31:58.981Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:31:58.981Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:31:58.981Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:31:58.981Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:31:58.981Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:31:58.981Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18784.242 ms) ====== [2025-08-29T12:31:58.981Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-08-29T12:31:58.981Z] GC before operation: completed in 162.878 ms, heap usage 331.803 MB -> 89.077 MB. [2025-08-29T12:32:02.019Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:32:05.052Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:32:08.083Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:32:10.063Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:32:12.028Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:32:13.996Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:32:15.961Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:32:16.919Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:32:17.876Z] 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. [2025-08-29T12:32:17.876Z] The best model improves the baseline by 14.52%. [2025-08-29T12:32:17.876Z] Top recommended movies for user id 72: [2025-08-29T12:32:17.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:32:17.877Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:32:17.877Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:32:17.877Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:32:17.877Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:32:17.877Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18626.414 ms) ====== [2025-08-29T12:32:17.877Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-08-29T12:32:17.877Z] GC before operation: completed in 160.268 ms, heap usage 467.674 MB -> 89.082 MB. [2025-08-29T12:32:20.909Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:32:23.963Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:32:26.800Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:32:29.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:32:31.801Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:32:32.769Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:32:34.735Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:32:36.709Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:32:36.709Z] 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. [2025-08-29T12:32:36.709Z] The best model improves the baseline by 14.52%. [2025-08-29T12:32:37.666Z] Top recommended movies for user id 72: [2025-08-29T12:32:37.666Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:32:37.666Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:32:37.666Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:32:37.666Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:32:37.666Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:32:37.666Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19326.109 ms) ====== [2025-08-29T12:32:37.666Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-08-29T12:32:37.666Z] GC before operation: completed in 168.543 ms, heap usage 477.344 MB -> 89.306 MB. [2025-08-29T12:32:40.703Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:32:43.741Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:32:46.774Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:32:48.736Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:32:50.703Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:32:52.670Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:32:54.645Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:32:56.607Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:32:56.607Z] 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. [2025-08-29T12:32:56.607Z] The best model improves the baseline by 14.52%. [2025-08-29T12:32:56.607Z] Top recommended movies for user id 72: [2025-08-29T12:32:56.607Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:32:56.607Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:32:56.607Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:32:56.607Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:32:56.607Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:32:56.607Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19260.419 ms) ====== [2025-08-29T12:32:56.607Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-08-29T12:32:56.607Z] GC before operation: completed in 181.057 ms, heap usage 282.600 MB -> 88.920 MB. [2025-08-29T12:32:59.638Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:33:02.682Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:33:05.711Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:33:08.750Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:33:09.706Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:33:11.675Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:33:13.639Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:33:15.603Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:33:15.603Z] 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. [2025-08-29T12:33:15.603Z] The best model improves the baseline by 14.52%. [2025-08-29T12:33:15.603Z] Top recommended movies for user id 72: [2025-08-29T12:33:15.603Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:33:15.603Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:33:15.603Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:33:15.603Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:33:15.603Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:33:15.603Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18977.259 ms) ====== [2025-08-29T12:33:15.603Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-08-29T12:33:15.603Z] GC before operation: completed in 172.911 ms, heap usage 396.239 MB -> 89.149 MB. [2025-08-29T12:33:19.335Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:33:21.305Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:33:24.343Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:33:27.387Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:33:29.351Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:33:30.306Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:33:32.283Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:33:34.245Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:33:35.201Z] 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. [2025-08-29T12:33:35.201Z] The best model improves the baseline by 14.52%. [2025-08-29T12:33:35.201Z] Top recommended movies for user id 72: [2025-08-29T12:33:35.201Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:33:35.201Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:33:35.201Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:33:35.201Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:33:35.201Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:33:35.201Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19015.767 ms) ====== [2025-08-29T12:33:35.201Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-08-29T12:33:35.201Z] GC before operation: completed in 178.689 ms, heap usage 437.710 MB -> 89.069 MB. [2025-08-29T12:33:38.227Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:33:41.254Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:33:44.280Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:33:47.311Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:33:48.267Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:33:50.227Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:33:52.190Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:33:54.151Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:33:55.109Z] 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. [2025-08-29T12:33:55.109Z] The best model improves the baseline by 14.52%. [2025-08-29T12:33:55.109Z] Top recommended movies for user id 72: [2025-08-29T12:33:55.109Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:33:55.109Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:33:55.109Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:33:55.109Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:33:55.109Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:33:55.109Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19810.893 ms) ====== [2025-08-29T12:33:55.109Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-08-29T12:33:55.109Z] GC before operation: completed in 183.122 ms, heap usage 395.613 MB -> 89.086 MB. [2025-08-29T12:33:58.132Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T12:34:01.170Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T12:34:04.233Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T12:34:07.259Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T12:34:09.228Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T12:34:11.189Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T12:34:13.152Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T12:34:15.833Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T12:34:15.833Z] 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. [2025-08-29T12:34:15.833Z] The best model improves the baseline by 14.52%. [2025-08-29T12:34:15.833Z] Top recommended movies for user id 72: [2025-08-29T12:34:15.833Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T12:34:15.833Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T12:34:15.833Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T12:34:15.833Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T12:34:15.833Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T12:34:15.833Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (20105.642 ms) ====== [2025-08-29T12:34:15.833Z] ----------------------------------- [2025-08-29T12:34:15.833Z] renaissance-movie-lens_0_PASSED [2025-08-29T12:34:15.833Z] ----------------------------------- [2025-08-29T12:34:15.833Z] [2025-08-29T12:34:15.833Z] TEST TEARDOWN: [2025-08-29T12:34:15.833Z] Nothing to be done for teardown. [2025-08-29T12:34:15.833Z] renaissance-movie-lens_0 Finish Time: Fri Aug 29 12:34:15 2025 Epoch Time (ms): 1756470855354