[2025-12-03T22:57:10.174Z] Running test renaissance-movie-lens_0 ... [2025-12-03T22:57:10.174Z] =============================================== [2025-12-03T22:57:10.174Z] renaissance-movie-lens_0 Start Time: Wed Dec 3 22:57:10 2025 Epoch Time (ms): 1764802630075 [2025-12-03T22:57:10.174Z] variation: NoOptions [2025-12-03T22:57:11.127Z] JVM_OPTIONS: [2025-12-03T22:57:11.127Z] { \ [2025-12-03T22:57:11.127Z] echo ""; echo "TEST SETUP:"; \ [2025-12-03T22:57:11.127Z] echo "Nothing to be done for setup."; \ [2025-12-03T22:57:11.128Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648011688190/renaissance-movie-lens_0"; \ [2025-12-03T22:57:11.128Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648011688190/renaissance-movie-lens_0"; \ [2025-12-03T22:57:11.128Z] echo ""; echo "TESTING:"; \ [2025-12-03T22:57:11.128Z] "/home/jenkins/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648011688190/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-03T22:57:11.128Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648011688190/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-03T22:57:11.128Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-03T22:57:11.128Z] echo "Nothing to be done for teardown."; \ [2025-12-03T22:57:11.128Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648011688190/TestTargetResult"; [2025-12-03T22:57:11.128Z] [2025-12-03T22:57:11.128Z] TEST SETUP: [2025-12-03T22:57:11.128Z] Nothing to be done for setup. [2025-12-03T22:57:11.128Z] [2025-12-03T22:57:11.128Z] TESTING: [2025-12-03T22:57:16.238Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-03T22:57:23.175Z] 22:57:22.138 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-03T22:57:25.254Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-03T22:57:25.254Z] Training: 60056, validation: 20285, test: 19854 [2025-12-03T22:57:25.254Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-03T22:57:25.254Z] GC before operation: completed in 152.639 ms, heap usage 180.123 MB -> 75.786 MB. [2025-12-03T22:57:30.783Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:57:34.936Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:57:38.335Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:57:40.289Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:57:42.380Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:57:44.335Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:57:45.356Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:57:47.306Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:57:48.266Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:57:48.266Z] The best model improves the baseline by 14.52%. [2025-12-03T22:57:48.266Z] Top recommended movies for user id 72: [2025-12-03T22:57:48.266Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:57:48.266Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:57:48.266Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:57:48.266Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:57:48.266Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:57:48.266Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22757.988 ms) ====== [2025-12-03T22:57:48.266Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-03T22:57:48.266Z] GC before operation: completed in 163.619 ms, heap usage 532.789 MB -> 92.802 MB. [2025-12-03T22:57:51.588Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:57:54.064Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:57:56.137Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:57:59.152Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:58:01.102Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:58:02.054Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:58:04.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:58:04.965Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:58:06.010Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:58:06.010Z] The best model improves the baseline by 14.52%. [2025-12-03T22:58:06.010Z] Top recommended movies for user id 72: [2025-12-03T22:58:06.010Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:58:06.010Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:58:06.010Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:58:06.010Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:58:06.010Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:58:06.010Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17566.129 ms) ====== [2025-12-03T22:58:06.010Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-03T22:58:06.010Z] GC before operation: completed in 138.565 ms, heap usage 473.132 MB -> 89.047 MB. [2025-12-03T22:58:08.105Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:58:11.271Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:58:13.224Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:58:15.708Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:58:17.661Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:58:18.611Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:58:20.560Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:58:22.531Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:58:22.531Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:58:22.531Z] The best model improves the baseline by 14.52%. [2025-12-03T22:58:22.531Z] Top recommended movies for user id 72: [2025-12-03T22:58:22.531Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:58:22.531Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:58:22.531Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:58:22.531Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:58:22.531Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:58:22.531Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16756.956 ms) ====== [2025-12-03T22:58:22.531Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-03T22:58:22.531Z] GC before operation: completed in 127.763 ms, heap usage 144.571 MB -> 89.477 MB. [2025-12-03T22:58:25.545Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:58:27.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:58:30.532Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:58:33.544Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:58:34.494Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:58:37.028Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:58:37.978Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:58:39.945Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:58:39.945Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:58:39.945Z] The best model improves the baseline by 14.52%. [2025-12-03T22:58:39.945Z] Top recommended movies for user id 72: [2025-12-03T22:58:39.945Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:58:39.945Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:58:39.945Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:58:39.945Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:58:39.945Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:58:39.945Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17171.736 ms) ====== [2025-12-03T22:58:39.945Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-03T22:58:39.945Z] GC before operation: completed in 147.103 ms, heap usage 132.801 MB -> 89.637 MB. [2025-12-03T22:58:42.957Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:58:44.909Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:58:47.929Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:58:49.889Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:58:51.103Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:58:53.053Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:58:54.062Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:58:56.094Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:58:56.094Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:58:56.094Z] The best model improves the baseline by 14.52%. [2025-12-03T22:58:56.094Z] Top recommended movies for user id 72: [2025-12-03T22:58:56.094Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:58:56.094Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:58:56.094Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:58:56.094Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:58:56.094Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:58:56.094Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15812.626 ms) ====== [2025-12-03T22:58:56.094Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-03T22:58:56.094Z] GC before operation: completed in 203.254 ms, heap usage 521.223 MB -> 90.086 MB. [2025-12-03T22:58:59.105Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:59:01.057Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:59:03.019Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:59:06.100Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:59:07.051Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:59:09.000Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:59:09.964Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:59:11.433Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:59:12.384Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:59:12.384Z] The best model improves the baseline by 14.52%. [2025-12-03T22:59:12.384Z] Top recommended movies for user id 72: [2025-12-03T22:59:12.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:59:12.384Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:59:12.384Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:59:12.384Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:59:12.384Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:59:12.384Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15912.836 ms) ====== [2025-12-03T22:59:12.384Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-03T22:59:12.384Z] GC before operation: completed in 151.760 ms, heap usage 152.417 MB -> 89.969 MB. [2025-12-03T22:59:14.337Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:59:17.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:59:19.310Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:59:21.270Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:59:23.225Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:59:24.175Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:59:26.201Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:59:28.155Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:59:28.155Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:59:28.155Z] The best model improves the baseline by 14.52%. [2025-12-03T22:59:28.155Z] Top recommended movies for user id 72: [2025-12-03T22:59:28.155Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:59:28.155Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:59:28.155Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:59:28.155Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:59:28.155Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:59:28.155Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15927.847 ms) ====== [2025-12-03T22:59:28.155Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-03T22:59:28.155Z] GC before operation: completed in 145.129 ms, heap usage 382.318 MB -> 90.143 MB. [2025-12-03T22:59:31.519Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:59:32.472Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:59:35.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:59:37.466Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:59:39.427Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:59:40.403Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:59:42.366Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:59:43.318Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:59:44.269Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:59:44.269Z] The best model improves the baseline by 14.52%. [2025-12-03T22:59:44.269Z] Top recommended movies for user id 72: [2025-12-03T22:59:44.269Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:59:44.269Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:59:44.269Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:59:44.269Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:59:44.269Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:59:44.269Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16014.924 ms) ====== [2025-12-03T22:59:44.269Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-03T22:59:44.269Z] GC before operation: completed in 148.618 ms, heap usage 120.947 MB -> 90.009 MB. [2025-12-03T22:59:47.287Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:59:49.610Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:59:51.574Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:59:53.527Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:59:55.655Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:59:56.607Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:59:58.557Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:59:59.508Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:00:00.458Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:00:00.458Z] The best model improves the baseline by 14.52%. [2025-12-03T23:00:00.458Z] Top recommended movies for user id 72: [2025-12-03T23:00:00.458Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:00:00.458Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:00:00.458Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:00:00.458Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:00:00.458Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:00:00.458Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15796.657 ms) ====== [2025-12-03T23:00:00.458Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-03T23:00:00.458Z] GC before operation: completed in 142.044 ms, heap usage 361.903 MB -> 90.220 MB. [2025-12-03T23:00:02.560Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:00:05.166Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:00:08.133Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:00:09.766Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:00:12.214Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:00:13.202Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:00:14.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:00:17.055Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:00:17.055Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:00:17.055Z] The best model improves the baseline by 14.52%. [2025-12-03T23:00:17.055Z] Top recommended movies for user id 72: [2025-12-03T23:00:17.055Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:00:17.055Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:00:17.055Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:00:17.055Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:00:17.055Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:00:17.055Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15828.760 ms) ====== [2025-12-03T23:00:17.055Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-03T23:00:17.055Z] GC before operation: completed in 147.503 ms, heap usage 333.398 MB -> 90.309 MB. [2025-12-03T23:00:19.234Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:00:21.543Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:00:23.520Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:00:26.675Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:00:28.082Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:00:29.237Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:00:30.496Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:00:33.420Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:00:33.420Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:00:33.420Z] The best model improves the baseline by 14.52%. [2025-12-03T23:00:33.420Z] Top recommended movies for user id 72: [2025-12-03T23:00:33.420Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:00:33.420Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:00:33.420Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:00:33.420Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:00:33.420Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:00:33.420Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16024.377 ms) ====== [2025-12-03T23:00:33.420Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-03T23:00:33.420Z] GC before operation: completed in 148.405 ms, heap usage 150.884 MB -> 89.806 MB. [2025-12-03T23:00:34.405Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:00:38.038Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:00:39.039Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:00:42.363Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:00:43.436Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:00:44.416Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:00:45.390Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:00:47.387Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:00:47.387Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:00:47.387Z] The best model improves the baseline by 14.52%. [2025-12-03T23:00:47.387Z] Top recommended movies for user id 72: [2025-12-03T23:00:47.387Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:00:47.387Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:00:47.387Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:00:47.387Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:00:47.387Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:00:47.387Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14879.378 ms) ====== [2025-12-03T23:00:47.387Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-03T23:00:47.387Z] GC before operation: completed in 155.818 ms, heap usage 354.891 MB -> 90.401 MB. [2025-12-03T23:00:50.481Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:00:52.672Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:00:55.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:00:56.535Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:00:58.725Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:00:59.682Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:01:00.652Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:01:02.704Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:01:02.704Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:01:02.704Z] The best model improves the baseline by 14.52%. [2025-12-03T23:01:02.704Z] Top recommended movies for user id 72: [2025-12-03T23:01:02.704Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:01:02.704Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:01:02.704Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:01:02.704Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:01:02.704Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:01:02.704Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15175.834 ms) ====== [2025-12-03T23:01:02.704Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-03T23:01:02.704Z] GC before operation: completed in 160.978 ms, heap usage 246.722 MB -> 90.222 MB. [2025-12-03T23:01:04.708Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:01:07.793Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:01:09.836Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:01:12.285Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:01:13.369Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:01:14.326Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:01:16.309Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:01:17.276Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:01:17.276Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:01:17.276Z] The best model improves the baseline by 14.52%. [2025-12-03T23:01:18.259Z] Top recommended movies for user id 72: [2025-12-03T23:01:18.259Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:01:18.259Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:01:18.259Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:01:18.259Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:01:18.259Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:01:18.259Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14846.443 ms) ====== [2025-12-03T23:01:18.259Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-03T23:01:18.259Z] GC before operation: completed in 131.114 ms, heap usage 198.212 MB -> 90.065 MB. [2025-12-03T23:01:20.228Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:01:22.197Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:01:24.458Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:01:26.440Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:01:28.580Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:01:29.556Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:01:30.538Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:01:31.515Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:01:32.477Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:01:32.477Z] The best model improves the baseline by 14.52%. [2025-12-03T23:01:32.477Z] Top recommended movies for user id 72: [2025-12-03T23:01:32.477Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:01:32.477Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:01:32.477Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:01:32.477Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:01:32.477Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:01:32.477Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14432.171 ms) ====== [2025-12-03T23:01:32.477Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-03T23:01:32.477Z] GC before operation: completed in 152.249 ms, heap usage 713.364 MB -> 94.251 MB. [2025-12-03T23:01:36.241Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:01:37.220Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:01:39.308Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:01:41.287Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:01:42.246Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:01:44.248Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:01:45.223Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:01:46.191Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:01:47.250Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:01:47.250Z] The best model improves the baseline by 14.52%. [2025-12-03T23:01:47.250Z] Top recommended movies for user id 72: [2025-12-03T23:01:47.250Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:01:47.250Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:01:47.250Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:01:47.250Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:01:47.250Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:01:47.250Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14546.865 ms) ====== [2025-12-03T23:01:47.250Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-03T23:01:47.250Z] GC before operation: completed in 187.952 ms, heap usage 123.521 MB -> 90.029 MB. [2025-12-03T23:01:49.245Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:01:51.222Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:01:54.129Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:01:56.106Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:01:57.072Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:01:58.047Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:02:00.016Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:02:00.976Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:02:00.976Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:02:00.976Z] The best model improves the baseline by 14.52%. [2025-12-03T23:02:00.976Z] Top recommended movies for user id 72: [2025-12-03T23:02:00.976Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:02:00.976Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:02:00.976Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:02:00.976Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:02:00.976Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:02:00.976Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14171.703 ms) ====== [2025-12-03T23:02:00.976Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-03T23:02:01.952Z] GC before operation: completed in 157.253 ms, heap usage 512.657 MB -> 90.729 MB. [2025-12-03T23:02:03.943Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:02:05.934Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:02:07.904Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:02:10.742Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:02:11.699Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:02:12.657Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:02:14.621Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:02:15.577Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:02:15.577Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:02:16.537Z] The best model improves the baseline by 14.52%. [2025-12-03T23:02:16.537Z] Top recommended movies for user id 72: [2025-12-03T23:02:16.537Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:02:16.537Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:02:16.537Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:02:16.537Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:02:16.537Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:02:16.537Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14706.725 ms) ====== [2025-12-03T23:02:16.537Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-03T23:02:16.537Z] GC before operation: completed in 172.229 ms, heap usage 227.543 MB -> 90.091 MB. [2025-12-03T23:02:18.490Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:02:21.513Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:02:23.486Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:02:25.483Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:02:27.445Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:02:29.553Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:02:31.731Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:02:32.685Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:02:32.685Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:02:32.685Z] The best model improves the baseline by 14.52%. [2025-12-03T23:02:32.685Z] Top recommended movies for user id 72: [2025-12-03T23:02:32.685Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:02:32.685Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:02:32.685Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:02:32.685Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:02:32.685Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:02:32.685Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16302.957 ms) ====== [2025-12-03T23:02:32.685Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-03T23:02:32.685Z] GC before operation: completed in 163.213 ms, heap usage 224.366 MB -> 90.185 MB. [2025-12-03T23:02:34.669Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T23:02:37.685Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T23:02:39.681Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T23:02:41.645Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T23:02:42.666Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T23:02:44.628Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T23:02:45.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T23:02:47.699Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T23:02:47.699Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T23:02:47.699Z] The best model improves the baseline by 14.52%. [2025-12-03T23:02:47.699Z] Top recommended movies for user id 72: [2025-12-03T23:02:47.699Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T23:02:47.699Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T23:02:47.699Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T23:02:47.699Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T23:02:47.699Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T23:02:47.699Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14618.555 ms) ====== [2025-12-03T23:02:47.699Z] ----------------------------------- [2025-12-03T23:02:47.699Z] renaissance-movie-lens_0_PASSED [2025-12-03T23:02:47.699Z] ----------------------------------- [2025-12-03T23:02:47.699Z] [2025-12-03T23:02:47.699Z] TEST TEARDOWN: [2025-12-03T23:02:47.699Z] Nothing to be done for teardown. [2025-12-03T23:02:47.699Z] renaissance-movie-lens_0 Finish Time: Wed Dec 3 23:02:47 2025 Epoch Time (ms): 1764802967594