[2025-12-17T23:07:09.739Z] Running test renaissance-movie-lens_0 ... [2025-12-17T23:07:09.739Z] =============================================== [2025-12-17T23:07:09.739Z] renaissance-movie-lens_0 Start Time: Wed Dec 17 23:07:09 2025 Epoch Time (ms): 1766012829382 [2025-12-17T23:07:09.739Z] variation: NoOptions [2025-12-17T23:07:09.739Z] JVM_OPTIONS: [2025-12-17T23:07:09.739Z] { \ [2025-12-17T23:07:09.739Z] echo ""; echo "TEST SETUP:"; \ [2025-12-17T23:07:09.739Z] echo "Nothing to be done for setup."; \ [2025-12-17T23:07:09.739Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17660096091385/renaissance-movie-lens_0"; \ [2025-12-17T23:07:09.739Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17660096091385/renaissance-movie-lens_0"; \ [2025-12-17T23:07:09.739Z] echo ""; echo "TESTING:"; \ [2025-12-17T23:07:09.739Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17660096091385/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-17T23:07:09.739Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17660096091385/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-17T23:07:09.739Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-17T23:07:09.739Z] echo "Nothing to be done for teardown."; \ [2025-12-17T23:07:09.739Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17660096091385/TestTargetResult"; [2025-12-17T23:07:09.739Z] [2025-12-17T23:07:09.739Z] TEST SETUP: [2025-12-17T23:07:09.739Z] Nothing to be done for setup. [2025-12-17T23:07:09.739Z] [2025-12-17T23:07:09.739Z] TESTING: [2025-12-17T23:07:25.647Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-17T23:07:44.405Z] 23:07:43.072 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-17T23:07:51.433Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-17T23:07:53.449Z] Training: 60056, validation: 20285, test: 19854 [2025-12-17T23:07:53.449Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-17T23:07:54.427Z] GC before operation: completed in 275.652 ms, heap usage 325.582 MB -> 75.848 MB. [2025-12-17T23:08:19.452Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:08:29.398Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:08:39.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:08:49.868Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:08:54.278Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:08:59.782Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:09:04.849Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:09:09.290Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:09:10.263Z] 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. [2025-12-17T23:09:10.263Z] The best model improves the baseline by 14.52%. [2025-12-17T23:09:11.238Z] Top recommended movies for user id 72: [2025-12-17T23:09:11.238Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:09:11.238Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:09:11.238Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:09:11.238Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:09:11.238Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:09:11.238Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (77461.838 ms) ====== [2025-12-17T23:09:11.238Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-17T23:09:11.238Z] GC before operation: completed in 296.306 ms, heap usage 231.764 MB -> 91.558 MB. [2025-12-17T23:09:21.277Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:09:28.222Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:09:36.890Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:09:45.406Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:09:50.797Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:09:55.615Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:10:01.458Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:10:04.589Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:10:05.750Z] 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. [2025-12-17T23:10:05.750Z] The best model improves the baseline by 14.52%. [2025-12-17T23:10:06.728Z] Top recommended movies for user id 72: [2025-12-17T23:10:06.728Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:10:06.728Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:10:06.728Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:10:06.728Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:10:06.728Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:10:06.728Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (54660.278 ms) ====== [2025-12-17T23:10:06.728Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-17T23:10:06.728Z] GC before operation: completed in 354.688 ms, heap usage 235.568 MB -> 88.683 MB. [2025-12-17T23:10:15.309Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:10:24.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:10:32.166Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:10:39.771Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:10:44.279Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:10:50.435Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:10:55.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:10:59.454Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:11:00.434Z] 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. [2025-12-17T23:11:00.434Z] The best model improves the baseline by 14.52%. [2025-12-17T23:11:00.434Z] Top recommended movies for user id 72: [2025-12-17T23:11:00.434Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:11:00.434Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:11:00.434Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:11:00.434Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:11:00.434Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:11:00.434Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (53842.216 ms) ====== [2025-12-17T23:11:00.434Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-17T23:11:01.430Z] GC before operation: completed in 439.350 ms, heap usage 258.165 MB -> 90.566 MB. [2025-12-17T23:11:08.578Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:11:15.900Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:11:24.397Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:11:33.144Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:11:37.101Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:11:39.091Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:11:42.388Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:11:44.448Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:11:45.414Z] 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. [2025-12-17T23:11:45.414Z] The best model improves the baseline by 14.52%. [2025-12-17T23:11:45.414Z] Top recommended movies for user id 72: [2025-12-17T23:11:45.414Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:11:45.414Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:11:45.414Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:11:45.414Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:11:45.414Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:11:45.414Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (44719.687 ms) ====== [2025-12-17T23:11:45.414Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-17T23:11:46.392Z] GC before operation: completed in 214.622 ms, heap usage 460.318 MB -> 92.196 MB. [2025-12-17T23:11:52.180Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:11:58.136Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:12:03.894Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:12:08.217Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:12:11.299Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:12:14.374Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:12:16.428Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:12:19.525Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:12:19.525Z] 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. [2025-12-17T23:12:19.525Z] The best model improves the baseline by 14.52%. [2025-12-17T23:12:20.487Z] Top recommended movies for user id 72: [2025-12-17T23:12:20.487Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:12:20.487Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:12:20.487Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:12:20.487Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:12:20.487Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:12:20.487Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (34255.792 ms) ====== [2025-12-17T23:12:20.487Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-17T23:12:20.487Z] GC before operation: completed in 258.974 ms, heap usage 284.001 MB -> 93.224 MB. [2025-12-17T23:12:24.694Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:12:27.750Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:12:31.953Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:12:35.033Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:12:37.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:12:39.004Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:12:41.706Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:12:42.686Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:12:42.686Z] 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. [2025-12-17T23:12:42.686Z] The best model improves the baseline by 14.52%. [2025-12-17T23:12:42.686Z] Top recommended movies for user id 72: [2025-12-17T23:12:42.686Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:12:42.686Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:12:42.686Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:12:42.686Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:12:42.686Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:12:42.686Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (22368.582 ms) ====== [2025-12-17T23:12:42.686Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-17T23:12:42.686Z] GC before operation: completed in 171.522 ms, heap usage 543.103 MB -> 90.329 MB. [2025-12-17T23:12:46.923Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:12:48.918Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:12:53.178Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:12:55.186Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:12:57.173Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:12:59.160Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:13:01.191Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:13:03.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:13:03.176Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-17T23:13:03.176Z] The best model improves the baseline by 14.52%. [2025-12-17T23:13:04.146Z] Top recommended movies for user id 72: [2025-12-17T23:13:04.146Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:13:04.146Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:13:04.146Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:13:04.146Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:13:04.146Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:13:04.146Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20676.008 ms) ====== [2025-12-17T23:13:04.146Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-17T23:13:04.146Z] GC before operation: completed in 218.603 ms, heap usage 620.505 MB -> 93.606 MB. [2025-12-17T23:13:08.365Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:13:13.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:13:19.372Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:13:23.604Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:13:26.659Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:13:28.648Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:13:31.717Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:13:33.721Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:13:33.721Z] 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. [2025-12-17T23:13:33.721Z] The best model improves the baseline by 14.52%. [2025-12-17T23:13:34.691Z] Top recommended movies for user id 72: [2025-12-17T23:13:34.691Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:13:34.691Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:13:34.691Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:13:34.691Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:13:34.691Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:13:34.691Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (30436.413 ms) ====== [2025-12-17T23:13:34.691Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-17T23:13:34.691Z] GC before operation: completed in 204.062 ms, heap usage 694.015 MB -> 93.941 MB. [2025-12-17T23:13:38.952Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:13:43.389Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:13:49.585Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:13:55.063Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:13:58.210Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:14:01.317Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:14:04.398Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:14:07.496Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:14:08.475Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-17T23:14:08.475Z] The best model improves the baseline by 14.52%. [2025-12-17T23:14:08.475Z] Top recommended movies for user id 72: [2025-12-17T23:14:08.475Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:14:08.475Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:14:08.475Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:14:08.475Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:14:08.475Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:14:08.475Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (33944.138 ms) ====== [2025-12-17T23:14:08.475Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-17T23:14:08.475Z] GC before operation: completed in 295.262 ms, heap usage 559.248 MB -> 95.603 MB. [2025-12-17T23:14:13.925Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:14:19.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:14:24.931Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:14:29.173Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:14:32.246Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:14:35.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:14:37.338Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:14:39.321Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:14:39.321Z] 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. [2025-12-17T23:14:39.321Z] The best model improves the baseline by 14.52%. [2025-12-17T23:14:40.288Z] Top recommended movies for user id 72: [2025-12-17T23:14:40.288Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:14:40.288Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:14:40.288Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:14:40.288Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:14:40.288Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:14:40.288Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (31134.056 ms) ====== [2025-12-17T23:14:40.288Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-17T23:14:40.288Z] GC before operation: completed in 165.366 ms, heap usage 246.081 MB -> 92.470 MB. [2025-12-17T23:14:43.340Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:14:46.389Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:14:49.471Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:14:52.292Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:14:54.298Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:14:56.276Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:14:59.358Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:15:02.426Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:15:02.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-17T23:15:02.426Z] The best model improves the baseline by 14.52%. [2025-12-17T23:15:02.426Z] Top recommended movies for user id 72: [2025-12-17T23:15:02.426Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:15:02.426Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:15:02.427Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:15:02.427Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:15:02.427Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:15:02.427Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (22702.607 ms) ====== [2025-12-17T23:15:02.427Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-17T23:15:03.390Z] GC before operation: completed in 226.542 ms, heap usage 171.574 MB -> 93.022 MB. [2025-12-17T23:15:07.600Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:15:11.828Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:15:16.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:15:21.558Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:15:21.558Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:15:24.626Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:15:27.698Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:15:30.788Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:15:30.788Z] 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. [2025-12-17T23:15:30.788Z] The best model improves the baseline by 14.52%. [2025-12-17T23:15:31.764Z] Top recommended movies for user id 72: [2025-12-17T23:15:31.764Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:15:31.764Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:15:31.764Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:15:31.764Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:15:31.764Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:15:31.764Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (28518.484 ms) ====== [2025-12-17T23:15:31.764Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-17T23:15:31.764Z] GC before operation: completed in 320.927 ms, heap usage 748.876 MB -> 94.107 MB. [2025-12-17T23:15:38.594Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:15:44.114Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:15:49.740Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:15:55.258Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:15:58.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:16:01.904Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:16:05.080Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:16:09.333Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:16:09.333Z] 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. [2025-12-17T23:16:09.333Z] The best model improves the baseline by 14.52%. [2025-12-17T23:16:09.333Z] Top recommended movies for user id 72: [2025-12-17T23:16:09.333Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:16:09.333Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:16:09.333Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:16:09.333Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:16:09.333Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:16:09.333Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (37900.063 ms) ====== [2025-12-17T23:16:09.333Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-17T23:16:10.300Z] GC before operation: completed in 360.736 ms, heap usage 492.171 MB -> 91.760 MB. [2025-12-17T23:16:17.129Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:16:23.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:16:30.757Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:16:36.251Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:16:39.318Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:16:42.385Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:16:44.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:16:47.448Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:16:47.448Z] 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. [2025-12-17T23:16:47.448Z] The best model improves the baseline by 14.52%. [2025-12-17T23:16:47.448Z] Top recommended movies for user id 72: [2025-12-17T23:16:47.448Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:16:47.448Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:16:47.448Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:16:47.448Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:16:47.448Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:16:47.448Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (37753.178 ms) ====== [2025-12-17T23:16:47.448Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-17T23:16:48.429Z] GC before operation: completed in 230.502 ms, heap usage 551.199 MB -> 93.090 MB. [2025-12-17T23:16:54.096Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:16:58.324Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:17:02.539Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:17:05.222Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:17:07.200Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:17:09.179Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:17:11.164Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:17:12.127Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:17:13.095Z] 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. [2025-12-17T23:17:13.095Z] The best model improves the baseline by 14.52%. [2025-12-17T23:17:13.095Z] Top recommended movies for user id 72: [2025-12-17T23:17:13.095Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:17:13.095Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:17:13.095Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:17:13.095Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:17:13.095Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:17:13.095Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (24844.987 ms) ====== [2025-12-17T23:17:13.095Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-17T23:17:13.095Z] GC before operation: completed in 173.712 ms, heap usage 523.008 MB -> 92.888 MB. [2025-12-17T23:17:17.289Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:17:19.272Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:17:23.480Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:17:25.464Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:17:27.439Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:17:29.426Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:17:33.624Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:17:35.610Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:17:35.610Z] 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. [2025-12-17T23:17:35.610Z] The best model improves the baseline by 14.52%. [2025-12-17T23:17:35.610Z] Top recommended movies for user id 72: [2025-12-17T23:17:35.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:17:35.610Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:17:35.610Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:17:35.610Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:17:35.610Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:17:35.610Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (22612.595 ms) ====== [2025-12-17T23:17:35.610Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-17T23:17:35.610Z] GC before operation: completed in 176.452 ms, heap usage 133.948 MB -> 93.440 MB. [2025-12-17T23:17:42.475Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:17:46.691Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:17:49.746Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:17:54.011Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:17:55.993Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:17:57.969Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:18:01.022Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:18:03.002Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:18:03.002Z] 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. [2025-12-17T23:18:03.002Z] The best model improves the baseline by 14.52%. [2025-12-17T23:18:03.002Z] Top recommended movies for user id 72: [2025-12-17T23:18:03.002Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:18:03.002Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:18:03.002Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:18:03.002Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:18:03.002Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:18:03.002Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (27536.560 ms) ====== [2025-12-17T23:18:03.002Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-17T23:18:03.965Z] GC before operation: completed in 194.841 ms, heap usage 283.328 MB -> 93.535 MB. [2025-12-17T23:18:07.746Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:18:10.814Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:18:15.033Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:18:19.250Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:18:21.315Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:18:23.294Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:18:26.342Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:18:28.333Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:18:28.333Z] 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. [2025-12-17T23:18:28.333Z] The best model improves the baseline by 14.52%. [2025-12-17T23:18:28.333Z] Top recommended movies for user id 72: [2025-12-17T23:18:28.333Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:18:28.333Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:18:28.333Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:18:28.333Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:18:28.333Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:18:28.333Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (24912.614 ms) ====== [2025-12-17T23:18:28.333Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-17T23:18:28.333Z] GC before operation: completed in 191.496 ms, heap usage 214.748 MB -> 92.684 MB. [2025-12-17T23:18:32.548Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:18:36.975Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:18:41.412Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:18:44.856Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:18:46.831Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:18:50.085Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:18:52.063Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:18:54.335Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:18:55.297Z] 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. [2025-12-17T23:18:55.297Z] The best model improves the baseline by 14.52%. [2025-12-17T23:18:55.297Z] Top recommended movies for user id 72: [2025-12-17T23:18:55.297Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:18:55.297Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:18:55.297Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:18:55.297Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:18:55.297Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:18:55.297Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (26713.756 ms) ====== [2025-12-17T23:18:55.297Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-17T23:18:55.297Z] GC before operation: completed in 190.030 ms, heap usage 242.457 MB -> 93.735 MB. [2025-12-17T23:19:00.800Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-17T23:19:03.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-17T23:19:08.090Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-17T23:19:12.601Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-17T23:19:14.594Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-17T23:19:16.575Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-17T23:19:19.642Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-17T23:19:22.704Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-17T23:19:22.704Z] 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. [2025-12-17T23:19:22.704Z] The best model improves the baseline by 14.52%. [2025-12-17T23:19:22.704Z] Top recommended movies for user id 72: [2025-12-17T23:19:22.704Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-17T23:19:22.704Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-17T23:19:22.704Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-17T23:19:22.704Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-17T23:19:22.704Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-17T23:19:22.704Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27356.581 ms) ====== [2025-12-17T23:19:24.687Z] ----------------------------------- [2025-12-17T23:19:24.687Z] renaissance-movie-lens_0_PASSED [2025-12-17T23:19:24.687Z] ----------------------------------- [2025-12-17T23:19:24.687Z] [2025-12-17T23:19:24.687Z] TEST TEARDOWN: [2025-12-17T23:19:24.687Z] Nothing to be done for teardown. [2025-12-17T23:19:24.687Z] renaissance-movie-lens_0 Finish Time: Wed Dec 17 23:19:24 2025 Epoch Time (ms): 1766013564386