[2025-09-25T00:37:54.778Z] Running test renaissance-movie-lens_0 ... [2025-09-25T00:37:54.778Z] =============================================== [2025-09-25T00:37:54.778Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 00:37:54 2025 Epoch Time (ms): 1758760674305 [2025-09-25T00:37:54.778Z] variation: NoOptions [2025-09-25T00:37:54.778Z] JVM_OPTIONS: [2025-09-25T00:37:54.778Z] { \ [2025-09-25T00:37:54.778Z] echo ""; echo "TEST SETUP:"; \ [2025-09-25T00:37:54.778Z] echo "Nothing to be done for setup."; \ [2025-09-25T00:37:54.778Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17587592341836/renaissance-movie-lens_0"; \ [2025-09-25T00:37:54.778Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17587592341836/renaissance-movie-lens_0"; \ [2025-09-25T00:37:54.778Z] echo ""; echo "TESTING:"; \ [2025-09-25T00:37:54.778Z] "/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_17587592341836/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-25T00:37:54.778Z] 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_17587592341836/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-25T00:37:54.778Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-25T00:37:54.778Z] echo "Nothing to be done for teardown."; \ [2025-09-25T00:37:54.778Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17587592341836/TestTargetResult"; [2025-09-25T00:37:54.778Z] [2025-09-25T00:37:54.778Z] TEST SETUP: [2025-09-25T00:37:54.778Z] Nothing to be done for setup. [2025-09-25T00:37:54.778Z] [2025-09-25T00:37:54.778Z] TESTING: [2025-09-25T00:38:00.106Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-25T00:38:06.773Z] 00:38:06.082 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. [2025-09-25T00:38:08.778Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-25T00:38:08.778Z] Training: 60056, validation: 20285, test: 19854 [2025-09-25T00:38:08.778Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-25T00:38:09.741Z] GC before operation: completed in 151.040 ms, heap usage 423.744 MB -> 75.942 MB. [2025-09-25T00:38:15.185Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:38:18.219Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:38:21.241Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:38:24.250Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:38:26.225Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:38:27.174Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:38:29.160Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:38:31.107Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:38:31.107Z] 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. [2025-09-25T00:38:31.107Z] The best model improves the baseline by 14.52%. [2025-09-25T00:38:31.107Z] Top recommended movies for user id 72: [2025-09-25T00:38:31.107Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:38:31.107Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:38:31.107Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:38:31.107Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:38:31.107Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:38:31.107Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22176.181 ms) ====== [2025-09-25T00:38:31.107Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-25T00:38:32.989Z] GC before operation: completed in 172.917 ms, heap usage 179.826 MB -> 96.907 MB. [2025-09-25T00:38:34.116Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:38:37.127Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:38:40.136Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:38:42.076Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:38:44.014Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:38:45.949Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:38:46.891Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:38:48.832Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:38:48.832Z] 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. [2025-09-25T00:38:48.832Z] The best model improves the baseline by 14.52%. [2025-09-25T00:38:48.832Z] Top recommended movies for user id 72: [2025-09-25T00:38:48.832Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:38:48.832Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:38:48.832Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:38:48.832Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:38:48.832Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:38:48.832Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17370.811 ms) ====== [2025-09-25T00:38:48.832Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-25T00:38:48.832Z] GC before operation: completed in 158.306 ms, heap usage 433.198 MB -> 89.015 MB. [2025-09-25T00:38:51.843Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:38:53.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:38:56.933Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:38:59.069Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:39:01.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:39:02.009Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:39:03.965Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:39:05.978Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:39:05.978Z] 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. [2025-09-25T00:39:05.978Z] The best model improves the baseline by 14.52%. [2025-09-25T00:39:05.978Z] Top recommended movies for user id 72: [2025-09-25T00:39:05.978Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:39:05.978Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:39:05.978Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:39:05.978Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:39:05.978Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:39:05.978Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17117.799 ms) ====== [2025-09-25T00:39:05.978Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-25T00:39:06.921Z] GC before operation: completed in 125.451 ms, heap usage 102.958 MB -> 89.218 MB. [2025-09-25T00:39:08.866Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:39:11.894Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:39:13.866Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:39:16.923Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:39:17.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:39:19.847Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:39:21.419Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:39:23.366Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:39:23.366Z] 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. [2025-09-25T00:39:23.366Z] The best model improves the baseline by 14.52%. [2025-09-25T00:39:23.366Z] Top recommended movies for user id 72: [2025-09-25T00:39:23.366Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:39:23.366Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:39:23.366Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:39:23.366Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:39:23.366Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:39:23.366Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17007.841 ms) ====== [2025-09-25T00:39:23.366Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-25T00:39:23.366Z] GC before operation: completed in 156.964 ms, heap usage 129.868 MB -> 89.568 MB. [2025-09-25T00:39:26.394Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:39:28.354Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:39:31.441Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:39:33.378Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:39:34.469Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:39:36.413Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:39:37.365Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:39:39.345Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:39:39.345Z] 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. [2025-09-25T00:39:39.345Z] The best model improves the baseline by 14.52%. [2025-09-25T00:39:39.345Z] Top recommended movies for user id 72: [2025-09-25T00:39:39.345Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:39:39.345Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:39:39.345Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:39:39.345Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:39:39.345Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:39:39.345Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15783.784 ms) ====== [2025-09-25T00:39:39.345Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-25T00:39:39.345Z] GC before operation: completed in 145.494 ms, heap usage 491.137 MB -> 90.066 MB. [2025-09-25T00:39:42.391Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:39:44.331Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:39:46.297Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:39:49.325Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:39:50.272Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:39:52.226Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:39:53.169Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:39:55.126Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:39:55.126Z] 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. [2025-09-25T00:39:55.126Z] The best model improves the baseline by 14.52%. [2025-09-25T00:39:55.126Z] Top recommended movies for user id 72: [2025-09-25T00:39:55.126Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:39:55.126Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:39:55.126Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:39:55.126Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:39:55.126Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:39:55.126Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15974.758 ms) ====== [2025-09-25T00:39:55.126Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-25T00:39:56.091Z] GC before operation: completed in 134.389 ms, heap usage 233.889 MB -> 90.006 MB. [2025-09-25T00:39:58.055Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:40:01.080Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:40:03.018Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:40:04.970Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:40:06.950Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:40:09.569Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:40:09.569Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:40:11.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:40:11.533Z] 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. [2025-09-25T00:40:11.533Z] The best model improves the baseline by 14.52%. [2025-09-25T00:40:11.533Z] Top recommended movies for user id 72: [2025-09-25T00:40:11.533Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:40:11.533Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:40:11.533Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:40:11.533Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:40:11.533Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:40:11.533Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16134.663 ms) ====== [2025-09-25T00:40:11.533Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-25T00:40:11.533Z] GC before operation: completed in 126.260 ms, heap usage 363.351 MB -> 90.238 MB. [2025-09-25T00:40:14.605Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:40:16.590Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:40:18.629Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:40:20.603Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:40:22.595Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:40:23.542Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:40:24.485Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:40:26.490Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:40:26.490Z] 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. [2025-09-25T00:40:26.490Z] The best model improves the baseline by 14.52%. [2025-09-25T00:40:26.490Z] Top recommended movies for user id 72: [2025-09-25T00:40:26.490Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:40:26.490Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:40:26.490Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:40:26.490Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:40:26.490Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:40:26.490Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14699.589 ms) ====== [2025-09-25T00:40:26.490Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-25T00:40:26.490Z] GC before operation: completed in 126.866 ms, heap usage 232.579 MB -> 90.147 MB. [2025-09-25T00:40:29.492Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:40:31.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:40:33.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:40:35.326Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:40:37.263Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:40:38.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:40:39.150Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:40:41.095Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:40:41.095Z] 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. [2025-09-25T00:40:41.095Z] The best model improves the baseline by 14.52%. [2025-09-25T00:40:41.095Z] Top recommended movies for user id 72: [2025-09-25T00:40:41.095Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:40:41.095Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:40:41.095Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:40:41.095Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:40:41.095Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:40:41.095Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14404.421 ms) ====== [2025-09-25T00:40:41.095Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-25T00:40:41.095Z] GC before operation: completed in 130.163 ms, heap usage 197.307 MB -> 90.010 MB. [2025-09-25T00:40:43.030Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:40:46.023Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:40:47.961Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:40:49.903Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:40:51.856Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:40:52.832Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:40:54.840Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:40:55.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:40:55.783Z] 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. [2025-09-25T00:40:55.783Z] The best model improves the baseline by 14.52%. [2025-09-25T00:40:58.065Z] Top recommended movies for user id 72: [2025-09-25T00:40:58.065Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:40:58.065Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:40:58.065Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:40:58.065Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:40:58.065Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:40:58.065Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15052.637 ms) ====== [2025-09-25T00:40:58.065Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-25T00:40:58.065Z] GC before operation: completed in 155.389 ms, heap usage 112.098 MB -> 90.120 MB. [2025-09-25T00:40:59.008Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:41:00.947Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:41:03.939Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:41:05.887Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:41:07.827Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:41:08.770Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:41:10.719Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:41:11.664Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:41:11.664Z] 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. [2025-09-25T00:41:12.617Z] The best model improves the baseline by 14.52%. [2025-09-25T00:41:12.617Z] Top recommended movies for user id 72: [2025-09-25T00:41:12.617Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:41:12.617Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:41:12.617Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:41:12.617Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:41:12.617Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:41:12.617Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15744.892 ms) ====== [2025-09-25T00:41:12.617Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-25T00:41:12.617Z] GC before operation: completed in 175.647 ms, heap usage 453.462 MB -> 90.258 MB. [2025-09-25T00:41:14.558Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:41:16.499Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:41:19.496Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:41:21.447Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:41:23.386Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:41:24.330Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:41:26.266Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:41:28.208Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:41:28.208Z] 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. [2025-09-25T00:41:28.208Z] The best model improves the baseline by 14.52%. [2025-09-25T00:41:28.208Z] Top recommended movies for user id 72: [2025-09-25T00:41:28.208Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:41:28.208Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:41:28.208Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:41:28.208Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:41:28.208Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:41:28.208Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15713.210 ms) ====== [2025-09-25T00:41:28.208Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-25T00:41:28.208Z] GC before operation: completed in 151.349 ms, heap usage 439.646 MB -> 90.492 MB. [2025-09-25T00:41:30.151Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:41:33.141Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:41:35.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:41:38.089Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:41:39.032Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:41:40.971Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:41:41.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:41:46.790Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:41:46.790Z] 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. [2025-09-25T00:41:46.790Z] The best model improves the baseline by 14.52%. [2025-09-25T00:41:46.790Z] Top recommended movies for user id 72: [2025-09-25T00:41:46.790Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:41:46.790Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:41:46.790Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:41:46.790Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:41:46.790Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:41:46.790Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15959.327 ms) ====== [2025-09-25T00:41:46.790Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-25T00:41:46.790Z] GC before operation: completed in 139.775 ms, heap usage 380.870 MB -> 90.483 MB. [2025-09-25T00:41:46.790Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:41:48.737Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:41:51.741Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:41:53.683Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:41:55.624Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:41:56.567Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:41:59.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:41:59.948Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:41:59.948Z] 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. [2025-09-25T00:41:59.948Z] The best model improves the baseline by 14.52%. [2025-09-25T00:42:00.899Z] Top recommended movies for user id 72: [2025-09-25T00:42:00.899Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:42:00.899Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:42:00.899Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:42:00.899Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:42:00.899Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:42:00.899Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16029.203 ms) ====== [2025-09-25T00:42:00.899Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-25T00:42:00.899Z] GC before operation: completed in 137.230 ms, heap usage 289.631 MB -> 90.235 MB. [2025-09-25T00:42:02.861Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:42:04.803Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:42:07.804Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:42:09.748Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:42:10.697Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:42:12.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:42:13.583Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:42:15.525Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:42:15.525Z] 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. [2025-09-25T00:42:15.525Z] The best model improves the baseline by 14.52%. [2025-09-25T00:42:15.525Z] Top recommended movies for user id 72: [2025-09-25T00:42:15.525Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:42:15.525Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:42:15.525Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:42:15.525Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:42:15.525Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:42:15.525Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15069.110 ms) ====== [2025-09-25T00:42:15.525Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-25T00:42:15.525Z] GC before operation: completed in 130.624 ms, heap usage 191.751 MB -> 90.327 MB. [2025-09-25T00:42:18.518Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:42:20.461Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:42:22.399Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:42:24.339Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:42:26.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:42:27.234Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:42:29.186Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:42:30.138Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:42:31.083Z] 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. [2025-09-25T00:42:31.083Z] The best model improves the baseline by 14.52%. [2025-09-25T00:42:31.083Z] Top recommended movies for user id 72: [2025-09-25T00:42:31.083Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:42:31.083Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:42:31.083Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:42:31.083Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:42:31.083Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:42:31.083Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15103.129 ms) ====== [2025-09-25T00:42:31.083Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-25T00:42:31.083Z] GC before operation: completed in 136.155 ms, heap usage 249.981 MB -> 90.244 MB. [2025-09-25T00:42:33.028Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:42:35.520Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:42:38.531Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:42:40.471Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:42:42.412Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:42:43.357Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:42:45.393Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:42:46.336Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:42:46.336Z] 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. [2025-09-25T00:42:46.336Z] The best model improves the baseline by 14.52%. [2025-09-25T00:42:47.280Z] Top recommended movies for user id 72: [2025-09-25T00:42:47.280Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:42:47.280Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:42:47.280Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:42:47.280Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:42:47.280Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:42:47.280Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15866.766 ms) ====== [2025-09-25T00:42:47.280Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-25T00:42:47.280Z] GC before operation: completed in 123.301 ms, heap usage 154.781 MB -> 90.162 MB. [2025-09-25T00:42:49.222Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:42:51.159Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:42:54.157Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:42:56.094Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:42:57.040Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:42:57.996Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:42:59.936Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:43:00.880Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:43:00.880Z] 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. [2025-09-25T00:43:00.880Z] The best model improves the baseline by 14.52%. [2025-09-25T00:43:01.822Z] Top recommended movies for user id 72: [2025-09-25T00:43:01.822Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:43:01.822Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:43:01.822Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:43:01.822Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:43:01.822Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:43:01.822Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14379.743 ms) ====== [2025-09-25T00:43:01.822Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-25T00:43:01.822Z] GC before operation: completed in 146.797 ms, heap usage 118.120 MB -> 91.787 MB. [2025-09-25T00:43:03.760Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:43:05.697Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:43:07.644Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:43:09.581Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:43:11.517Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:43:12.460Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:43:13.403Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:43:15.426Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:43:15.426Z] 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. [2025-09-25T00:43:15.426Z] The best model improves the baseline by 14.52%. [2025-09-25T00:43:15.426Z] Top recommended movies for user id 72: [2025-09-25T00:43:15.426Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:43:15.426Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:43:15.426Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:43:15.426Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:43:15.426Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:43:15.426Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13986.281 ms) ====== [2025-09-25T00:43:15.426Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-25T00:43:15.426Z] GC before operation: completed in 156.064 ms, heap usage 841.954 MB -> 94.489 MB. [2025-09-25T00:43:17.366Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T00:43:21.227Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T00:43:22.175Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T00:43:24.115Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T00:43:25.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T00:43:26.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T00:43:27.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T00:43:29.878Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T00:43:29.878Z] 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. [2025-09-25T00:43:29.878Z] The best model improves the baseline by 14.52%. [2025-09-25T00:43:29.878Z] Top recommended movies for user id 72: [2025-09-25T00:43:29.878Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-25T00:43:29.878Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-25T00:43:29.878Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-25T00:43:29.878Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-25T00:43:29.878Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-25T00:43:29.878Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14302.688 ms) ====== [2025-09-25T00:43:30.826Z] ----------------------------------- [2025-09-25T00:43:30.826Z] renaissance-movie-lens_0_PASSED [2025-09-25T00:43:30.826Z] ----------------------------------- [2025-09-25T00:43:30.826Z] [2025-09-25T00:43:30.826Z] TEST TEARDOWN: [2025-09-25T00:43:30.826Z] Nothing to be done for teardown. [2025-09-25T00:43:30.826Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 00:43:29 2025 Epoch Time (ms): 1758761010007