[2026-03-04T23:18:29.543Z] Running test renaissance-movie-lens_0 ... [2026-03-04T23:18:29.543Z] =============================================== [2026-03-04T23:18:29.543Z] renaissance-movie-lens_0 Start Time: Wed Mar 4 23:18:28 2026 Epoch Time (ms): 1772666308543 [2026-03-04T23:18:29.543Z] variation: NoOptions [2026-03-04T23:18:29.543Z] JVM_OPTIONS: [2026-03-04T23:18:29.543Z] { \ [2026-03-04T23:18:29.543Z] echo ""; echo "TEST SETUP:"; \ [2026-03-04T23:18:29.543Z] echo "Nothing to be done for setup."; \ [2026-03-04T23:18:29.543Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1772665439678/renaissance-movie-lens_0"; \ [2026-03-04T23:18:29.543Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1772665439678/renaissance-movie-lens_0"; \ [2026-03-04T23:18:29.543Z] echo ""; echo "TESTING:"; \ [2026-03-04T23:18:29.543Z] "/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_1772665439678/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2026-03-04T23:18:29.544Z] 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_1772665439678/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2026-03-04T23:18:29.544Z] echo ""; echo "TEST TEARDOWN:"; \ [2026-03-04T23:18:29.544Z] echo "Nothing to be done for teardown."; \ [2026-03-04T23:18:29.544Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1772665439678/TestTargetResult"; [2026-03-04T23:18:29.544Z] [2026-03-04T23:18:29.544Z] TEST SETUP: [2026-03-04T23:18:29.544Z] Nothing to be done for setup. [2026-03-04T23:18:29.544Z] [2026-03-04T23:18:29.544Z] TESTING: [2026-03-04T23:18:33.761Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2026-03-04T23:18:40.462Z] 23:18:40.063 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2026-03-04T23:18:43.986Z] Got 100004 ratings from 671 users on 9066 movies. [2026-03-04T23:18:45.805Z] Training: 60056, validation: 20285, test: 19854 [2026-03-04T23:18:45.805Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2026-03-04T23:18:45.805Z] GC before operation: completed in 140.941 ms, heap usage 180.607 MB -> 75.984 MB. [2026-03-04T23:18:47.758Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:18:50.788Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:18:53.806Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:18:56.935Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:18:58.888Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:18:59.842Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:19:01.796Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:19:02.927Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:19:03.880Z] 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. [2026-03-04T23:19:03.880Z] The best model improves the baseline by 14.52%. [2026-03-04T23:19:03.880Z] Top recommended movies for user id 72: [2026-03-04T23:19:03.880Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:19:03.880Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:19:03.880Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:19:03.880Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:19:03.880Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:19:03.880Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20746.235 ms) ====== [2026-03-04T23:19:03.880Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2026-03-04T23:19:03.880Z] GC before operation: completed in 157.525 ms, heap usage 192.421 MB -> 88.756 MB. [2026-03-04T23:19:07.072Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:19:09.031Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:19:10.991Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:19:14.011Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:19:14.962Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:19:16.920Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:19:17.874Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:19:19.831Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:19:19.831Z] 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. [2026-03-04T23:19:19.831Z] The best model improves the baseline by 14.52%. [2026-03-04T23:19:19.831Z] Top recommended movies for user id 72: [2026-03-04T23:19:19.831Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:19:19.831Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:19:19.831Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:19:19.831Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:19:19.831Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:19:19.831Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15968.989 ms) ====== [2026-03-04T23:19:19.831Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2026-03-04T23:19:19.831Z] GC before operation: completed in 141.229 ms, heap usage 472.153 MB -> 89.361 MB. [2026-03-04T23:19:22.846Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:19:24.800Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:19:26.753Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:19:29.775Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:19:30.740Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:19:31.773Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:19:34.920Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:19:34.920Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:19:34.920Z] 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. [2026-03-04T23:19:34.920Z] The best model improves the baseline by 14.52%. [2026-03-04T23:19:35.879Z] Top recommended movies for user id 72: [2026-03-04T23:19:35.879Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:19:35.879Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:19:35.879Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:19:35.879Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:19:35.879Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:19:35.879Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15301.410 ms) ====== [2026-03-04T23:19:35.879Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2026-03-04T23:19:35.879Z] GC before operation: completed in 131.714 ms, heap usage 241.979 MB -> 89.519 MB. [2026-03-04T23:19:37.843Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:19:39.815Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:19:42.927Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:19:44.884Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:19:45.835Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:19:47.788Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:19:48.741Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:19:50.695Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:19:50.695Z] 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. [2026-03-04T23:19:50.695Z] The best model improves the baseline by 14.52%. [2026-03-04T23:19:50.695Z] Top recommended movies for user id 72: [2026-03-04T23:19:50.695Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:19:50.695Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:19:50.695Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:19:50.695Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:19:50.695Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:19:50.695Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15067.897 ms) ====== [2026-03-04T23:19:50.695Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2026-03-04T23:19:50.695Z] GC before operation: completed in 133.603 ms, heap usage 250.265 MB -> 89.824 MB. [2026-03-04T23:19:52.649Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:19:55.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:19:57.628Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:19:59.584Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:20:01.539Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:20:02.496Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:20:03.448Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:20:05.402Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:20:05.402Z] 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. [2026-03-04T23:20:05.402Z] The best model improves the baseline by 14.52%. [2026-03-04T23:20:05.402Z] Top recommended movies for user id 72: [2026-03-04T23:20:05.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:20:05.402Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:20:05.402Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:20:05.402Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:20:05.402Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:20:05.402Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14826.538 ms) ====== [2026-03-04T23:20:05.402Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2026-03-04T23:20:05.402Z] GC before operation: completed in 115.820 ms, heap usage 294.342 MB -> 89.901 MB. [2026-03-04T23:20:08.423Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:20:10.378Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:20:12.332Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:20:15.348Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:20:16.302Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:20:17.254Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:20:19.210Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:20:20.167Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:20:23.299Z] 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. [2026-03-04T23:20:23.299Z] The best model improves the baseline by 14.52%. [2026-03-04T23:20:23.299Z] Top recommended movies for user id 72: [2026-03-04T23:20:23.299Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:20:23.299Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:20:23.299Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:20:23.299Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:20:23.299Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:20:23.299Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15083.517 ms) ====== [2026-03-04T23:20:23.299Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2026-03-04T23:20:23.299Z] GC before operation: completed in 106.750 ms, heap usage 287.058 MB -> 90.265 MB. [2026-03-04T23:20:23.299Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:20:25.254Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:20:27.237Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:20:30.253Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:20:31.205Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:20:32.157Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:20:34.114Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:20:35.065Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:20:36.016Z] 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. [2026-03-04T23:20:36.016Z] The best model improves the baseline by 14.52%. [2026-03-04T23:20:36.016Z] Top recommended movies for user id 72: [2026-03-04T23:20:36.016Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:20:36.016Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:20:36.016Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:20:36.016Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:20:36.016Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:20:36.016Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14943.842 ms) ====== [2026-03-04T23:20:36.016Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2026-03-04T23:20:36.016Z] GC before operation: completed in 125.047 ms, heap usage 211.662 MB -> 90.083 MB. [2026-03-04T23:20:37.970Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:20:40.989Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:20:42.944Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:20:44.899Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:20:46.854Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:20:47.809Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:20:48.760Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:20:50.715Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:20:50.715Z] 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. [2026-03-04T23:20:50.715Z] The best model improves the baseline by 14.52%. [2026-03-04T23:20:50.715Z] Top recommended movies for user id 72: [2026-03-04T23:20:50.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:20:50.715Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:20:50.715Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:20:50.715Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:20:50.715Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:20:50.715Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15057.965 ms) ====== [2026-03-04T23:20:50.715Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2026-03-04T23:20:51.666Z] GC before operation: completed in 110.857 ms, heap usage 117.883 MB -> 90.162 MB. [2026-03-04T23:20:53.621Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:20:55.605Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:20:57.817Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:21:27.018Z] test-osuosl-centos74-ppc64le-1 seems to be removed or offline (java.lang.InterruptedException); will wait for 5 min 0 sec for it to come back online [2026-03-04T23:21:27.318Z] test-osuosl-centos74-ppc64le-1 is back online [2026-03-04T23:21:47.319Z] test-osuosl-centos74-ppc64le-1 seems to be removed or offline (java.lang.InterruptedException); will wait for 5 min 0 sec for it to come back online [2026-03-04T23:21:48.494Z] test-osuosl-centos74-ppc64le-1 is back online [2026-03-04T23:22:08.496Z] test-osuosl-centos74-ppc64le-1 seems to be removed or offline (java.lang.InterruptedException); will wait for 5 min 0 sec for it to come back online [2026-03-04T23:22:08.796Z] test-osuosl-centos74-ppc64le-1 is back online [2026-03-04T23:22:28.797Z] test-osuosl-centos74-ppc64le-1 seems to be removed or offline (java.lang.InterruptedException); will wait for 5 min 0 sec for it to come back online [2026-03-04T23:22:29.098Z] test-osuosl-centos74-ppc64le-1 is back online [2026-03-04T23:22:32.114Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:32.114Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:32.114Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:32.114Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:32.114Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:32.114Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2026-03-04T23:22:32.114Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:32.114Z] Top recommended movies for user id 72: [2026-03-04T23:22:32.114Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:32.114Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:32.114Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:32.114Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:32.114Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:32.114Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14170.226 ms) ====== [2026-03-04T23:22:32.114Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2026-03-04T23:22:32.114Z] GC before operation: completed in 122.906 ms, heap usage 400.842 MB -> 90.349 MB. [2026-03-04T23:22:32.114Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:32.114Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:32.114Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:32.114Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:32.114Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:32.114Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:32.114Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:32.114Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:32.114Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2026-03-04T23:22:32.114Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:32.114Z] Top recommended movies for user id 72: [2026-03-04T23:22:32.114Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:32.114Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:32.114Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:32.114Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:32.114Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:32.114Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13672.323 ms) ====== [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2026-03-04T23:22:32.115Z] GC before operation: completed in 107.815 ms, heap usage 424.033 MB -> 90.641 MB. [2026-03-04T23:22:32.115Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:32.115Z] 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. [2026-03-04T23:22:32.115Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:32.115Z] Top recommended movies for user id 72: [2026-03-04T23:22:32.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:32.115Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:32.115Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:32.115Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:32.115Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14784.597 ms) ====== [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2026-03-04T23:22:32.115Z] GC before operation: completed in 108.918 ms, heap usage 467.958 MB -> 90.459 MB. [2026-03-04T23:22:32.115Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:32.115Z] 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. [2026-03-04T23:22:32.115Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:32.115Z] Top recommended movies for user id 72: [2026-03-04T23:22:32.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:32.115Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:32.115Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:32.115Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:32.115Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13893.644 ms) ====== [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2026-03-04T23:22:32.115Z] GC before operation: completed in 108.431 ms, heap usage 360.315 MB -> 90.475 MB. [2026-03-04T23:22:32.115Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:32.115Z] 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. [2026-03-04T23:22:32.115Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:32.115Z] Top recommended movies for user id 72: [2026-03-04T23:22:32.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:32.115Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:32.115Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:32.115Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:32.115Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15083.506 ms) ====== [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2026-03-04T23:22:32.115Z] GC before operation: completed in 107.674 ms, heap usage 129.929 MB -> 90.194 MB. [2026-03-04T23:22:32.115Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:32.115Z] 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. [2026-03-04T23:22:32.115Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:32.115Z] Top recommended movies for user id 72: [2026-03-04T23:22:32.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:32.115Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:32.115Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:32.115Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:32.115Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13848.099 ms) ====== [2026-03-04T23:22:32.115Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2026-03-04T23:22:32.115Z] GC before operation: completed in 108.605 ms, heap usage 413.028 MB -> 90.456 MB. [2026-03-04T23:22:32.115Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:32.115Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:32.116Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:32.116Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:32.116Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:32.116Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:32.116Z] 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. [2026-03-04T23:22:32.116Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:32.116Z] Top recommended movies for user id 72: [2026-03-04T23:22:32.116Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:32.116Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:32.116Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:32.116Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:32.116Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:32.116Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14510.928 ms) ====== [2026-03-04T23:22:32.116Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2026-03-04T23:22:32.116Z] GC before operation: completed in 109.308 ms, heap usage 132.939 MB -> 90.414 MB. [2026-03-04T23:22:34.073Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:36.029Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:42.070Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:42.070Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:43.023Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:43.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:44.982Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:22:45.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:22:45.934Z] 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. [2026-03-04T23:22:45.934Z] The best model improves the baseline by 14.52%. [2026-03-04T23:22:45.934Z] Top recommended movies for user id 72: [2026-03-04T23:22:45.934Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:22:45.934Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:22:45.934Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:22:45.934Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:22:45.934Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:22:45.934Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14381.194 ms) ====== [2026-03-04T23:22:45.934Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2026-03-04T23:22:46.886Z] GC before operation: completed in 123.142 ms, heap usage 311.206 MB -> 90.435 MB. [2026-03-04T23:22:48.839Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:22:50.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:22:52.747Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:22:54.703Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:22:56.658Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:22:57.612Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:22:59.571Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:23:00.525Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:23:00.525Z] 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. [2026-03-04T23:23:00.525Z] The best model improves the baseline by 14.52%. [2026-03-04T23:23:00.525Z] Top recommended movies for user id 72: [2026-03-04T23:23:00.525Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:23:00.525Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:23:00.525Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:23:00.525Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:23:00.525Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:23:00.525Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14480.466 ms) ====== [2026-03-04T23:23:00.525Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2026-03-04T23:23:01.509Z] GC before operation: completed in 131.842 ms, heap usage 338.231 MB -> 90.618 MB. [2026-03-04T23:23:03.464Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:23:05.422Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:23:07.380Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:23:10.398Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:23:11.351Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:23:12.305Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:23:13.261Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:23:15.219Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:23:15.219Z] 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. [2026-03-04T23:23:15.219Z] The best model improves the baseline by 14.52%. [2026-03-04T23:23:15.219Z] Top recommended movies for user id 72: [2026-03-04T23:23:15.219Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:23:15.219Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:23:15.219Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:23:15.219Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:23:15.219Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:23:15.219Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14203.738 ms) ====== [2026-03-04T23:23:15.219Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2026-03-04T23:23:15.219Z] GC before operation: completed in 118.576 ms, heap usage 712.002 MB -> 94.129 MB. [2026-03-04T23:23:17.179Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:23:20.200Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:23:22.157Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:23:24.143Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:23:25.096Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:23:27.051Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:23:28.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:23:31.532Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:23:31.532Z] 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. [2026-03-04T23:23:31.532Z] The best model improves the baseline by 14.52%. [2026-03-04T23:23:31.532Z] Top recommended movies for user id 72: [2026-03-04T23:23:31.532Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:23:31.532Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:23:31.532Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:23:31.532Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:23:31.532Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:23:31.532Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14516.603 ms) ====== [2026-03-04T23:23:31.532Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2026-03-04T23:23:31.532Z] GC before operation: completed in 120.880 ms, heap usage 618.930 MB -> 94.116 MB. [2026-03-04T23:23:33.461Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-03-04T23:23:34.416Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-03-04T23:23:36.372Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-03-04T23:23:38.383Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-03-04T23:23:40.341Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-03-04T23:23:41.294Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-03-04T23:23:43.251Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-03-04T23:23:44.205Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-03-04T23:23:44.205Z] 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. [2026-03-04T23:23:44.205Z] The best model improves the baseline by 14.52%. [2026-03-04T23:23:45.159Z] Top recommended movies for user id 72: [2026-03-04T23:23:45.159Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-03-04T23:23:45.159Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-03-04T23:23:45.159Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-03-04T23:23:45.159Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-03-04T23:23:45.159Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-03-04T23:23:45.159Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14702.243 ms) ====== [2026-03-04T23:23:45.159Z] ----------------------------------- [2026-03-04T23:23:45.159Z] renaissance-movie-lens_0_PASSED [2026-03-04T23:23:45.159Z] ----------------------------------- [2026-03-04T23:23:45.159Z] [2026-03-04T23:23:45.159Z] TEST TEARDOWN: [2026-03-04T23:23:45.159Z] Nothing to be done for teardown. [2026-03-04T23:23:45.159Z] renaissance-movie-lens_0 Finish Time: Wed Mar 4 23:23:44 2026 Epoch Time (ms): 1772666624752