[2025-09-04T00:46:12.407Z] Running test renaissance-movie-lens_0 ... [2025-09-04T00:46:12.407Z] =============================================== [2025-09-04T00:46:12.407Z] renaissance-movie-lens_0 Start Time: Thu Sep 4 00:46:11 2025 Epoch Time (ms): 1756946771788 [2025-09-04T00:46:12.407Z] variation: NoOptions [2025-09-04T00:46:12.407Z] JVM_OPTIONS: [2025-09-04T00:46:12.407Z] { \ [2025-09-04T00:46:12.408Z] echo ""; echo "TEST SETUP:"; \ [2025-09-04T00:46:12.408Z] echo "Nothing to be done for setup."; \ [2025-09-04T00:46:12.408Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569450679783/renaissance-movie-lens_0"; \ [2025-09-04T00:46:12.408Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569450679783/renaissance-movie-lens_0"; \ [2025-09-04T00:46:12.408Z] echo ""; echo "TESTING:"; \ [2025-09-04T00:46:12.408Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/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_aarch64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569450679783/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-04T00:46:12.408Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569450679783/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-04T00:46:12.408Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-04T00:46:12.408Z] echo "Nothing to be done for teardown."; \ [2025-09-04T00:46:12.408Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569450679783/TestTargetResult"; [2025-09-04T00:46:12.408Z] [2025-09-04T00:46:12.408Z] TEST SETUP: [2025-09-04T00:46:12.408Z] Nothing to be done for setup. [2025-09-04T00:46:12.408Z] [2025-09-04T00:46:12.408Z] TESTING: [2025-09-04T00:46:28.259Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-04T00:46:56.979Z] 00:46:52.945 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-09-04T00:47:01.930Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-04T00:47:03.931Z] Training: 60056, validation: 20285, test: 19854 [2025-09-04T00:47:03.931Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-04T00:47:03.931Z] GC before operation: completed in 402.500 ms, heap usage 174.705 MB -> 76.199 MB. [2025-09-04T00:47:28.799Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:47:44.841Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:47:56.725Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:48:06.606Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:48:13.440Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:48:20.282Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:48:25.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:48:32.645Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:48:32.645Z] 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. [2025-09-04T00:48:33.614Z] The best model improves the baseline by 14.52%. [2025-09-04T00:48:33.614Z] Top recommended movies for user id 72: [2025-09-04T00:48:33.614Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:48:33.614Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:48:33.614Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:48:33.614Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:48:33.614Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:48:33.614Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (90202.898 ms) ====== [2025-09-04T00:48:33.614Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-04T00:48:34.587Z] GC before operation: completed in 435.108 ms, heap usage 322.241 MB -> 86.978 MB. [2025-09-04T00:48:45.266Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:48:53.560Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:49:03.425Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:49:11.688Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:49:15.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:49:20.087Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:49:25.602Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:49:29.826Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:49:30.794Z] 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. [2025-09-04T00:49:30.794Z] The best model improves the baseline by 14.52%. [2025-09-04T00:49:30.794Z] Top recommended movies for user id 72: [2025-09-04T00:49:30.794Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:49:30.794Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:49:30.794Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:49:30.794Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:49:30.794Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:49:30.794Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (56579.485 ms) ====== [2025-09-04T00:49:30.794Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-04T00:49:31.763Z] GC before operation: completed in 350.473 ms, heap usage 365.604 MB -> 89.175 MB. [2025-09-04T00:49:40.067Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:49:48.377Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:49:56.623Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:50:04.154Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:50:08.373Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:50:13.858Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:50:18.047Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:50:22.265Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:50:23.245Z] 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. [2025-09-04T00:50:23.245Z] The best model improves the baseline by 14.52%. [2025-09-04T00:50:24.422Z] Top recommended movies for user id 72: [2025-09-04T00:50:24.422Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:50:24.422Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:50:24.422Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:50:24.422Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:50:24.422Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:50:24.422Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (52564.732 ms) ====== [2025-09-04T00:50:24.422Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-04T00:50:24.422Z] GC before operation: completed in 492.334 ms, heap usage 489.629 MB -> 90.010 MB. [2025-09-04T00:50:32.692Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:50:39.611Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:50:47.878Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:50:54.675Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:51:00.131Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:51:04.394Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:51:09.847Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:51:14.067Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:51:15.038Z] 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. [2025-09-04T00:51:15.038Z] The best model improves the baseline by 14.52%. [2025-09-04T00:51:16.008Z] Top recommended movies for user id 72: [2025-09-04T00:51:16.008Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:51:16.008Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:51:16.008Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:51:16.008Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:51:16.008Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:51:16.008Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (51240.565 ms) ====== [2025-09-04T00:51:16.008Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-04T00:51:16.008Z] GC before operation: completed in 497.664 ms, heap usage 409.230 MB -> 90.142 MB. [2025-09-04T00:51:24.985Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:51:31.749Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:51:39.998Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:51:48.285Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:51:53.754Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:51:57.953Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:52:03.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:52:07.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:52:08.662Z] 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. [2025-09-04T00:52:08.662Z] The best model improves the baseline by 14.52%. [2025-09-04T00:52:09.627Z] Top recommended movies for user id 72: [2025-09-04T00:52:09.627Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:52:09.627Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:52:09.627Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:52:09.627Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:52:09.627Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:52:09.627Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (53053.218 ms) ====== [2025-09-04T00:52:09.627Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-04T00:52:09.627Z] GC before operation: completed in 353.280 ms, heap usage 184.746 MB -> 89.767 MB. [2025-09-04T00:52:17.911Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:52:24.750Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:52:31.533Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:52:39.771Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:52:44.801Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:52:49.022Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:52:54.485Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:52:58.878Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:52:59.844Z] 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. [2025-09-04T00:52:59.844Z] The best model improves the baseline by 14.52%. [2025-09-04T00:53:00.817Z] Top recommended movies for user id 72: [2025-09-04T00:53:00.817Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:53:00.817Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:53:00.817Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:53:00.817Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:53:00.817Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:53:00.817Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (50786.076 ms) ====== [2025-09-04T00:53:00.817Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-04T00:53:00.817Z] GC before operation: completed in 486.021 ms, heap usage 154.184 MB -> 90.043 MB. [2025-09-04T00:53:07.705Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:53:15.954Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:53:22.721Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:53:31.095Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:53:35.320Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:53:39.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:53:43.736Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:53:47.945Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:53:47.945Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-04T00:53:47.945Z] The best model improves the baseline by 14.52%. [2025-09-04T00:53:47.945Z] Top recommended movies for user id 72: [2025-09-04T00:53:47.945Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:53:47.945Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:53:47.945Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:53:47.945Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:53:47.945Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:53:47.945Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (47423.697 ms) ====== [2025-09-04T00:53:47.945Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-04T00:53:48.907Z] GC before operation: completed in 294.177 ms, heap usage 481.087 MB -> 90.528 MB. [2025-09-04T00:53:55.707Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:54:01.182Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:54:08.325Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:54:13.783Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:54:18.010Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:54:22.242Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:54:25.310Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:54:28.363Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:54:29.337Z] 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. [2025-09-04T00:54:29.337Z] The best model improves the baseline by 14.52%. [2025-09-04T00:54:30.302Z] Top recommended movies for user id 72: [2025-09-04T00:54:30.302Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:54:30.302Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:54:30.302Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:54:30.302Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:54:30.302Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:54:30.302Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (41243.158 ms) ====== [2025-09-04T00:54:30.302Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-04T00:54:30.302Z] GC before operation: completed in 320.787 ms, heap usage 292.385 MB -> 90.454 MB. [2025-09-04T00:54:35.743Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:54:42.719Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:54:48.167Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:54:53.658Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:54:56.731Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:55:00.924Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:55:03.966Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:55:07.025Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:55:07.025Z] 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. [2025-09-04T00:55:07.025Z] The best model improves the baseline by 14.52%. [2025-09-04T00:55:07.025Z] Top recommended movies for user id 72: [2025-09-04T00:55:07.025Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:55:07.025Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:55:07.025Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:55:07.025Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:55:07.025Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:55:07.025Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (37216.010 ms) ====== [2025-09-04T00:55:07.025Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-04T00:55:07.981Z] GC before operation: completed in 338.384 ms, heap usage 347.301 MB -> 90.330 MB. [2025-09-04T00:55:13.417Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:55:20.208Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:55:26.564Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:55:34.823Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:55:39.074Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:55:43.297Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:55:47.503Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:55:52.974Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:55:52.974Z] 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. [2025-09-04T00:55:52.974Z] The best model improves the baseline by 14.52%. [2025-09-04T00:55:53.941Z] Top recommended movies for user id 72: [2025-09-04T00:55:53.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:55:53.941Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:55:53.941Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:55:53.941Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:55:53.941Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:55:53.941Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (45991.464 ms) ====== [2025-09-04T00:55:53.941Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-04T00:55:53.941Z] GC before operation: completed in 400.052 ms, heap usage 451.069 MB -> 90.737 MB. [2025-09-04T00:56:02.190Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:56:08.990Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:56:15.778Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:56:22.580Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:56:26.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:56:31.119Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:56:36.578Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:56:41.504Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:56:41.504Z] 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. [2025-09-04T00:56:41.504Z] The best model improves the baseline by 14.52%. [2025-09-04T00:56:42.469Z] Top recommended movies for user id 72: [2025-09-04T00:56:42.469Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:56:42.469Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:56:42.469Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:56:42.469Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:56:42.469Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:56:42.469Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (48069.626 ms) ====== [2025-09-04T00:56:42.469Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-04T00:56:42.469Z] GC before operation: completed in 498.548 ms, heap usage 432.114 MB -> 90.398 MB. [2025-09-04T00:56:50.745Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:56:56.215Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:57:04.478Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:57:09.938Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:57:14.150Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:57:18.369Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:57:22.562Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:57:25.732Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:57:26.701Z] 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. [2025-09-04T00:57:26.701Z] The best model improves the baseline by 14.52%. [2025-09-04T00:57:26.701Z] Top recommended movies for user id 72: [2025-09-04T00:57:26.701Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:57:26.701Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:57:26.701Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:57:26.701Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:57:26.701Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:57:26.701Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (44335.033 ms) ====== [2025-09-04T00:57:26.701Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-04T00:57:27.660Z] GC before operation: completed in 332.705 ms, heap usage 185.181 MB -> 90.332 MB. [2025-09-04T00:57:33.107Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:57:38.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:57:45.380Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:57:52.166Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:57:55.225Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:57:59.614Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:58:04.250Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:58:07.323Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:58:08.291Z] 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. [2025-09-04T00:58:08.291Z] The best model improves the baseline by 14.52%. [2025-09-04T00:58:09.258Z] Top recommended movies for user id 72: [2025-09-04T00:58:09.258Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:58:09.258Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:58:09.258Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:58:09.258Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:58:09.258Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:58:09.258Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (41426.753 ms) ====== [2025-09-04T00:58:09.258Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-04T00:58:09.258Z] GC before operation: completed in 342.514 ms, heap usage 541.496 MB -> 90.969 MB. [2025-09-04T00:58:17.516Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:58:22.979Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:58:29.820Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:58:35.285Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:58:39.512Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:58:43.762Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:58:46.833Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:58:51.074Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:58:52.042Z] 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. [2025-09-04T00:58:52.042Z] The best model improves the baseline by 14.52%. [2025-09-04T00:58:52.042Z] Top recommended movies for user id 72: [2025-09-04T00:58:52.042Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:58:52.042Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:58:52.042Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:58:52.042Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:58:52.042Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:58:52.042Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (43073.214 ms) ====== [2025-09-04T00:58:52.042Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-04T00:58:53.012Z] GC before operation: completed in 462.606 ms, heap usage 638.634 MB -> 94.071 MB. [2025-09-04T00:58:59.818Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:59:05.272Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:59:10.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:59:16.175Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:59:19.235Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T00:59:24.234Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T00:59:27.297Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T00:59:30.360Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T00:59:31.318Z] 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. [2025-09-04T00:59:31.318Z] The best model improves the baseline by 14.52%. [2025-09-04T00:59:31.318Z] Top recommended movies for user id 72: [2025-09-04T00:59:31.318Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T00:59:31.318Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T00:59:31.318Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T00:59:31.318Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T00:59:31.318Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T00:59:31.318Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (39074.336 ms) ====== [2025-09-04T00:59:31.318Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-04T00:59:32.274Z] GC before operation: completed in 340.195 ms, heap usage 545.164 MB -> 90.992 MB. [2025-09-04T00:59:39.069Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T00:59:44.523Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T00:59:49.944Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T00:59:56.710Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T00:59:59.782Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T01:00:02.893Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T01:00:08.377Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T01:00:11.459Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T01:00:12.440Z] 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. [2025-09-04T01:00:12.440Z] The best model improves the baseline by 14.52%. [2025-09-04T01:00:13.412Z] Top recommended movies for user id 72: [2025-09-04T01:00:13.412Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T01:00:13.412Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T01:00:13.412Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T01:00:13.412Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T01:00:13.412Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T01:00:13.412Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (41067.794 ms) ====== [2025-09-04T01:00:13.412Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-04T01:00:13.412Z] GC before operation: completed in 465.826 ms, heap usage 417.767 MB -> 90.630 MB. [2025-09-04T01:00:21.666Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T01:00:26.026Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T01:00:31.497Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T01:00:35.681Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T01:00:38.350Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T01:00:41.446Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T01:00:44.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T01:00:46.451Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T01:00:47.433Z] 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. [2025-09-04T01:00:47.433Z] The best model improves the baseline by 14.52%. [2025-09-04T01:00:47.433Z] Top recommended movies for user id 72: [2025-09-04T01:00:47.433Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T01:00:47.433Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T01:00:47.433Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T01:00:47.433Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T01:00:47.433Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T01:00:47.433Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (34174.965 ms) ====== [2025-09-04T01:00:47.433Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-04T01:00:48.391Z] GC before operation: completed in 278.565 ms, heap usage 245.911 MB -> 90.641 MB. [2025-09-04T01:00:52.587Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T01:00:59.362Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T01:01:03.310Z] test-docker-ubuntu2404-armv8-4 seems to be removed or offline (java.io.IOException: SSH channel is closed); will wait for 5 min 0 sec for it to come back online [2025-09-04T01:05:08.652Z] test-docker-ubuntu2404-armv8-4 is back online [2025-09-04T01:10:33.129Z] wrapper script does not seem to be touching the log file in /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1@tmp/durable-639c29b5 [2025-09-04T01:10:33.129Z] (JENKINS-48300: if on an extremely laggy filesystem, consider -Dorg.jenkinsci.plugins.durabletask.BourneShellScript.HEARTBEAT_CHECK_INTERVAL=86400) [Pipeline] sh [2025-09-04T01:10:45.328Z] + uname [2025-09-04T01:10:45.328Z] + [ Linux = AIX ] [2025-09-04T01:10:45.328Z] + uname [2025-09-04T01:10:45.328Z] + [ Linux = SunOS ] [2025-09-04T01:10:45.328Z] + uname [2025-09-04T01:10:45.328Z] + [ Linux = *BSD ] [2025-09-04T01:10:45.328Z] + MAKE=make [2025-09-04T01:10:45.328Z] + make -f ./aqa-tests/TKG/testEnv.mk testEnvTeardown [2025-09-04T01:10:45.328Z] make: Nothing to be done for 'testEnvTeardown'. [Pipeline] } [2025-09-04T01:10:45.986Z] $ ssh-agent -k [2025-09-04T01:10:46.007Z] kill: No such process [Pipeline] // sshagent [Pipeline] } [2025-09-04T01:10:46.863Z] Xvfb stopping [Pipeline] // wrap [Pipeline] } [Pipeline] // stage [Pipeline] stage [Pipeline] { (Post) [Pipeline] echo [2025-09-04T01:10:48.127Z] Saving aqa-tests/testenv/testenv.properties file on jenkins. [Pipeline] archiveArtifacts [2025-09-04T01:10:48.317Z] Archiving artifacts [2025-09-04T01:11:03.194Z] Recording fingerprints [Pipeline] echo [2025-09-04T01:11:03.835Z] Saving aqa-tests/TKG/**/*.tap file on jenkins. [Pipeline] archiveArtifacts [2025-09-04T01:11:04.025Z] Archiving artifacts [2025-09-04T01:11:05.348Z] No artifacts found that match the file pattern "aqa-tests/TKG/**/*.tap". Configuration error? [Pipeline] sh [2025-09-04T01:11:07.413Z] + tar -cf benchmark_test_output.tar.gz ./aqa-tests/TKG/output_17569450679783 [Pipeline] echo [2025-09-04T01:11:07.953Z] ARTIFACTORY_SERVER is not set. Saving artifacts on jenkins. [Pipeline] archiveArtifacts [2025-09-04T01:11:08.139Z] Archiving artifacts [2025-09-04T01:12:04.470Z] Recording fingerprints [Pipeline] findFiles [Pipeline] junit [2025-09-04T01:12:07.060Z] Recording test results [2025-09-04T01:12:11.108Z] No test report files were found. Configuration error? [2025-09-04T01:12:17.568Z] None of the test reports contained any result [2025-09-04T01:12:17.569Z] [Checks API] No suitable checks publisher found. [Pipeline] } [Pipeline] // stage [Pipeline] echo [2025-09-04T01:12:17.596Z] PROCESSCATCH: Terminating any hung/left over test processes: [Pipeline] sh [2025-09-04T01:12:19.637Z] + aqa-tests/terminateTestProcesses.sh jenkins [2025-09-04T01:12:19.637Z] Unix type machine.. [2025-09-04T01:12:19.637Z] Running on a Linux host [2025-09-04T01:12:19.637Z] Woohoo - no rogue processes detected! [Pipeline] cleanWs [2025-09-04T01:12:20.540Z] [WS-CLEANUP] Deleting project workspace... [2025-09-04T01:12:20.541Z] [WS-CLEANUP] Deferred wipeout is disabled by the job configuration... [2025-09-04T01:12:27.222Z] [WS-CLEANUP] done [Pipeline] sh [2025-09-04T01:12:29.268Z] + find /tmp -name *core* -print -exec rm -f {} ; [Pipeline] } [Pipeline] // timeout [Pipeline] echo [2025-09-04T01:12:32.877Z] Exception: hudson.AbortException: Failed to run ssh-agent -k [Pipeline] timeout [2025-09-04T01:12:32.881Z] Timeout set to expire in 5 min 0 sec [Pipeline] { [Pipeline] echo [2025-09-04T01:12:32.905Z] Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1 #12 result is FAILURE. Checking console log for specific errors... [Pipeline] } [Pipeline] // timeout [Pipeline] } [Pipeline] // node [Pipeline] } [Pipeline] // stage [Pipeline] } [Pipeline] // timestamps [Pipeline] End of Pipeline Finished: FAILURE