[2025-06-27T01:11:19.814Z] Running test renaissance-movie-lens_0 ... [2025-06-27T01:11:19.814Z] =============================================== [2025-06-27T01:11:19.814Z] renaissance-movie-lens_0 Start Time: Fri Jun 27 01:11:19 2025 Epoch Time (ms): 1750986679788 [2025-06-27T01:11:19.814Z] variation: NoOptions [2025-06-27T01:11:20.151Z] JVM_OPTIONS: [2025-06-27T01:11:20.151Z] { \ [2025-06-27T01:11:20.151Z] echo ""; echo "TEST SETUP:"; \ [2025-06-27T01:11:20.151Z] echo "Nothing to be done for setup."; \ [2025-06-27T01:11:20.151Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17509816891623/renaissance-movie-lens_0"; \ [2025-06-27T01:11:20.151Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17509816891623/renaissance-movie-lens_0"; \ [2025-06-27T01:11:20.151Z] echo ""; echo "TESTING:"; \ [2025-06-27T01:11:20.151Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_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_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17509816891623/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-27T01:11:20.151Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17509816891623/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-27T01:11:20.151Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-27T01:11:20.151Z] echo "Nothing to be done for teardown."; \ [2025-06-27T01:11:20.151Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17509816891623/TestTargetResult"; [2025-06-27T01:11:20.151Z] [2025-06-27T01:11:20.151Z] TEST SETUP: [2025-06-27T01:11:20.151Z] Nothing to be done for setup. [2025-06-27T01:11:20.151Z] [2025-06-27T01:11:20.151Z] TESTING: [2025-06-27T01:11:22.390Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-06-27T01:11:22.390Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/output_17509816891623/renaissance-movie-lens_0/launcher-011120-11734479232036284268/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-06-27T01:11:22.390Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-06-27T01:11:22.390Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-06-27T01:11:45.523Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-27T01:12:18.869Z] 01:12:13.586 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-27T01:12:22.667Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-27T01:12:24.924Z] Training: 60056, validation: 20285, test: 19854 [2025-06-27T01:12:24.924Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-27T01:12:25.635Z] GC before operation: completed in 667.990 ms, heap usage 341.416 MB -> 75.964 MB. [2025-06-27T01:12:53.801Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T01:13:04.599Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T01:13:17.743Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T01:13:28.786Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T01:13:34.673Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T01:13:40.559Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T01:13:47.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T01:13:52.581Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T01:13:53.741Z] 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. [2025-06-27T01:13:53.741Z] The best model improves the baseline by 14.52%. [2025-06-27T01:13:54.885Z] Top recommended movies for user id 72: [2025-06-27T01:13:54.885Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T01:13:54.885Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T01:13:54.885Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T01:13:54.885Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T01:13:54.885Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T01:13:54.885Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (89277.395 ms) ====== [2025-06-27T01:13:54.885Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-27T01:13:56.051Z] GC before operation: completed in 1084.188 ms, heap usage 907.605 MB -> 93.196 MB. [2025-06-27T01:14:07.837Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T01:14:16.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T01:14:25.623Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T01:14:36.415Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T01:14:41.244Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T01:14:47.131Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T01:14:53.018Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T01:14:59.022Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T01:14:59.351Z] 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. [2025-06-27T01:14:59.351Z] The best model improves the baseline by 14.52%. [2025-06-27T01:15:00.061Z] Top recommended movies for user id 72: [2025-06-27T01:15:00.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T01:15:00.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T01:15:00.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T01:15:00.061Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T01:15:00.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T01:15:00.061Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (64327.174 ms) ====== [2025-06-27T01:15:00.061Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-27T01:15:01.230Z] GC before operation: completed in 961.099 ms, heap usage 1.392 GB -> 94.491 MB. [2025-06-27T01:15:12.122Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T01:15:22.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T01:15:31.801Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T01:15:40.669Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T01:15:46.567Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T01:15:52.440Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T01:15:58.318Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T01:16:03.042Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T01:16:04.701Z] 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. [2025-06-27T01:16:04.701Z] The best model improves the baseline by 14.52%. [2025-06-27T01:16:05.415Z] Top recommended movies for user id 72: [2025-06-27T01:16:05.415Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T01:16:05.415Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T01:16:05.415Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T01:16:05.415Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T01:16:05.415Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T01:16:05.415Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (64144.402 ms) ====== [2025-06-27T01:16:05.415Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-27T01:16:06.141Z] GC before operation: completed in 849.476 ms, heap usage 428.012 MB -> 89.404 MB. [2025-06-27T01:16:16.949Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T01:16:24.282Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T01:16:33.144Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T01:16:41.993Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T01:16:47.890Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T01:16:53.756Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T01:16:59.654Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T01:17:04.559Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T01:17:05.700Z] 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. [2025-06-27T01:17:05.700Z] The best model improves the baseline by 14.52%. [2025-06-27T01:17:06.432Z] Top recommended movies for user id 72: [2025-06-27T01:17:06.432Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T01:17:06.432Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T01:17:06.432Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T01:17:06.432Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T01:17:06.432Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T01:17:06.432Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60159.824 ms) ====== [2025-06-27T01:17:06.432Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-27T01:17:07.169Z] GC before operation: completed in 868.778 ms, heap usage 189.962 MB -> 89.473 MB. [2025-06-27T01:17:16.127Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T01:17:24.977Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T01:17:35.789Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T01:17:43.093Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T01:17:49.030Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T01:17:54.905Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T01:17:59.653Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T01:18:05.596Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T01:18:05.924Z] 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. [2025-06-27T01:18:05.925Z] The best model improves the baseline by 14.52%. [2025-06-27T01:18:07.072Z] Top recommended movies for user id 72: [2025-06-27T01:18:07.072Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T01:18:07.072Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T01:18:07.072Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T01:18:07.072Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T01:18:07.072Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T01:18:07.072Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (59628.922 ms) ====== [2025-06-27T01:18:07.072Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-27T01:18:07.801Z] GC before operation: completed in 878.654 ms, heap usage 371.817 MB -> 89.775 MB. [2025-06-27T01:18:16.695Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T01:18:25.978Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T01:18:35.090Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T01:18:43.953Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T01:18:48.725Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T01:18:53.473Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T01:18:59.391Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T01:19:04.145Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T01:19:04.845Z] 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. [2025-06-27T01:19:05.168Z] The best model improves the baseline by 14.52%. [2025-06-27T01:19:05.495Z] Top recommended movies for user id 72: [2025-06-27T01:19:05.495Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T01:19:05.495Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T01:19:05.495Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T01:19:05.495Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T01:19:05.495Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T01:19:05.495Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57898.134 ms) ====== [2025-06-27T01:19:05.495Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-27T01:19:06.671Z] GC before operation: completed in 862.364 ms, heap usage 499.248 MB -> 90.256 MB. [2025-06-27T01:19:17.204Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T01:19:23.070Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T01:19:32.033Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T01:19:40.885Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T01:19:44.658Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T01:19:50.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T01:19:56.414Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T00:39:29.184Z] Cancelling nested steps due to timeout [2025-06-28T00:39:29.207Z] Sending interrupt signal to process [2025-06-28T00:39:44.171Z] Terminated [2025-06-28T00:39:44.171Z] make[4]: *** [autoGen.mk:270: renaissance-movie-lens_0] Error 143 [2025-06-28T00:39:44.171Z] make[4]: Leaving directory '/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/perf/renaissance' [2025-06-28T00:39:44.171Z] make[3]: *** [/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/settings.mk:362: extended.perf-renaissance] Error 2 [2025-06-28T00:39:44.171Z] make[3]: Leaving directory '/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/perf' [2025-06-28T00:39:44.171Z] make[2]: *** [/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/settings.mk:362: extended.perf-perf] Error 2 [2025-06-28T00:39:44.171Z] make[2]: Leaving directory '/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests' [2025-06-28T00:39:44.171Z] make[1]: *** [settings.mk:362: extended.perf-..] Error 2 [2025-06-28T00:39:44.171Z] make[1]: Leaving directory '/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux/aqa-tests/TKG' [2025-06-28T00:39:44.171Z] make: *** [makefile:62: _extended.perf] Error 2 [2025-06-28T00:39:44.238Z] script returned exit code 2 [Pipeline] sh [2025-06-28T00:39:44.944Z] + uname [2025-06-28T00:39:44.944Z] + [ Linux = AIX ] [2025-06-28T00:39:44.944Z] + uname [2025-06-28T00:39:44.944Z] + [ Linux = SunOS ] [2025-06-28T00:39:44.944Z] + uname [2025-06-28T00:39:44.944Z] + [ Linux = *BSD ] [2025-06-28T00:39:44.944Z] + MAKE=make [2025-06-28T00:39:44.944Z] + make -f ./aqa-tests/TKG/testEnv.mk testEnvTeardown [2025-06-28T00:39:44.944Z] make: Nothing to be done for 'testEnvTeardown'. [Pipeline] } [2025-06-28T00:39:45.023Z] $ ssh-agent -k [2025-06-28T00:39:45.049Z] unset SSH_AUTH_SOCK; [2025-06-28T00:39:45.051Z] unset SSH_AGENT_PID; [2025-06-28T00:39:45.055Z] echo Agent pid 852583 killed; [2025-06-28T00:39:45.149Z] [ssh-agent] Stopped. [Pipeline] // sshagent [Pipeline] } [2025-06-28T00:39:45.172Z] Xvfb stopping [Pipeline] // wrap [Pipeline] echo [2025-06-28T00:39:45.449Z] no DaCapo-h2 metric found [Pipeline] echo [2025-06-28T00:39:45.463Z] Could not find test result, set build result to FAILURE. [Pipeline] } [Pipeline] // stage [Pipeline] stage [Pipeline] { (Post) [Pipeline] step [2025-06-28T00:39:45.553Z] TAP Reports Processing: START [2025-06-28T00:39:45.554Z] Looking for TAP results report in workspace using pattern: aqa-tests/TKG/**/*.tap [2025-06-28T00:39:45.958Z] Did not find any matching files. Setting build result to FAILURE. [Pipeline] echo [2025-06-28T00:39:45.975Z] Saving aqa-tests/testenv/testenv.properties file on jenkins. [Pipeline] archiveArtifacts [2025-06-28T00:39:46.005Z] Archiving artifacts [2025-06-28T00:39:46.121Z] Recording fingerprints [Pipeline] echo [2025-06-28T00:39:46.179Z] Saving aqa-tests/TKG/**/*.tap file on jenkins. [Pipeline] archiveArtifacts [2025-06-28T00:39:46.208Z] Archiving artifacts [Pipeline] sh [2025-06-28T00:39:46.873Z] + tar -cf benchmark_test_output.tar.gz ./aqa-tests/TKG/output_17509816891623 [Pipeline] echo [2025-06-28T00:39:49.910Z] ARTIFACTORY_SERVER is not set. Saving artifacts on jenkins. [Pipeline] archiveArtifacts [2025-06-28T00:39:49.944Z] Archiving artifacts [2025-06-28T00:40:29.189Z] Body did not finish within grace period; terminating with extreme prejudice [Pipeline] } [Pipeline] // stage [Pipeline] echo [2025-06-28T00:40:29.234Z] PROCESSCATCH: Terminating any hung/left over test processes: [Pipeline] sh [2025-06-28T00:40:29.713Z] + aqa-tests/terminateTestProcesses.sh jenkins [2025-06-28T00:40:29.713Z] Unix type machine.. [2025-06-28T00:40:29.713Z] Running on a Linux host [2025-06-28T00:40:29.713Z] Woohoo - no rogue processes detected! [Pipeline] cleanWs [2025-06-28T00:40:29.836Z] [WS-CLEANUP] Deleting project workspace... [2025-06-28T00:40:29.836Z] [WS-CLEANUP] Deferred wipeout is disabled by the job configuration... [2025-06-28T00:40:43.456Z] [WS-CLEANUP] done [Pipeline] sh [2025-06-28T00:40:43.958Z] + find /tmp -name *core* -print -exec rm -f {} ; [2025-06-28T00:40:44.296Z] + true [Pipeline] } [Pipeline] // timeout [Pipeline] echo [2025-06-28T00:40:44.399Z] Exception: org.jenkinsci.plugins.workflow.steps.FlowInterruptedException [Pipeline] timeout [2025-06-28T00:40:44.405Z] Timeout set to expire in 5 min 0 sec [Pipeline] { [Pipeline] } [Pipeline] // timeout [Pipeline] } [Pipeline] // node [Pipeline] } [Pipeline] // stage [Pipeline] echo [2025-06-28T00:40:44.528Z] SETUP_LABEL: ci.role.test [Pipeline] stage [Pipeline] { (Parallel Tests) [Pipeline] parallel [2025-06-28T00:40:44.554Z] No branches to run [Pipeline] // parallel [Pipeline] node [2025-06-28T00:40:44.643Z] Running on test-docker-ubi9-s390x-1 in /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux [Pipeline] { [Pipeline] cleanWs [2025-06-28T00:40:45.139Z] [WS-CLEANUP] Deleting project workspace... [2025-06-28T00:40:45.139Z] [WS-CLEANUP] Deferred wipeout is disabled by the job configuration... [2025-06-28T00:40:45.240Z] [WS-CLEANUP] done [Pipeline] findFiles [Pipeline] cleanWs [2025-06-28T00:40:45.550Z] [WS-CLEANUP] Deleting project workspace... [2025-06-28T00:40:45.550Z] [WS-CLEANUP] Deferred wipeout is disabled by the job configuration... [2025-06-28T00:40:45.648Z] [WS-CLEANUP] done [Pipeline] } [Pipeline] // node [Pipeline] } [Pipeline] // stage [Pipeline] } [Pipeline] // timestamps [Pipeline] End of Pipeline Finished: ABORTED