Test Results Summary Service

renaissance-movie-lens_0

[2024-08-10T05:20:41.992Z] Running test renaissance-movie-lens_0 ... [2024-08-10T05:20:41.992Z] =============================================== [2024-08-10T05:20:41.992Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 00:20:41 2024 Epoch Time (ms): 1723267241375 [2024-08-10T05:20:41.992Z] variation: NoOptions [2024-08-10T05:20:41.992Z] JVM_OPTIONS: [2024-08-10T05:20:41.992Z] { \ [2024-08-10T05:20:41.992Z] echo ""; echo "TEST SETUP:"; \ [2024-08-10T05:20:41.992Z] echo "Nothing to be done for setup."; \ [2024-08-10T05:20:41.992Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232663323668/renaissance-movie-lens_0"; \ [2024-08-10T05:20:41.992Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232663323668/renaissance-movie-lens_0"; \ [2024-08-10T05:20:41.992Z] echo ""; echo "TESTING:"; \ [2024-08-10T05:20:41.992Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-11.0.25+2/bin/..//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_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232663323668/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-10T05:20:41.993Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232663323668/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-10T05:20:41.993Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-10T05:20:41.993Z] echo "Nothing to be done for teardown."; \ [2024-08-10T05:20:41.993Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232663323668/TestTargetResult"; [2024-08-10T05:20:41.993Z] [2024-08-10T05:20:41.993Z] TEST SETUP: [2024-08-10T05:20:41.993Z] Nothing to be done for setup. [2024-08-10T05:20:41.993Z] [2024-08-10T05:20:41.993Z] TESTING: [2024-08-10T05:20:45.133Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-10T05:20:47.355Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-08-10T05:20:50.453Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-10T05:20:50.453Z] Training: 60056, validation: 20285, test: 19854 [2024-08-10T05:20:50.453Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-10T05:20:50.453Z] GC before operation: completed in 163.618 ms, heap usage 137.828 MB -> 37.221 MB. [2024-08-10T05:20:58.209Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:21:02.312Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:21:06.383Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:21:09.517Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:21:11.789Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:21:13.230Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:21:15.483Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:21:16.914Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:21:17.616Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:21:17.616Z] The best model improves the baseline by 14.43%. [2024-08-10T05:21:17.616Z] Movies recommended for you: [2024-08-10T05:21:17.616Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:21:17.616Z] There is no way to check that no silent failure occurred. [2024-08-10T05:21:17.616Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26836.178 ms) ====== [2024-08-10T05:21:17.616Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-10T05:21:17.616Z] GC before operation: completed in 128.658 ms, heap usage 376.030 MB -> 48.319 MB. [2024-08-10T05:21:20.754Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:21:24.857Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:21:27.133Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:21:30.247Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:21:31.679Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:21:33.915Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:21:35.366Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:21:37.641Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:21:37.641Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:21:37.641Z] The best model improves the baseline by 14.43%. [2024-08-10T05:21:37.641Z] Movies recommended for you: [2024-08-10T05:21:37.641Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:21:37.641Z] There is no way to check that no silent failure occurred. [2024-08-10T05:21:37.641Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20085.662 ms) ====== [2024-08-10T05:21:37.641Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-10T05:21:38.326Z] GC before operation: completed in 137.068 ms, heap usage 412.218 MB -> 51.091 MB. [2024-08-10T05:21:41.423Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:21:44.526Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:21:47.684Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:21:49.924Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:21:52.256Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:21:53.680Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:21:55.105Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:21:57.327Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:21:57.327Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:21:57.327Z] The best model improves the baseline by 14.43%. [2024-08-10T05:21:57.327Z] Movies recommended for you: [2024-08-10T05:21:57.327Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:21:57.327Z] There is no way to check that no silent failure occurred. [2024-08-10T05:21:57.327Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19404.951 ms) ====== [2024-08-10T05:21:57.327Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-10T05:21:57.327Z] GC before operation: completed in 127.679 ms, heap usage 395.002 MB -> 51.478 MB. [2024-08-10T05:22:00.418Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:22:02.650Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:22:05.779Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:22:08.042Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:22:09.494Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:22:11.747Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:22:13.179Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:22:15.438Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:22:15.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:22:15.438Z] The best model improves the baseline by 14.43%. [2024-08-10T05:22:15.438Z] Movies recommended for you: [2024-08-10T05:22:15.438Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:22:15.438Z] There is no way to check that no silent failure occurred. [2024-08-10T05:22:15.438Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17966.555 ms) ====== [2024-08-10T05:22:15.438Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-10T05:22:15.438Z] GC before operation: completed in 149.425 ms, heap usage 415.646 MB -> 51.811 MB. [2024-08-10T05:22:18.560Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:22:20.809Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:22:23.932Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:22:26.166Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:22:27.600Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:22:29.022Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:22:31.252Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:22:32.688Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:22:32.688Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:22:33.380Z] The best model improves the baseline by 14.43%. [2024-08-10T05:22:33.380Z] Movies recommended for you: [2024-08-10T05:22:33.380Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:22:33.380Z] There is no way to check that no silent failure occurred. [2024-08-10T05:22:33.380Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17569.182 ms) ====== [2024-08-10T05:22:33.380Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-10T05:22:33.380Z] GC before operation: completed in 142.629 ms, heap usage 400.359 MB -> 52.034 MB. [2024-08-10T05:22:36.481Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:22:38.706Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:22:40.960Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:22:44.081Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:22:45.509Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:22:46.965Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:22:48.395Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:22:50.640Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:22:50.640Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:22:50.640Z] The best model improves the baseline by 14.43%. [2024-08-10T05:22:50.640Z] Movies recommended for you: [2024-08-10T05:22:50.640Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:22:50.640Z] There is no way to check that no silent failure occurred. [2024-08-10T05:22:50.640Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17217.443 ms) ====== [2024-08-10T05:22:50.640Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-10T05:22:50.640Z] GC before operation: completed in 136.575 ms, heap usage 99.003 MB -> 55.051 MB. [2024-08-10T05:22:53.775Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:22:56.012Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:22:59.121Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:23:01.352Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:23:02.778Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:23:04.223Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:23:05.684Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:23:07.916Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:23:07.916Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:23:07.916Z] The best model improves the baseline by 14.43%. [2024-08-10T05:23:07.916Z] Movies recommended for you: [2024-08-10T05:23:07.916Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:23:07.916Z] There is no way to check that no silent failure occurred. [2024-08-10T05:23:07.916Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17298.033 ms) ====== [2024-08-10T05:23:07.916Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-10T05:23:07.916Z] GC before operation: completed in 130.801 ms, heap usage 375.087 MB -> 51.969 MB. [2024-08-10T05:23:11.026Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:23:13.254Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:23:16.357Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:23:18.592Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:23:20.038Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:23:21.469Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:23:23.701Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:23:25.148Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:23:25.148Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:23:25.148Z] The best model improves the baseline by 14.43%. [2024-08-10T05:23:25.855Z] Movies recommended for you: [2024-08-10T05:23:25.855Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:23:25.855Z] There is no way to check that no silent failure occurred. [2024-08-10T05:23:25.855Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17412.234 ms) ====== [2024-08-10T05:23:25.855Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-10T05:23:25.855Z] GC before operation: completed in 124.921 ms, heap usage 96.305 MB -> 53.793 MB. [2024-08-10T05:23:28.952Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:23:31.201Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:23:34.321Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:23:36.555Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:23:37.995Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:23:39.449Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:23:40.911Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:23:42.353Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:23:43.041Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:23:43.041Z] The best model improves the baseline by 14.43%. [2024-08-10T05:23:43.041Z] Movies recommended for you: [2024-08-10T05:23:43.041Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:23:43.041Z] There is no way to check that no silent failure occurred. [2024-08-10T05:23:43.041Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17294.217 ms) ====== [2024-08-10T05:23:43.041Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-10T05:23:43.041Z] GC before operation: completed in 137.627 ms, heap usage 86.737 MB -> 54.851 MB. [2024-08-10T05:23:46.149Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:23:48.397Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:23:51.535Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:23:53.790Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:23:55.239Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:23:56.665Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:23:58.121Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:23:59.565Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:24:00.257Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:24:00.257Z] The best model improves the baseline by 14.43%. [2024-08-10T05:24:00.257Z] Movies recommended for you: [2024-08-10T05:24:00.257Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:24:00.257Z] There is no way to check that no silent failure occurred. [2024-08-10T05:24:00.257Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17208.239 ms) ====== [2024-08-10T05:24:00.257Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-10T05:24:00.257Z] GC before operation: completed in 121.250 ms, heap usage 253.338 MB -> 52.187 MB. [2024-08-10T05:24:03.367Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:24:05.613Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:24:07.876Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:24:10.990Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:24:12.454Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:24:13.887Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:24:15.339Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:24:17.578Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:24:17.578Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:24:17.578Z] The best model improves the baseline by 14.43%. [2024-08-10T05:24:17.578Z] Movies recommended for you: [2024-08-10T05:24:17.578Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:24:17.578Z] There is no way to check that no silent failure occurred. [2024-08-10T05:24:17.578Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17152.916 ms) ====== [2024-08-10T05:24:17.578Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-10T05:24:17.578Z] GC before operation: completed in 128.902 ms, heap usage 261.905 MB -> 51.877 MB. [2024-08-10T05:24:20.825Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:24:23.154Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:24:25.380Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:24:27.630Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:24:29.076Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:24:31.300Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:24:32.738Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:24:34.192Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:24:34.192Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:24:34.192Z] The best model improves the baseline by 14.43%. [2024-08-10T05:24:34.889Z] Movies recommended for you: [2024-08-10T05:24:34.889Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:24:34.889Z] There is no way to check that no silent failure occurred. [2024-08-10T05:24:34.889Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16936.416 ms) ====== [2024-08-10T05:24:34.889Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-10T05:24:34.889Z] GC before operation: completed in 131.036 ms, heap usage 302.121 MB -> 52.184 MB. [2024-08-10T05:24:38.043Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:24:40.285Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:24:43.484Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:24:44.910Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:24:47.182Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:24:48.633Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:24:50.063Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:24:51.501Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:24:52.219Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:24:52.219Z] The best model improves the baseline by 14.43%. [2024-08-10T05:24:52.219Z] Movies recommended for you: [2024-08-10T05:24:52.219Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:24:52.219Z] There is no way to check that no silent failure occurred. [2024-08-10T05:24:52.219Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17350.797 ms) ====== [2024-08-10T05:24:52.219Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-10T05:24:52.219Z] GC before operation: completed in 135.820 ms, heap usage 226.771 MB -> 52.296 MB. [2024-08-10T05:24:55.334Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:24:57.568Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:25:00.700Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:25:02.936Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:25:04.363Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:25:05.799Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:25:07.250Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:25:08.704Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:25:09.413Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:25:09.413Z] The best model improves the baseline by 14.43%. [2024-08-10T05:25:09.413Z] Movies recommended for you: [2024-08-10T05:25:09.413Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:25:09.413Z] There is no way to check that no silent failure occurred. [2024-08-10T05:25:09.413Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17096.621 ms) ====== [2024-08-10T05:25:09.413Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-10T05:25:09.413Z] GC before operation: completed in 148.328 ms, heap usage 353.394 MB -> 52.066 MB. [2024-08-10T05:25:12.531Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:25:14.770Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:25:17.026Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:25:20.128Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:25:21.570Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:25:23.019Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:25:24.469Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:25:25.911Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:25:26.610Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:25:26.610Z] The best model improves the baseline by 14.43%. [2024-08-10T05:25:26.610Z] Movies recommended for you: [2024-08-10T05:25:26.610Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:25:26.610Z] There is no way to check that no silent failure occurred. [2024-08-10T05:25:26.610Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17067.411 ms) ====== [2024-08-10T05:25:26.610Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-10T05:25:26.610Z] GC before operation: completed in 149.968 ms, heap usage 356.769 MB -> 52.244 MB. [2024-08-10T05:25:29.714Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:25:31.937Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:25:35.044Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:25:37.394Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:25:38.839Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:25:40.298Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:25:42.525Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:25:43.953Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:25:43.953Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:25:43.953Z] The best model improves the baseline by 14.43%. [2024-08-10T05:25:43.953Z] Movies recommended for you: [2024-08-10T05:25:43.953Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:25:43.953Z] There is no way to check that no silent failure occurred. [2024-08-10T05:25:43.953Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17514.174 ms) ====== [2024-08-10T05:25:43.953Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-10T05:25:44.638Z] GC before operation: completed in 134.208 ms, heap usage 135.997 MB -> 52.223 MB. [2024-08-10T05:25:46.878Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:25:49.978Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:25:52.235Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:25:54.479Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:25:55.941Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:25:58.196Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:25:59.643Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:26:01.067Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:26:01.759Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:26:01.759Z] The best model improves the baseline by 14.43%. [2024-08-10T05:26:01.759Z] Movies recommended for you: [2024-08-10T05:26:01.759Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:26:01.759Z] There is no way to check that no silent failure occurred. [2024-08-10T05:26:01.759Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17223.355 ms) ====== [2024-08-10T05:26:01.759Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-10T05:26:01.759Z] GC before operation: completed in 143.497 ms, heap usage 165.877 MB -> 52.058 MB. [2024-08-10T05:26:04.885Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:26:07.123Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:26:10.259Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:26:12.495Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:26:13.934Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:26:15.393Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:26:17.645Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:26:19.085Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:26:19.085Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:26:19.086Z] The best model improves the baseline by 14.43%. [2024-08-10T05:26:19.086Z] Movies recommended for you: [2024-08-10T05:26:19.086Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:26:19.086Z] There is no way to check that no silent failure occurred. [2024-08-10T05:26:19.086Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17553.150 ms) ====== [2024-08-10T05:26:19.086Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-10T05:26:19.086Z] GC before operation: completed in 128.540 ms, heap usage 248.890 MB -> 52.162 MB. [2024-08-10T05:26:22.182Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:26:24.410Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:26:27.557Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:26:29.786Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:26:31.218Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:26:32.644Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:26:34.076Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:26:35.522Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:26:36.210Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:26:36.210Z] The best model improves the baseline by 14.43%. [2024-08-10T05:26:36.210Z] Movies recommended for you: [2024-08-10T05:26:36.211Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:26:36.211Z] There is no way to check that no silent failure occurred. [2024-08-10T05:26:36.211Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16651.301 ms) ====== [2024-08-10T05:26:36.211Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-10T05:26:36.211Z] GC before operation: completed in 137.035 ms, heap usage 403.968 MB -> 52.463 MB. [2024-08-10T05:26:38.438Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T05:26:41.541Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T05:26:43.791Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T05:26:46.038Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T05:26:48.283Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T05:26:49.726Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T05:26:51.166Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T05:26:52.606Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T05:26:53.294Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T05:26:53.294Z] The best model improves the baseline by 14.43%. [2024-08-10T05:26:53.294Z] Movies recommended for you: [2024-08-10T05:26:53.294Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T05:26:53.294Z] There is no way to check that no silent failure occurred. [2024-08-10T05:26:53.294Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16915.292 ms) ====== [2024-08-10T05:26:53.989Z] ----------------------------------- [2024-08-10T05:26:53.989Z] renaissance-movie-lens_0_PASSED [2024-08-10T05:26:53.989Z] ----------------------------------- [2024-08-10T05:26:53.989Z] [2024-08-10T05:26:53.989Z] TEST TEARDOWN: [2024-08-10T05:26:53.989Z] Nothing to be done for teardown. [2024-08-10T05:26:53.989Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 00:26:53 2024 Epoch Time (ms): 1723267613898