[2024-08-15T03:24:52.063Z] Running test renaissance-movie-lens_0 ... [2024-08-15T03:24:52.063Z] =============================================== [2024-08-15T03:24:52.063Z] renaissance-movie-lens_0 Start Time: Wed Aug 14 22:24:51 2024 Epoch Time (ms): 1723692291537 [2024-08-15T03:24:52.063Z] variation: NoOptions [2024-08-15T03:24:52.063Z] JVM_OPTIONS: [2024-08-15T03:24:52.063Z] { \ [2024-08-15T03:24:52.063Z] echo ""; echo "TEST SETUP:"; \ [2024-08-15T03:24:52.063Z] echo "Nothing to be done for setup."; \ [2024-08-15T03:24:52.063Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723691364640/renaissance-movie-lens_0"; \ [2024-08-15T03:24:52.063Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723691364640/renaissance-movie-lens_0"; \ [2024-08-15T03:24:52.063Z] echo ""; echo "TESTING:"; \ [2024-08-15T03:24:52.063Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-11.0.25+3/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_1723691364640/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-15T03:24:52.063Z] 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_1723691364640/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-15T03:24:52.063Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-15T03:24:52.063Z] echo "Nothing to be done for teardown."; \ [2024-08-15T03:24:52.063Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723691364640/TestTargetResult"; [2024-08-15T03:24:52.063Z] [2024-08-15T03:24:52.063Z] TEST SETUP: [2024-08-15T03:24:52.063Z] Nothing to be done for setup. [2024-08-15T03:24:52.063Z] [2024-08-15T03:24:52.063Z] TESTING: [2024-08-15T03:24:55.125Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-15T03:24:57.327Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-08-15T03:25:00.395Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-15T03:25:00.395Z] Training: 60056, validation: 20285, test: 19854 [2024-08-15T03:25:00.395Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-15T03:25:01.171Z] GC before operation: completed in 71.073 ms, heap usage 135.994 MB -> 37.182 MB. [2024-08-15T03:25:09.302Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:25:13.350Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:25:17.388Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:25:20.457Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:25:22.654Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:25:24.095Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:25:26.304Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:25:28.550Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:25:28.550Z] 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. [2024-08-15T03:25:28.550Z] The best model improves the baseline by 14.43%. [2024-08-15T03:25:29.231Z] Movies recommended for you: [2024-08-15T03:25:29.231Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:25:29.231Z] There is no way to check that no silent failure occurred. [2024-08-15T03:25:29.231Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28181.583 ms) ====== [2024-08-15T03:25:29.231Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-15T03:25:29.231Z] GC before operation: completed in 138.387 ms, heap usage 154.239 MB -> 48.143 MB. [2024-08-15T03:25:32.317Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:25:35.409Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:25:38.542Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:25:41.613Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:25:43.051Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:25:45.250Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:25:47.456Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:25:48.882Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:25:49.571Z] 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. [2024-08-15T03:25:49.571Z] The best model improves the baseline by 14.43%. [2024-08-15T03:25:49.571Z] Movies recommended for you: [2024-08-15T03:25:49.571Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:25:49.571Z] There is no way to check that no silent failure occurred. [2024-08-15T03:25:49.571Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20337.185 ms) ====== [2024-08-15T03:25:49.571Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-15T03:25:49.571Z] GC before operation: completed in 138.047 ms, heap usage 360.922 MB -> 51.023 MB. [2024-08-15T03:25:52.649Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:25:56.695Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:25:58.927Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:26:02.554Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:26:03.978Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:26:05.408Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:26:06.831Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:26:09.064Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:26:09.064Z] 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. [2024-08-15T03:26:09.064Z] The best model improves the baseline by 14.43%. [2024-08-15T03:26:09.746Z] Movies recommended for you: [2024-08-15T03:26:09.746Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:26:09.747Z] There is no way to check that no silent failure occurred. [2024-08-15T03:26:09.747Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19863.380 ms) ====== [2024-08-15T03:26:09.747Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-15T03:26:09.747Z] GC before operation: completed in 136.511 ms, heap usage 289.806 MB -> 51.415 MB. [2024-08-15T03:26:12.833Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:26:15.029Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:26:17.238Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:26:20.312Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:26:21.730Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:26:23.150Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:26:25.353Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:26:26.802Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:26:27.483Z] 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. [2024-08-15T03:26:27.483Z] The best model improves the baseline by 14.43%. [2024-08-15T03:26:27.483Z] Movies recommended for you: [2024-08-15T03:26:27.483Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:26:27.483Z] There is no way to check that no silent failure occurred. [2024-08-15T03:26:27.483Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17936.483 ms) ====== [2024-08-15T03:26:27.483Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-15T03:26:27.483Z] GC before operation: completed in 126.215 ms, heap usage 425.704 MB -> 51.873 MB. [2024-08-15T03:26:30.541Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:26:33.646Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:26:35.882Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:26:38.099Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:26:39.540Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:26:41.732Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:26:43.149Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:26:44.566Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:26:44.566Z] 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. [2024-08-15T03:26:44.566Z] The best model improves the baseline by 14.43%. [2024-08-15T03:26:45.246Z] Movies recommended for you: [2024-08-15T03:26:45.246Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:26:45.246Z] There is no way to check that no silent failure occurred. [2024-08-15T03:26:45.246Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17379.222 ms) ====== [2024-08-15T03:26:45.246Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-15T03:26:45.246Z] GC before operation: completed in 155.405 ms, heap usage 263.803 MB -> 51.900 MB. [2024-08-15T03:26:48.316Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:26:50.530Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:26:53.696Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:26:55.917Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:26:57.338Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:26:58.769Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:27:00.984Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:27:02.397Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:27:02.397Z] 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. [2024-08-15T03:27:02.397Z] The best model improves the baseline by 14.43%. [2024-08-15T03:27:03.074Z] Movies recommended for you: [2024-08-15T03:27:03.074Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:27:03.074Z] There is no way to check that no silent failure occurred. [2024-08-15T03:27:03.074Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17691.653 ms) ====== [2024-08-15T03:27:03.074Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-15T03:27:03.074Z] GC before operation: completed in 136.343 ms, heap usage 341.591 MB -> 51.882 MB. [2024-08-15T03:27:06.162Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:27:08.392Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:27:11.482Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:27:13.688Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:27:15.613Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:27:17.054Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:27:18.464Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:27:19.901Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:27:19.901Z] 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. [2024-08-15T03:27:19.901Z] The best model improves the baseline by 14.43%. [2024-08-15T03:27:20.578Z] Movies recommended for you: [2024-08-15T03:27:20.578Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:27:20.578Z] There is no way to check that no silent failure occurred. [2024-08-15T03:27:20.578Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17370.490 ms) ====== [2024-08-15T03:27:20.578Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-15T03:27:20.578Z] GC before operation: completed in 136.762 ms, heap usage 256.927 MB -> 51.959 MB. [2024-08-15T03:27:23.657Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:27:25.871Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:27:28.999Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:27:31.201Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:27:32.620Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:27:34.052Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:27:36.270Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:27:37.742Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:27:38.422Z] 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. [2024-08-15T03:27:38.422Z] The best model improves the baseline by 14.43%. [2024-08-15T03:27:38.422Z] Movies recommended for you: [2024-08-15T03:27:38.422Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:27:38.422Z] There is no way to check that no silent failure occurred. [2024-08-15T03:27:38.422Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17800.208 ms) ====== [2024-08-15T03:27:38.422Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-15T03:27:38.422Z] GC before operation: completed in 121.868 ms, heap usage 324.407 MB -> 52.294 MB. [2024-08-15T03:27:41.496Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:27:43.698Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:27:46.796Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:27:49.030Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:27:50.441Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:27:51.848Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:27:54.063Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:27:55.503Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:27:55.503Z] 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. [2024-08-15T03:27:55.503Z] The best model improves the baseline by 14.43%. [2024-08-15T03:27:55.503Z] Movies recommended for you: [2024-08-15T03:27:55.503Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:27:55.503Z] There is no way to check that no silent failure occurred. [2024-08-15T03:27:55.503Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17131.132 ms) ====== [2024-08-15T03:27:55.503Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-15T03:27:55.503Z] GC before operation: completed in 133.265 ms, heap usage 426.115 MB -> 52.229 MB. [2024-08-15T03:27:58.598Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:28:00.809Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:28:03.898Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:28:06.114Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:28:08.331Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:28:09.747Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:28:11.152Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:28:12.569Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:28:12.569Z] 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. [2024-08-15T03:28:13.247Z] The best model improves the baseline by 14.43%. [2024-08-15T03:28:13.247Z] Movies recommended for you: [2024-08-15T03:28:13.247Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:28:13.247Z] There is no way to check that no silent failure occurred. [2024-08-15T03:28:13.247Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17393.882 ms) ====== [2024-08-15T03:28:13.247Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-15T03:28:13.247Z] GC before operation: completed in 135.096 ms, heap usage 390.308 MB -> 52.323 MB. [2024-08-15T03:28:16.328Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:28:18.576Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:28:21.292Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:28:23.506Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:28:24.956Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:28:27.177Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:28:28.586Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:28:30.007Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:28:30.741Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-15T03:28:30.741Z] The best model improves the baseline by 14.43%. [2024-08-15T03:28:30.741Z] Movies recommended for you: [2024-08-15T03:28:30.741Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:28:30.741Z] There is no way to check that no silent failure occurred. [2024-08-15T03:28:30.741Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17306.103 ms) ====== [2024-08-15T03:28:30.741Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-15T03:28:30.741Z] GC before operation: completed in 111.733 ms, heap usage 404.114 MB -> 52.012 MB. [2024-08-15T03:28:33.853Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:28:36.059Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:28:38.283Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:28:41.369Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:28:42.807Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:28:44.227Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:28:45.656Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:28:47.071Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:28:47.749Z] 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. [2024-08-15T03:28:47.749Z] The best model improves the baseline by 14.43%. [2024-08-15T03:28:47.749Z] Movies recommended for you: [2024-08-15T03:28:47.749Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:28:47.749Z] There is no way to check that no silent failure occurred. [2024-08-15T03:28:47.749Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17079.277 ms) ====== [2024-08-15T03:28:47.749Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-15T03:28:47.749Z] GC before operation: completed in 129.482 ms, heap usage 71.661 MB -> 55.076 MB. [2024-08-15T03:28:50.825Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:28:53.042Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:28:56.142Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:28:58.343Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:28:59.764Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:29:01.189Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:29:02.602Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:29:04.807Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:29:04.807Z] 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. [2024-08-15T03:29:04.807Z] The best model improves the baseline by 14.43%. [2024-08-15T03:29:04.807Z] Movies recommended for you: [2024-08-15T03:29:04.807Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:29:04.807Z] There is no way to check that no silent failure occurred. [2024-08-15T03:29:04.807Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17276.709 ms) ====== [2024-08-15T03:29:04.807Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-15T03:29:05.489Z] GC before operation: completed in 138.714 ms, heap usage 184.987 MB -> 52.269 MB. [2024-08-15T03:29:07.713Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:29:10.790Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:29:13.030Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:29:15.255Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:29:17.470Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:29:18.889Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:29:20.301Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:29:21.707Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:29:21.707Z] 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. [2024-08-15T03:29:21.707Z] The best model improves the baseline by 14.43%. [2024-08-15T03:29:21.707Z] Movies recommended for you: [2024-08-15T03:29:21.707Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:29:21.707Z] There is no way to check that no silent failure occurred. [2024-08-15T03:29:21.707Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16589.705 ms) ====== [2024-08-15T03:29:21.708Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-15T03:29:21.708Z] GC before operation: completed in 125.488 ms, heap usage 71.435 MB -> 55.256 MB. [2024-08-15T03:29:24.770Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:29:26.993Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:29:30.415Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:29:32.621Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:29:34.038Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:29:35.460Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:29:37.672Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:29:39.083Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:29:39.083Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-15T03:29:39.083Z] The best model improves the baseline by 14.43%. [2024-08-15T03:29:39.083Z] Movies recommended for you: [2024-08-15T03:29:39.083Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:29:39.083Z] There is no way to check that no silent failure occurred. [2024-08-15T03:29:39.083Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17392.224 ms) ====== [2024-08-15T03:29:39.083Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-15T03:29:39.765Z] GC before operation: completed in 124.374 ms, heap usage 73.675 MB -> 52.035 MB. [2024-08-15T03:29:42.023Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:29:44.251Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:29:47.345Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:29:49.561Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:29:51.763Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:29:53.182Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:29:54.590Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:29:56.006Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:29:56.700Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-15T03:29:56.700Z] The best model improves the baseline by 14.43%. [2024-08-15T03:29:56.700Z] Movies recommended for you: [2024-08-15T03:29:56.700Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:29:56.700Z] There is no way to check that no silent failure occurred. [2024-08-15T03:29:56.700Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17091.662 ms) ====== [2024-08-15T03:29:56.700Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-15T03:29:56.700Z] GC before operation: completed in 139.513 ms, heap usage 455.981 MB -> 52.453 MB. [2024-08-15T03:29:59.775Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:30:01.986Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:30:04.220Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:30:07.300Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:30:08.710Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:30:10.143Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:30:11.557Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:30:13.809Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:30:13.809Z] 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. [2024-08-15T03:30:13.809Z] The best model improves the baseline by 14.43%. [2024-08-15T03:30:13.809Z] Movies recommended for you: [2024-08-15T03:30:13.809Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:30:13.809Z] There is no way to check that no silent failure occurred. [2024-08-15T03:30:13.809Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17028.617 ms) ====== [2024-08-15T03:30:13.809Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-15T03:30:13.809Z] GC before operation: completed in 120.919 ms, heap usage 209.469 MB -> 52.126 MB. [2024-08-15T03:30:16.870Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:30:19.075Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:30:22.162Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:30:24.362Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:30:25.783Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:30:27.209Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:30:29.414Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:30:30.855Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:30:30.855Z] 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. [2024-08-15T03:30:30.855Z] The best model improves the baseline by 14.43%. [2024-08-15T03:30:30.855Z] Movies recommended for you: [2024-08-15T03:30:30.855Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:30:30.855Z] There is no way to check that no silent failure occurred. [2024-08-15T03:30:30.855Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17195.515 ms) ====== [2024-08-15T03:30:30.855Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-15T03:30:31.533Z] GC before operation: completed in 142.855 ms, heap usage 439.814 MB -> 52.302 MB. [2024-08-15T03:30:34.276Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:30:36.477Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:30:39.551Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:30:41.766Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:30:43.179Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:30:44.589Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:30:46.114Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:30:47.533Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:30:48.231Z] 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. [2024-08-15T03:30:48.231Z] The best model improves the baseline by 14.43%. [2024-08-15T03:30:48.231Z] Movies recommended for you: [2024-08-15T03:30:48.231Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:30:48.231Z] There is no way to check that no silent failure occurred. [2024-08-15T03:30:48.231Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16986.649 ms) ====== [2024-08-15T03:30:48.231Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-15T03:30:48.231Z] GC before operation: completed in 127.661 ms, heap usage 327.129 MB -> 52.393 MB. [2024-08-15T03:30:51.300Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-15T03:30:53.514Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-15T03:30:56.598Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-15T03:30:58.804Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-15T03:31:00.220Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-15T03:31:02.445Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-15T03:31:03.871Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-15T03:31:05.287Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-15T03:31:05.966Z] 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. [2024-08-15T03:31:05.966Z] The best model improves the baseline by 14.43%. [2024-08-15T03:31:05.966Z] Movies recommended for you: [2024-08-15T03:31:05.967Z] WARNING: This benchmark provides no result that can be validated. [2024-08-15T03:31:05.967Z] There is no way to check that no silent failure occurred. [2024-08-15T03:31:05.967Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17578.884 ms) ====== [2024-08-15T03:31:07.380Z] ----------------------------------- [2024-08-15T03:31:07.380Z] renaissance-movie-lens_0_PASSED [2024-08-15T03:31:07.380Z] ----------------------------------- [2024-08-15T03:31:07.380Z] [2024-08-15T03:31:07.380Z] TEST TEARDOWN: [2024-08-15T03:31:07.380Z] Nothing to be done for teardown. [2024-08-15T03:31:07.380Z] renaissance-movie-lens_0 Finish Time: Wed Aug 14 22:31:06 2024 Epoch Time (ms): 1723692666717