[2024-06-26T21:20:08.821Z] Running test renaissance-movie-lens_0 ... [2024-06-26T21:20:08.821Z] =============================================== [2024-06-26T21:20:08.821Z] renaissance-movie-lens_0 Start Time: Wed Jun 26 21:20:08 2024 Epoch Time (ms): 1719436808090 [2024-06-26T21:20:08.821Z] variation: NoOptions [2024-06-26T21:20:08.821Z] JVM_OPTIONS: [2024-06-26T21:20:08.821Z] { \ [2024-06-26T21:20:08.821Z] echo ""; echo "TEST SETUP:"; \ [2024-06-26T21:20:08.821Z] echo "Nothing to be done for setup."; \ [2024-06-26T21:20:08.821Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17194356267082/renaissance-movie-lens_0"; \ [2024-06-26T21:20:08.821Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17194356267082/renaissance-movie-lens_0"; \ [2024-06-26T21:20:08.821Z] echo ""; echo "TESTING:"; \ [2024-06-26T21:20:08.821Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/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_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17194356267082/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-06-26T21:20:08.821Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17194356267082/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-06-26T21:20:08.821Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-06-26T21:20:08.821Z] echo "Nothing to be done for teardown."; \ [2024-06-26T21:20:08.821Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17194356267082/TestTargetResult"; [2024-06-26T21:20:08.821Z] [2024-06-26T21:20:08.821Z] TEST SETUP: [2024-06-26T21:20:08.821Z] Nothing to be done for setup. [2024-06-26T21:20:08.821Z] [2024-06-26T21:20:08.821Z] TESTING: [2024-06-26T21:20:12.910Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-06-26T21:20:17.703Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-06-26T21:20:23.013Z] Got 100004 ratings from 671 users on 9066 movies. [2024-06-26T21:20:23.013Z] Training: 60056, validation: 20285, test: 19854 [2024-06-26T21:20:23.013Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-06-26T21:20:23.013Z] GC before operation: completed in 107.513 ms, heap usage 147.318 MB -> 37.197 MB. [2024-06-26T21:20:34.576Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:20:39.894Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:20:44.014Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:20:49.330Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:20:51.270Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:20:54.329Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:20:57.302Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:20:59.309Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:21:00.245Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-06-26T21:21:00.245Z] The best model improves the baseline by 14.43%. [2024-06-26T21:21:00.245Z] Movies recommended for you: [2024-06-26T21:21:00.245Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:21:00.245Z] There is no way to check that no silent failure occurred. [2024-06-26T21:21:00.245Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (37675.136 ms) ====== [2024-06-26T21:21:00.245Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-06-26T21:21:01.182Z] GC before operation: completed in 222.955 ms, heap usage 211.912 MB -> 48.217 MB. [2024-06-26T21:21:05.273Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:21:09.366Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:21:13.457Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:21:16.446Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:21:19.419Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:21:21.354Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:21:23.980Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:21:26.955Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:21:26.955Z] 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. [2024-06-26T21:21:26.955Z] The best model improves the baseline by 14.43%. [2024-06-26T21:21:26.955Z] Movies recommended for you: [2024-06-26T21:21:26.955Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:21:26.955Z] There is no way to check that no silent failure occurred. [2024-06-26T21:21:26.955Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (26590.302 ms) ====== [2024-06-26T21:21:26.955Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-06-26T21:21:27.894Z] GC before operation: completed in 227.897 ms, heap usage 229.015 MB -> 54.203 MB. [2024-06-26T21:21:31.982Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:21:36.069Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:21:39.057Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:21:43.149Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:21:45.073Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:21:46.998Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:21:49.987Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:21:51.927Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:21:51.927Z] 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. [2024-06-26T21:21:51.927Z] The best model improves the baseline by 14.43%. [2024-06-26T21:21:53.016Z] Movies recommended for you: [2024-06-26T21:21:53.017Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:21:53.017Z] There is no way to check that no silent failure occurred. [2024-06-26T21:21:53.017Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24875.440 ms) ====== [2024-06-26T21:21:53.017Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-06-26T21:21:53.017Z] GC before operation: completed in 199.516 ms, heap usage 130.176 MB -> 51.233 MB. [2024-06-26T21:21:55.990Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:22:00.086Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:22:03.079Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:22:06.050Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:22:07.974Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:22:10.943Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:22:12.869Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:22:14.800Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:22:14.800Z] 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. [2024-06-26T21:22:14.800Z] The best model improves the baseline by 14.43%. [2024-06-26T21:22:15.738Z] Movies recommended for you: [2024-06-26T21:22:15.738Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:22:15.738Z] There is no way to check that no silent failure occurred. [2024-06-26T21:22:15.738Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22673.483 ms) ====== [2024-06-26T21:22:15.738Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-06-26T21:22:15.738Z] GC before operation: completed in 201.616 ms, heap usage 252.451 MB -> 51.634 MB. [2024-06-26T21:22:18.710Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:22:21.698Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:22:25.367Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:22:28.341Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:22:31.319Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:22:33.245Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:22:35.172Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:22:37.095Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:22:38.031Z] 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. [2024-06-26T21:22:38.031Z] The best model improves the baseline by 14.43%. [2024-06-26T21:22:38.031Z] Movies recommended for you: [2024-06-26T21:22:38.031Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:22:38.031Z] There is no way to check that no silent failure occurred. [2024-06-26T21:22:38.031Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22200.578 ms) ====== [2024-06-26T21:22:38.031Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-06-26T21:22:38.031Z] GC before operation: completed in 205.238 ms, heap usage 194.593 MB -> 51.872 MB. [2024-06-26T21:22:42.121Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:22:45.095Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:22:48.174Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:22:51.151Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:22:53.205Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:22:56.181Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:22:58.106Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:23:00.032Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:23:00.969Z] 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. [2024-06-26T21:23:00.969Z] The best model improves the baseline by 14.43%. [2024-06-26T21:23:00.969Z] Movies recommended for you: [2024-06-26T21:23:00.969Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:23:00.969Z] There is no way to check that no silent failure occurred. [2024-06-26T21:23:00.969Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (22776.344 ms) ====== [2024-06-26T21:23:00.969Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-06-26T21:23:00.969Z] GC before operation: completed in 203.521 ms, heap usage 150.955 MB -> 51.684 MB. [2024-06-26T21:23:03.944Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:23:08.037Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:23:11.008Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:23:13.995Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:23:15.922Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:23:18.895Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:23:20.823Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:23:22.756Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:23:22.756Z] 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. [2024-06-26T21:23:22.756Z] The best model improves the baseline by 14.43%. [2024-06-26T21:23:24.380Z] Movies recommended for you: [2024-06-26T21:23:24.380Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:23:24.380Z] There is no way to check that no silent failure occurred. [2024-06-26T21:23:24.380Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (22330.632 ms) ====== [2024-06-26T21:23:24.380Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-06-26T21:23:24.380Z] GC before operation: completed in 211.108 ms, heap usage 222.603 MB -> 51.938 MB. [2024-06-26T21:23:27.355Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:23:30.324Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:23:34.414Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:23:37.401Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:23:39.323Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:23:41.245Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:23:43.174Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:23:45.098Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:23:46.035Z] 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. [2024-06-26T21:23:46.035Z] The best model improves the baseline by 14.43%. [2024-06-26T21:23:46.035Z] Movies recommended for you: [2024-06-26T21:23:46.035Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:23:46.035Z] There is no way to check that no silent failure occurred. [2024-06-26T21:23:46.035Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22461.030 ms) ====== [2024-06-26T21:23:46.035Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-06-26T21:23:46.035Z] GC before operation: completed in 183.589 ms, heap usage 234.692 MB -> 52.242 MB. [2024-06-26T21:23:49.007Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:23:53.284Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:23:56.254Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:23:59.226Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:24:01.149Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:24:03.072Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:24:05.021Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:24:06.950Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:24:07.890Z] 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. [2024-06-26T21:24:07.890Z] The best model improves the baseline by 14.43%. [2024-06-26T21:24:07.890Z] Movies recommended for you: [2024-06-26T21:24:07.890Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:24:07.890Z] There is no way to check that no silent failure occurred. [2024-06-26T21:24:07.890Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21881.488 ms) ====== [2024-06-26T21:24:07.890Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-06-26T21:24:07.890Z] GC before operation: completed in 181.551 ms, heap usage 261.899 MB -> 52.053 MB. [2024-06-26T21:24:11.992Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:24:14.969Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:24:17.948Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:24:22.055Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:24:24.681Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:24:25.622Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:24:28.598Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:24:30.528Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:24:30.528Z] 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. [2024-06-26T21:24:30.528Z] The best model improves the baseline by 14.43%. [2024-06-26T21:24:30.528Z] Movies recommended for you: [2024-06-26T21:24:30.528Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:24:30.528Z] There is no way to check that no silent failure occurred. [2024-06-26T21:24:30.528Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (22614.953 ms) ====== [2024-06-26T21:24:30.528Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-06-26T21:24:31.468Z] GC before operation: completed in 205.240 ms, heap usage 254.509 MB -> 52.142 MB. [2024-06-26T21:24:34.448Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:24:37.461Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:24:40.439Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:24:43.421Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:24:45.350Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:24:47.280Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:24:49.221Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:24:52.196Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:24:52.196Z] 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. [2024-06-26T21:24:52.196Z] The best model improves the baseline by 14.43%. [2024-06-26T21:24:52.196Z] Movies recommended for you: [2024-06-26T21:24:52.197Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:24:52.197Z] There is no way to check that no silent failure occurred. [2024-06-26T21:24:52.197Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (21163.562 ms) ====== [2024-06-26T21:24:52.197Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-06-26T21:24:52.197Z] GC before operation: completed in 201.887 ms, heap usage 166.457 MB -> 51.790 MB. [2024-06-26T21:24:56.366Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:24:59.350Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:25:02.332Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:25:05.331Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:25:07.262Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:25:09.196Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:25:11.128Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:25:12.071Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:25:13.009Z] 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. [2024-06-26T21:25:13.009Z] The best model improves the baseline by 14.43%. [2024-06-26T21:25:13.009Z] Movies recommended for you: [2024-06-26T21:25:13.009Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:25:13.009Z] There is no way to check that no silent failure occurred. [2024-06-26T21:25:13.009Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20592.842 ms) ====== [2024-06-26T21:25:13.009Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-06-26T21:25:13.009Z] GC before operation: completed in 184.125 ms, heap usage 570.464 MB -> 55.575 MB. [2024-06-26T21:25:15.994Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:25:18.978Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:25:23.092Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:25:25.729Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:25:27.710Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:25:29.640Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:25:31.746Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:25:33.677Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:25:33.677Z] 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. [2024-06-26T21:25:33.677Z] The best model improves the baseline by 14.43%. [2024-06-26T21:25:33.677Z] Movies recommended for you: [2024-06-26T21:25:33.677Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:25:33.677Z] There is no way to check that no silent failure occurred. [2024-06-26T21:25:33.677Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20738.960 ms) ====== [2024-06-26T21:25:33.677Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-06-26T21:25:33.677Z] GC before operation: completed in 171.381 ms, heap usage 150.676 MB -> 52.176 MB. [2024-06-26T21:25:37.777Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:25:40.754Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:25:43.741Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:25:46.720Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:25:48.653Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:25:50.591Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:25:52.525Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:25:54.490Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:25:54.490Z] 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. [2024-06-26T21:25:54.490Z] The best model improves the baseline by 14.43%. [2024-06-26T21:25:55.433Z] Movies recommended for you: [2024-06-26T21:25:55.433Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:25:55.433Z] There is no way to check that no silent failure occurred. [2024-06-26T21:25:55.433Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20917.146 ms) ====== [2024-06-26T21:25:55.433Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-06-26T21:25:55.433Z] GC before operation: completed in 177.525 ms, heap usage 600.400 MB -> 55.494 MB. [2024-06-26T21:25:58.420Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:26:01.422Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:26:04.405Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:26:07.395Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:26:09.331Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:26:11.268Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:26:13.198Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:26:15.127Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:26:15.127Z] 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. [2024-06-26T21:26:15.127Z] The best model improves the baseline by 14.43%. [2024-06-26T21:26:15.127Z] Movies recommended for you: [2024-06-26T21:26:15.128Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:26:15.128Z] There is no way to check that no silent failure occurred. [2024-06-26T21:26:15.128Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20229.887 ms) ====== [2024-06-26T21:26:15.128Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-06-26T21:26:15.128Z] GC before operation: completed in 167.180 ms, heap usage 239.242 MB -> 52.184 MB. [2024-06-26T21:26:19.252Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:26:21.187Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:26:24.366Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:26:26.834Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:26:28.764Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:26:30.697Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:26:32.630Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:26:34.573Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:26:34.573Z] 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. [2024-06-26T21:26:34.573Z] The best model improves the baseline by 14.43%. [2024-06-26T21:26:34.573Z] Movies recommended for you: [2024-06-26T21:26:34.573Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:26:34.573Z] There is no way to check that no silent failure occurred. [2024-06-26T21:26:34.573Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19115.861 ms) ====== [2024-06-26T21:26:34.573Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-06-26T21:26:34.573Z] GC before operation: completed in 170.968 ms, heap usage 113.247 MB -> 52.164 MB. [2024-06-26T21:26:37.551Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:26:40.533Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:26:43.521Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:26:46.503Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:26:48.435Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:26:50.368Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:26:51.309Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:26:53.380Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:26:53.380Z] 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. [2024-06-26T21:26:54.322Z] The best model improves the baseline by 14.43%. [2024-06-26T21:26:54.322Z] Movies recommended for you: [2024-06-26T21:26:54.322Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:26:54.322Z] There is no way to check that no silent failure occurred. [2024-06-26T21:26:54.322Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19090.633 ms) ====== [2024-06-26T21:26:54.322Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-06-26T21:26:54.322Z] GC before operation: completed in 169.930 ms, heap usage 263.547 MB -> 52.089 MB. [2024-06-26T21:26:57.307Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:27:00.296Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:27:03.297Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:27:06.287Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:27:08.222Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:27:10.170Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:27:12.120Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:27:13.063Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:27:14.005Z] 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. [2024-06-26T21:27:14.005Z] The best model improves the baseline by 14.43%. [2024-06-26T21:27:14.005Z] Movies recommended for you: [2024-06-26T21:27:14.005Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:27:14.005Z] There is no way to check that no silent failure occurred. [2024-06-26T21:27:14.005Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19679.760 ms) ====== [2024-06-26T21:27:14.005Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-06-26T21:27:14.005Z] GC before operation: completed in 233.333 ms, heap usage 523.711 MB -> 55.587 MB. [2024-06-26T21:27:16.992Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:27:19.983Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:27:22.968Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:27:26.649Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:27:27.590Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:27:29.521Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:27:31.457Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:27:33.384Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:27:33.384Z] 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. [2024-06-26T21:27:33.384Z] The best model improves the baseline by 14.43%. [2024-06-26T21:27:33.384Z] Movies recommended for you: [2024-06-26T21:27:33.384Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:27:33.384Z] There is no way to check that no silent failure occurred. [2024-06-26T21:27:33.384Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19497.794 ms) ====== [2024-06-26T21:27:33.384Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-06-26T21:27:33.384Z] GC before operation: completed in 193.729 ms, heap usage 132.018 MB -> 52.246 MB. [2024-06-26T21:27:36.369Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-06-26T21:27:39.363Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-06-26T21:27:42.342Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-06-26T21:27:45.319Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-06-26T21:27:47.250Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-06-26T21:27:48.194Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-06-26T21:27:50.122Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-06-26T21:27:52.050Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-06-26T21:27:52.050Z] 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. [2024-06-26T21:27:52.050Z] The best model improves the baseline by 14.43%. [2024-06-26T21:27:52.050Z] Movies recommended for you: [2024-06-26T21:27:52.050Z] WARNING: This benchmark provides no result that can be validated. [2024-06-26T21:27:52.050Z] There is no way to check that no silent failure occurred. [2024-06-26T21:27:52.050Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18723.505 ms) ====== [2024-06-26T21:27:54.028Z] ----------------------------------- [2024-06-26T21:27:54.028Z] renaissance-movie-lens_0_PASSED [2024-06-26T21:27:54.028Z] ----------------------------------- [2024-06-26T21:27:54.028Z] [2024-06-26T21:27:54.028Z] TEST TEARDOWN: [2024-06-26T21:27:54.028Z] Nothing to be done for teardown. [2024-06-26T21:27:54.028Z] renaissance-movie-lens_0 Finish Time: Wed Jun 26 21:27:53 2024 Epoch Time (ms): 1719437273901