[2024-08-23T23:11:26.395Z] Running test renaissance-movie-lens_0 ... [2024-08-23T23:11:26.395Z] =============================================== [2024-08-23T23:11:26.395Z] renaissance-movie-lens_0 Start Time: Fri Aug 23 23:11:25 2024 Epoch Time (ms): 1724454685151 [2024-08-23T23:11:26.395Z] variation: NoOptions [2024-08-23T23:11:26.395Z] JVM_OPTIONS: [2024-08-23T23:11:26.395Z] { \ [2024-08-23T23:11:26.395Z] echo ""; echo "TEST SETUP:"; \ [2024-08-23T23:11:26.395Z] echo "Nothing to be done for setup."; \ [2024-08-23T23:11:26.395Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1724445910903/renaissance-movie-lens_0"; \ [2024-08-23T23:11:26.395Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1724445910903/renaissance-movie-lens_0"; \ [2024-08-23T23:11:26.395Z] echo ""; echo "TESTING:"; \ [2024-08-23T23:11:26.395Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/jdk-11.0.25+4/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/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1724445910903/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-23T23:11:26.395Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1724445910903/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-23T23:11:26.395Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-23T23:11:26.395Z] echo "Nothing to be done for teardown."; \ [2024-08-23T23:11:26.395Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1724445910903/TestTargetResult"; [2024-08-23T23:11:26.395Z] [2024-08-23T23:11:26.395Z] TEST SETUP: [2024-08-23T23:11:26.395Z] Nothing to be done for setup. [2024-08-23T23:11:26.395Z] [2024-08-23T23:11:26.395Z] TESTING: [2024-08-23T23:11:37.732Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-23T23:11:47.374Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-23T23:12:13.984Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-23T23:12:13.984Z] Training: 60056, validation: 20285, test: 19854 [2024-08-23T23:12:13.984Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-23T23:12:14.819Z] GC before operation: completed in 570.135 ms, heap usage 50.019 MB -> 36.653 MB. [2024-08-23T23:13:04.650Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:13:33.381Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:14:01.143Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:14:24.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:14:37.739Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:14:50.613Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:14:59.760Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:15:10.822Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:15:13.667Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:15:13.667Z] The best model improves the baseline by 14.52%. [2024-08-23T23:15:15.515Z] Movies recommended for you: [2024-08-23T23:15:15.516Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:15:15.516Z] There is no way to check that no silent failure occurred. [2024-08-23T23:15:15.516Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (180384.427 ms) ====== [2024-08-23T23:15:15.516Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-23T23:15:16.421Z] GC before operation: completed in 816.240 ms, heap usage 271.637 MB -> 50.082 MB. [2024-08-23T23:15:34.078Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:15:54.439Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:16:12.022Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:16:27.822Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:16:38.982Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:16:50.139Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:17:01.057Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:17:10.293Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:17:12.118Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:17:12.118Z] The best model improves the baseline by 14.52%. [2024-08-23T23:17:12.988Z] Movies recommended for you: [2024-08-23T23:17:12.988Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:17:12.988Z] There is no way to check that no silent failure occurred. [2024-08-23T23:17:12.988Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (116566.539 ms) ====== [2024-08-23T23:17:12.988Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-23T23:17:12.988Z] GC before operation: completed in 595.430 ms, heap usage 278.114 MB -> 49.291 MB. [2024-08-23T23:17:28.166Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:17:45.984Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:18:04.323Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:18:18.167Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:18:27.984Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:18:37.730Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:18:47.563Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:18:57.477Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:18:58.229Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:18:58.229Z] The best model improves the baseline by 14.52%. [2024-08-23T23:18:59.015Z] Movies recommended for you: [2024-08-23T23:18:59.015Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:18:59.015Z] There is no way to check that no silent failure occurred. [2024-08-23T23:18:59.015Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (105781.730 ms) ====== [2024-08-23T23:18:59.015Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-23T23:18:59.787Z] GC before operation: completed in 632.168 ms, heap usage 219.199 MB -> 49.489 MB. [2024-08-23T23:19:15.846Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:19:30.270Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:19:46.450Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:20:00.109Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:20:06.902Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:20:15.195Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:20:23.432Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:20:30.217Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:20:31.790Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:20:31.790Z] The best model improves the baseline by 14.52%. [2024-08-23T23:20:32.544Z] Movies recommended for you: [2024-08-23T23:20:32.544Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:20:32.544Z] There is no way to check that no silent failure occurred. [2024-08-23T23:20:32.544Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (92958.874 ms) ====== [2024-08-23T23:20:32.544Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-23T23:20:32.544Z] GC before operation: completed in 441.888 ms, heap usage 177.572 MB -> 49.833 MB. [2024-08-23T23:20:48.597Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:21:00.613Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:21:14.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:21:26.027Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:21:34.951Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:21:42.254Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:21:52.859Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:22:01.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:22:02.622Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:22:03.482Z] The best model improves the baseline by 14.52%. [2024-08-23T23:22:03.482Z] Movies recommended for you: [2024-08-23T23:22:03.482Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:22:03.482Z] There is no way to check that no silent failure occurred. [2024-08-23T23:22:03.482Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (90615.290 ms) ====== [2024-08-23T23:22:03.482Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-23T23:22:04.335Z] GC before operation: completed in 532.019 ms, heap usage 303.714 MB -> 50.074 MB. [2024-08-23T23:22:16.630Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:22:31.718Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:22:46.253Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:22:56.843Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:23:04.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:23:12.928Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:23:21.718Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:23:30.461Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:23:33.096Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:23:33.096Z] The best model improves the baseline by 14.52%. [2024-08-23T23:23:33.096Z] Movies recommended for you: [2024-08-23T23:23:33.096Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:23:33.096Z] There is no way to check that no silent failure occurred. [2024-08-23T23:23:33.096Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (89242.981 ms) ====== [2024-08-23T23:23:33.096Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-23T23:23:33.923Z] GC before operation: completed in 670.083 ms, heap usage 335.581 MB -> 50.070 MB. [2024-08-23T23:23:50.897Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:24:05.552Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:24:19.921Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:24:32.444Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:24:43.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:24:50.517Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:24:57.866Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:25:05.118Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:25:05.949Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:25:05.949Z] The best model improves the baseline by 14.52%. [2024-08-23T23:25:05.949Z] Movies recommended for you: [2024-08-23T23:25:05.949Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:25:05.949Z] There is no way to check that no silent failure occurred. [2024-08-23T23:25:05.949Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (92261.683 ms) ====== [2024-08-23T23:25:05.949Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-23T23:25:06.785Z] GC before operation: completed in 501.002 ms, heap usage 103.904 MB -> 50.103 MB. [2024-08-23T23:25:19.103Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:25:30.081Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:25:42.351Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:25:52.670Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:25:58.647Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:26:04.721Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:26:13.531Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:26:19.598Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:26:21.320Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:26:21.320Z] The best model improves the baseline by 14.52%. [2024-08-23T23:26:22.154Z] Movies recommended for you: [2024-08-23T23:26:22.154Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:26:22.154Z] There is no way to check that no silent failure occurred. [2024-08-23T23:26:22.154Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (75017.805 ms) ====== [2024-08-23T23:26:22.154Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-23T23:26:22.154Z] GC before operation: completed in 474.087 ms, heap usage 193.523 MB -> 50.375 MB. [2024-08-23T23:26:36.494Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:26:46.897Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:27:00.714Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:27:10.513Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:27:16.146Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:27:22.995Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:27:29.976Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:27:36.898Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:27:38.516Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:27:38.516Z] The best model improves the baseline by 14.52%. [2024-08-23T23:27:39.283Z] Movies recommended for you: [2024-08-23T23:27:39.283Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:27:39.283Z] There is no way to check that no silent failure occurred. [2024-08-23T23:27:39.283Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (76672.657 ms) ====== [2024-08-23T23:27:39.283Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-23T23:27:39.283Z] GC before operation: completed in 494.500 ms, heap usage 225.015 MB -> 50.741 MB. [2024-08-23T23:27:51.038Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:28:04.900Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:28:18.570Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:28:28.903Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:28:37.304Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:28:44.163Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:28:52.522Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:28:59.485Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:29:00.266Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:29:00.266Z] The best model improves the baseline by 14.52%. [2024-08-23T23:29:01.032Z] Movies recommended for you: [2024-08-23T23:29:01.032Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:29:01.032Z] There is no way to check that no silent failure occurred. [2024-08-23T23:29:01.032Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (81766.341 ms) ====== [2024-08-23T23:29:01.032Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-23T23:29:01.814Z] GC before operation: completed in 476.100 ms, heap usage 95.907 MB -> 50.238 MB. [2024-08-23T23:29:15.609Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:29:27.314Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:29:41.160Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:29:53.581Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:30:00.703Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:30:09.356Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:30:16.618Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:30:25.338Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:30:26.145Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:30:26.145Z] The best model improves the baseline by 14.52%. [2024-08-23T23:30:26.966Z] Movies recommended for you: [2024-08-23T23:30:26.966Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:30:26.966Z] There is no way to check that no silent failure occurred. [2024-08-23T23:30:26.966Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (85449.516 ms) ====== [2024-08-23T23:30:26.966Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-23T23:30:27.780Z] GC before operation: completed in 591.772 ms, heap usage 194.706 MB -> 50.043 MB. [2024-08-23T23:30:39.857Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:30:54.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:31:06.557Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:31:19.280Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:31:26.466Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:31:33.896Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:31:41.094Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:31:49.791Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:31:50.596Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:31:50.596Z] The best model improves the baseline by 14.52%. [2024-08-23T23:31:50.596Z] Movies recommended for you: [2024-08-23T23:31:50.596Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:31:50.596Z] There is no way to check that no silent failure occurred. [2024-08-23T23:31:50.596Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (83195.424 ms) ====== [2024-08-23T23:31:50.596Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-23T23:31:51.419Z] GC before operation: completed in 590.115 ms, heap usage 248.892 MB -> 50.290 MB. [2024-08-23T23:32:03.663Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:32:18.072Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:32:34.908Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:32:49.628Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:33:00.101Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:33:08.895Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:33:19.309Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:33:31.891Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:33:33.626Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:33:33.626Z] The best model improves the baseline by 14.52%. [2024-08-23T23:33:34.434Z] Movies recommended for you: [2024-08-23T23:33:34.434Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:33:34.434Z] There is no way to check that no silent failure occurred. [2024-08-23T23:33:34.434Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (102637.700 ms) ====== [2024-08-23T23:33:34.434Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-23T23:33:34.434Z] GC before operation: completed in 613.414 ms, heap usage 208.397 MB -> 50.383 MB. [2024-08-23T23:33:54.220Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:34:11.113Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:34:28.760Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:34:45.534Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:34:54.130Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:35:04.618Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:35:16.869Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:35:27.187Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:35:28.012Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:35:28.818Z] The best model improves the baseline by 14.52%. [2024-08-23T23:35:28.818Z] Movies recommended for you: [2024-08-23T23:35:28.818Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:35:28.818Z] There is no way to check that no silent failure occurred. [2024-08-23T23:35:28.818Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (114389.169 ms) ====== [2024-08-23T23:35:28.818Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-23T23:35:29.625Z] GC before operation: completed in 625.468 ms, heap usage 280.423 MB -> 50.688 MB. [2024-08-23T23:35:49.754Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:36:04.772Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:36:25.218Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:36:40.223Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:36:51.517Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:37:00.499Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:37:13.095Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:37:22.263Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:37:24.046Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:37:24.046Z] The best model improves the baseline by 14.52%. [2024-08-23T23:37:24.908Z] Movies recommended for you: [2024-08-23T23:37:24.908Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:37:24.908Z] There is no way to check that no silent failure occurred. [2024-08-23T23:37:24.908Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (114726.115 ms) ====== [2024-08-23T23:37:24.908Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-23T23:37:24.908Z] GC before operation: completed in 728.326 ms, heap usage 148.155 MB -> 47.885 MB. [2024-08-23T23:37:42.855Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:38:00.332Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:38:17.762Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:38:32.638Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:38:41.731Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:38:52.580Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:39:05.531Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:39:14.603Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:39:17.339Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:39:17.339Z] The best model improves the baseline by 14.52%. [2024-08-23T23:39:17.339Z] Movies recommended for you: [2024-08-23T23:39:17.339Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:39:17.339Z] There is no way to check that no silent failure occurred. [2024-08-23T23:39:17.339Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (112444.632 ms) ====== [2024-08-23T23:39:17.339Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-23T23:39:18.203Z] GC before operation: completed in 610.685 ms, heap usage 258.817 MB -> 48.031 MB. [2024-08-23T23:39:35.738Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:39:50.882Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:40:08.329Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:40:23.186Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:40:34.066Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:40:43.483Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:40:54.251Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:41:03.286Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:41:06.184Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:41:06.185Z] The best model improves the baseline by 14.52%. [2024-08-23T23:41:06.185Z] Movies recommended for you: [2024-08-23T23:41:06.185Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:41:06.185Z] There is no way to check that no silent failure occurred. [2024-08-23T23:41:06.185Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (107954.223 ms) ====== [2024-08-23T23:41:06.185Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-23T23:41:07.044Z] GC before operation: completed in 705.029 ms, heap usage 190.814 MB -> 48.289 MB. [2024-08-23T23:41:24.321Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:41:41.893Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:42:02.242Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:42:17.266Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:42:28.392Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:42:39.320Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:42:48.399Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:42:59.210Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:43:00.071Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:43:00.071Z] The best model improves the baseline by 14.52%. [2024-08-23T23:43:00.937Z] Movies recommended for you: [2024-08-23T23:43:00.937Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:43:00.937Z] There is no way to check that no silent failure occurred. [2024-08-23T23:43:00.937Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (113843.846 ms) ====== [2024-08-23T23:43:00.937Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-23T23:43:01.813Z] GC before operation: completed in 670.562 ms, heap usage 185.738 MB -> 48.173 MB. [2024-08-23T23:43:19.058Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:43:34.111Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:43:49.003Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:44:04.466Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:44:13.747Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:44:21.375Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:44:32.174Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:44:42.887Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:44:43.751Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:44:43.751Z] The best model improves the baseline by 14.52%. [2024-08-23T23:44:44.615Z] Movies recommended for you: [2024-08-23T23:44:44.615Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:44:44.615Z] There is no way to check that no silent failure occurred. [2024-08-23T23:44:44.615Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (102826.231 ms) ====== [2024-08-23T23:44:44.615Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-23T23:44:45.480Z] GC before operation: completed in 778.183 ms, heap usage 231.110 MB -> 47.916 MB. [2024-08-23T23:45:04.619Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T23:45:20.558Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T23:45:36.930Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T23:45:52.945Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T23:46:04.529Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T23:46:12.876Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T23:46:24.425Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T23:46:32.700Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T23:46:34.496Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-23T23:46:34.496Z] The best model improves the baseline by 14.52%. [2024-08-23T23:46:35.265Z] Movies recommended for you: [2024-08-23T23:46:35.265Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T23:46:35.265Z] There is no way to check that no silent failure occurred. [2024-08-23T23:46:35.265Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (110275.525 ms) ====== [2024-08-23T23:46:38.724Z] ----------------------------------- [2024-08-23T23:46:38.724Z] renaissance-movie-lens_0_PASSED [2024-08-23T23:46:38.724Z] ----------------------------------- [2024-08-23T23:46:38.724Z] [2024-08-23T23:46:38.724Z] TEST TEARDOWN: [2024-08-23T23:46:38.724Z] Nothing to be done for teardown. [2024-08-23T23:46:38.724Z] renaissance-movie-lens_0 Finish Time: Fri Aug 23 23:46:37 2024 Epoch Time (ms): 1724456797990