[2024-08-08T04:13:15.018Z] Running test renaissance-movie-lens_0 ... [2024-08-08T04:13:15.018Z] =============================================== [2024-08-08T04:13:15.018Z] renaissance-movie-lens_0 Start Time: Thu Aug 8 04:13:14 2024 Epoch Time (ms): 1723090394508 [2024-08-08T04:13:15.018Z] variation: NoOptions [2024-08-08T04:13:15.018Z] JVM_OPTIONS: [2024-08-08T04:13:15.018Z] { \ [2024-08-08T04:13:15.018Z] echo ""; echo "TEST SETUP:"; \ [2024-08-08T04:13:15.018Z] echo "Nothing to be done for setup."; \ [2024-08-08T04:13:15.018Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230873725470/renaissance-movie-lens_0"; \ [2024-08-08T04:13:15.018Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230873725470/renaissance-movie-lens_0"; \ [2024-08-08T04:13:15.018Z] echo ""; echo "TESTING:"; \ [2024-08-08T04:13:15.019Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-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_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230873725470/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-08T04:13:15.019Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230873725470/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-08T04:13:15.019Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-08T04:13:15.019Z] echo "Nothing to be done for teardown."; \ [2024-08-08T04:13:15.019Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230873725470/TestTargetResult"; [2024-08-08T04:13:15.019Z] [2024-08-08T04:13:15.019Z] TEST SETUP: [2024-08-08T04:13:15.019Z] Nothing to be done for setup. [2024-08-08T04:13:15.019Z] [2024-08-08T04:13:15.019Z] TESTING: [2024-08-08T04:13:22.226Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-08T04:13:28.119Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-08T04:13:38.727Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-08T04:13:40.427Z] Training: 60056, validation: 20285, test: 19854 [2024-08-08T04:13:40.427Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-08T04:13:40.427Z] GC before operation: completed in 301.215 ms, heap usage 95.241 MB -> 36.443 MB. [2024-08-08T04:14:03.468Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:14:20.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:14:32.837Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:14:45.542Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:14:51.520Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:14:57.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:15:04.740Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:15:10.851Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:15:11.678Z] 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. [2024-08-08T04:15:11.678Z] The best model improves the baseline by 14.52%. [2024-08-08T04:15:11.678Z] Movies recommended for you: [2024-08-08T04:15:11.678Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:15:11.678Z] There is no way to check that no silent failure occurred. [2024-08-08T04:15:11.678Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (91579.903 ms) ====== [2024-08-08T04:15:11.678Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-08T04:15:12.506Z] GC before operation: completed in 481.377 ms, heap usage 194.156 MB -> 49.052 MB. [2024-08-08T04:15:21.254Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:15:31.690Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:15:40.419Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:15:47.913Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:15:53.907Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:15:59.842Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:16:05.783Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:16:10.574Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:16:10.574Z] 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. [2024-08-08T04:16:10.574Z] The best model improves the baseline by 14.52%. [2024-08-08T04:16:11.407Z] Movies recommended for you: [2024-08-08T04:16:11.407Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:16:11.407Z] There is no way to check that no silent failure occurred. [2024-08-08T04:16:11.407Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (58533.528 ms) ====== [2024-08-08T04:16:11.407Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-08T04:16:11.407Z] GC before operation: completed in 254.894 ms, heap usage 179.664 MB -> 49.058 MB. [2024-08-08T04:16:20.116Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:16:29.065Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:16:37.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:16:47.291Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:16:52.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:16:57.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:17:02.763Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:17:07.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:17:08.367Z] 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. [2024-08-08T04:17:08.367Z] The best model improves the baseline by 14.52%. [2024-08-08T04:17:08.367Z] Movies recommended for you: [2024-08-08T04:17:08.367Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:17:08.367Z] There is no way to check that no silent failure occurred. [2024-08-08T04:17:08.367Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (57375.369 ms) ====== [2024-08-08T04:17:08.367Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-08T04:17:09.199Z] GC before operation: completed in 326.741 ms, heap usage 128.163 MB -> 49.270 MB. [2024-08-08T04:17:17.346Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:17:25.429Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:17:33.518Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:17:41.614Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:17:46.497Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:17:50.849Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:17:56.302Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:18:00.782Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:18:00.782Z] 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. [2024-08-08T04:18:01.521Z] The best model improves the baseline by 14.52%. [2024-08-08T04:18:01.521Z] Movies recommended for you: [2024-08-08T04:18:01.521Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:18:01.521Z] There is no way to check that no silent failure occurred. [2024-08-08T04:18:01.521Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (52467.820 ms) ====== [2024-08-08T04:18:01.521Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-08T04:18:01.521Z] GC before operation: completed in 310.763 ms, heap usage 184.801 MB -> 49.667 MB. [2024-08-08T04:18:11.188Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:18:19.264Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:18:27.327Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:18:35.410Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:18:40.250Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:18:44.573Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:18:50.035Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:18:54.338Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:18:54.338Z] 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. [2024-08-08T04:18:54.338Z] The best model improves the baseline by 14.52%. [2024-08-08T04:18:55.078Z] Movies recommended for you: [2024-08-08T04:18:55.078Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:18:55.078Z] There is no way to check that no silent failure occurred. [2024-08-08T04:18:55.078Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (53201.679 ms) ====== [2024-08-08T04:18:55.078Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-08T04:18:55.078Z] GC before operation: completed in 309.244 ms, heap usage 107.667 MB -> 49.770 MB. [2024-08-08T04:19:04.723Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:19:11.412Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:19:19.450Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:19:27.514Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:19:32.316Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:19:37.778Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:19:42.088Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:19:47.518Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:19:48.252Z] 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. [2024-08-08T04:19:48.252Z] The best model improves the baseline by 14.52%. [2024-08-08T04:19:48.993Z] Movies recommended for you: [2024-08-08T04:19:48.994Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:19:48.994Z] There is no way to check that no silent failure occurred. [2024-08-08T04:19:48.994Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (53653.546 ms) ====== [2024-08-08T04:19:48.994Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-08T04:19:48.994Z] GC before operation: completed in 351.339 ms, heap usage 214.488 MB -> 49.823 MB. [2024-08-08T04:19:58.607Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:20:06.617Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:20:14.779Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:20:22.830Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:20:27.608Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:20:33.039Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:20:37.372Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:20:40.710Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:20:41.458Z] 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. [2024-08-08T04:20:41.458Z] The best model improves the baseline by 14.52%. [2024-08-08T04:20:42.298Z] Movies recommended for you: [2024-08-08T04:20:42.298Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:20:42.298Z] There is no way to check that no silent failure occurred. [2024-08-08T04:20:42.298Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (52788.024 ms) ====== [2024-08-08T04:20:42.298Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-08T04:20:42.298Z] GC before operation: completed in 276.360 ms, heap usage 140.291 MB -> 51.079 MB. [2024-08-08T04:20:50.324Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:20:57.006Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:21:05.039Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:21:11.852Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:21:15.149Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:21:19.990Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:21:24.310Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:21:28.632Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:21:28.632Z] 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. [2024-08-08T04:21:28.632Z] The best model improves the baseline by 14.52%. [2024-08-08T04:21:29.374Z] Movies recommended for you: [2024-08-08T04:21:29.374Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:21:29.374Z] There is no way to check that no silent failure occurred. [2024-08-08T04:21:29.374Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (46733.608 ms) ====== [2024-08-08T04:21:29.374Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-08T04:21:29.374Z] GC before operation: completed in 308.509 ms, heap usage 312.319 MB -> 50.466 MB. [2024-08-08T04:21:37.399Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:21:45.443Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:21:52.189Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:22:00.308Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:22:04.639Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:22:08.951Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:22:13.393Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:22:17.822Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:22:17.822Z] 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. [2024-08-08T04:22:17.822Z] The best model improves the baseline by 14.52%. [2024-08-08T04:22:17.822Z] Movies recommended for you: [2024-08-08T04:22:17.822Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:22:17.822Z] There is no way to check that no silent failure occurred. [2024-08-08T04:22:17.822Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (48762.801 ms) ====== [2024-08-08T04:22:17.822Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-08T04:22:18.559Z] GC before operation: completed in 269.381 ms, heap usage 339.624 MB -> 50.227 MB. [2024-08-08T04:22:26.572Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:22:33.220Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:22:39.885Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:22:47.919Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:22:51.213Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:22:55.541Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:23:01.054Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:23:04.354Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:23:05.090Z] 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. [2024-08-08T04:23:05.858Z] The best model improves the baseline by 14.52%. [2024-08-08T04:23:05.858Z] Movies recommended for you: [2024-08-08T04:23:05.858Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:23:05.858Z] There is no way to check that no silent failure occurred. [2024-08-08T04:23:05.858Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (47291.058 ms) ====== [2024-08-08T04:23:05.858Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-08T04:23:05.858Z] GC before operation: completed in 318.207 ms, heap usage 313.453 MB -> 50.308 MB. [2024-08-08T04:23:14.087Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:23:20.795Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:23:28.878Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:23:35.494Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:23:39.796Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:23:43.091Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:23:48.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:23:51.782Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:23:52.515Z] 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. [2024-08-08T04:23:52.515Z] The best model improves the baseline by 14.52%. [2024-08-08T04:23:52.515Z] Movies recommended for you: [2024-08-08T04:23:52.515Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:23:52.515Z] There is no way to check that no silent failure occurred. [2024-08-08T04:23:52.515Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (46828.749 ms) ====== [2024-08-08T04:23:52.515Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-08T04:23:53.246Z] GC before operation: completed in 265.948 ms, heap usage 282.914 MB -> 49.990 MB. [2024-08-08T04:23:59.186Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:24:05.838Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:24:12.502Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:24:20.561Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:24:23.835Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:24:28.126Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:24:33.516Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:24:37.858Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:24:38.610Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:24:38.610Z] The best model improves the baseline by 14.52%. [2024-08-08T04:24:38.610Z] Movies recommended for you: [2024-08-08T04:24:38.610Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:24:38.610Z] There is no way to check that no silent failure occurred. [2024-08-08T04:24:38.610Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (45576.165 ms) ====== [2024-08-08T04:24:38.610Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-08T04:24:39.351Z] GC before operation: completed in 296.064 ms, heap usage 218.225 MB -> 50.110 MB. [2024-08-08T04:24:47.357Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:24:54.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:25:02.635Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:25:09.350Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:25:14.771Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:25:18.094Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:25:23.513Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:25:27.830Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:25:28.570Z] 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. [2024-08-08T04:25:28.570Z] The best model improves the baseline by 14.52%. [2024-08-08T04:25:29.318Z] Movies recommended for you: [2024-08-08T04:25:29.318Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:25:29.318Z] There is no way to check that no silent failure occurred. [2024-08-08T04:25:29.318Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (50103.320 ms) ====== [2024-08-08T04:25:29.318Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-08T04:25:29.318Z] GC before operation: completed in 311.517 ms, heap usage 197.717 MB -> 50.280 MB. [2024-08-08T04:25:37.370Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:25:45.490Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:25:52.410Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:25:59.069Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:26:03.414Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:26:07.852Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:26:12.378Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:26:16.688Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:26:17.430Z] 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. [2024-08-08T04:26:17.430Z] The best model improves the baseline by 14.52%. [2024-08-08T04:26:17.430Z] Movies recommended for you: [2024-08-08T04:26:17.430Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:26:17.430Z] There is no way to check that no silent failure occurred. [2024-08-08T04:26:17.430Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (48144.803 ms) ====== [2024-08-08T04:26:17.430Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-08T04:26:18.194Z] GC before operation: completed in 341.781 ms, heap usage 106.120 MB -> 49.931 MB. [2024-08-08T04:26:24.903Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:26:33.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:26:40.360Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:26:47.223Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:26:50.629Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:26:55.071Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:26:59.503Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:27:03.931Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:27:04.688Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:27:04.688Z] The best model improves the baseline by 14.52%. [2024-08-08T04:27:04.688Z] Movies recommended for you: [2024-08-08T04:27:04.688Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:27:04.688Z] There is no way to check that no silent failure occurred. [2024-08-08T04:27:04.688Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (46744.100 ms) ====== [2024-08-08T04:27:04.688Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-08T04:27:04.688Z] GC before operation: completed in 335.339 ms, heap usage 127.472 MB -> 50.105 MB. [2024-08-08T04:27:12.925Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:27:19.715Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:27:26.527Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:27:32.695Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:27:37.127Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:27:41.555Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:27:45.999Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:27:49.390Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:27:50.159Z] 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. [2024-08-08T04:27:50.159Z] The best model improves the baseline by 14.52%. [2024-08-08T04:27:50.913Z] Movies recommended for you: [2024-08-08T04:27:50.913Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:27:50.913Z] There is no way to check that no silent failure occurred. [2024-08-08T04:27:50.913Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (45598.695 ms) ====== [2024-08-08T04:27:50.913Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-08T04:27:50.913Z] GC before operation: completed in 318.369 ms, heap usage 308.755 MB -> 50.406 MB. [2024-08-08T04:27:59.135Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:28:04.793Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:28:11.689Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:28:18.559Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:28:22.135Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:28:25.501Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:28:29.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:28:34.352Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:28:34.352Z] 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. [2024-08-08T04:28:34.352Z] The best model improves the baseline by 14.52%. [2024-08-08T04:28:35.110Z] Movies recommended for you: [2024-08-08T04:28:35.110Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:28:35.110Z] There is no way to check that no silent failure occurred. [2024-08-08T04:28:35.110Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43933.669 ms) ====== [2024-08-08T04:28:35.110Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-08T04:28:35.110Z] GC before operation: completed in 324.860 ms, heap usage 300.758 MB -> 50.182 MB. [2024-08-08T04:28:43.291Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:28:48.826Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:28:56.998Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:29:01.398Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:29:04.755Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:29:08.122Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:29:11.493Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:29:15.359Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:29:15.359Z] 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. [2024-08-08T04:29:15.359Z] The best model improves the baseline by 14.52%. [2024-08-08T04:29:16.123Z] Movies recommended for you: [2024-08-08T04:29:16.123Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:29:16.123Z] There is no way to check that no silent failure occurred. [2024-08-08T04:29:16.123Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (40662.831 ms) ====== [2024-08-08T04:29:16.123Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-08T04:29:16.123Z] GC before operation: completed in 282.560 ms, heap usage 192.291 MB -> 50.181 MB. [2024-08-08T04:29:22.903Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:29:29.676Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:29:35.195Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:29:41.981Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:29:46.378Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:29:50.761Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:29:55.168Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:29:58.557Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:29:59.308Z] 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. [2024-08-08T04:29:59.308Z] The best model improves the baseline by 14.52%. [2024-08-08T04:29:59.308Z] Movies recommended for you: [2024-08-08T04:29:59.308Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:29:59.308Z] There is no way to check that no silent failure occurred. [2024-08-08T04:29:59.308Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (43383.501 ms) ====== [2024-08-08T04:29:59.308Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-08T04:30:00.072Z] GC before operation: completed in 254.524 ms, heap usage 95.291 MB -> 50.272 MB. [2024-08-08T04:30:06.883Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:30:12.911Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:30:19.734Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:30:25.257Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:30:29.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:30:33.012Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:30:37.437Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:30:40.811Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:30:41.573Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:30:42.349Z] The best model improves the baseline by 14.52%. [2024-08-08T04:30:42.349Z] Movies recommended for you: [2024-08-08T04:30:42.349Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:30:42.349Z] There is no way to check that no silent failure occurred. [2024-08-08T04:30:42.349Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (42469.590 ms) ====== [2024-08-08T04:30:43.103Z] ----------------------------------- [2024-08-08T04:30:43.103Z] renaissance-movie-lens_0_PASSED [2024-08-08T04:30:43.103Z] ----------------------------------- [2024-08-08T04:30:43.103Z] [2024-08-08T04:30:43.103Z] TEST TEARDOWN: [2024-08-08T04:30:43.103Z] Nothing to be done for teardown. [2024-08-08T04:30:43.103Z] renaissance-movie-lens_0 Finish Time: Thu Aug 8 04:30:42 2024 Epoch Time (ms): 1723091442825