renaissance-movie-lens_0
[2024-08-08T02:46:15.560Z] Running test renaissance-movie-lens_0 ...
[2024-08-08T02:46:15.560Z] ===============================================
[2024-08-08T02:46:15.560Z] renaissance-movie-lens_0 Start Time: Thu Aug 8 02:46:15 2024 Epoch Time (ms): 1723085175063
[2024-08-08T02:46:15.560Z] variation: NoOptions
[2024-08-08T02:46:15.560Z] JVM_OPTIONS:
[2024-08-08T02:46:15.560Z] { \
[2024-08-08T02:46:15.560Z] echo ""; echo "TEST SETUP:"; \
[2024-08-08T02:46:15.561Z] echo "Nothing to be done for setup."; \
[2024-08-08T02:46:15.561Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17230842831066/renaissance-movie-lens_0"; \
[2024-08-08T02:46:15.561Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17230842831066/renaissance-movie-lens_0"; \
[2024-08-08T02:46:15.561Z] echo ""; echo "TESTING:"; \
[2024-08-08T02:46:15.561Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_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_s390x_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17230842831066/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-08T02:46:15.561Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17230842831066/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-08T02:46:15.561Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-08T02:46:15.561Z] echo "Nothing to be done for teardown."; \
[2024-08-08T02:46:15.561Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17230842831066/TestTargetResult";
[2024-08-08T02:46:15.561Z]
[2024-08-08T02:46:15.561Z] TEST SETUP:
[2024-08-08T02:46:15.561Z] Nothing to be done for setup.
[2024-08-08T02:46:15.561Z]
[2024-08-08T02:46:15.561Z] TESTING:
[2024-08-08T02:46:18.276Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-08T02:46:19.531Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-08T02:46:22.268Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-08T02:46:22.863Z] Training: 60056, validation: 20285, test: 19854
[2024-08-08T02:46:22.863Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-08T02:46:22.863Z] GC before operation: completed in 113.105 ms, heap usage 85.108 MB -> 36.386 MB.
[2024-08-08T02:46:29.174Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:46:32.752Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:46:36.336Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:46:39.089Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:46:40.334Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:46:41.567Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:46:43.512Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:46:44.746Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:46:44.746Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:46:44.746Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:46:44.746Z] Movies recommended for you:
[2024-08-08T02:46:44.746Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:46:44.746Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:46:44.746Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22088.168 ms) ======
[2024-08-08T02:46:44.746Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-08T02:46:45.336Z] GC before operation: completed in 146.319 ms, heap usage 194.580 MB -> 48.865 MB.
[2024-08-08T02:46:48.072Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:46:50.777Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:46:53.496Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:46:55.429Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:46:56.676Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:46:57.954Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:47:00.661Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:47:02.638Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:47:02.638Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:47:02.638Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:47:02.638Z] Movies recommended for you:
[2024-08-08T02:47:02.638Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:47:02.638Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:47:02.638Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17589.427 ms) ======
[2024-08-08T02:47:02.638Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-08T02:47:02.638Z] GC before operation: completed in 114.003 ms, heap usage 132.230 MB -> 48.374 MB.
[2024-08-08T02:47:05.393Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:47:07.344Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:47:10.062Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:47:11.994Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:47:13.236Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:47:15.203Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:47:16.376Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:47:18.310Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:47:18.310Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:47:18.310Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:47:18.310Z] Movies recommended for you:
[2024-08-08T02:47:18.310Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:47:18.311Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:47:18.311Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15476.148 ms) ======
[2024-08-08T02:47:18.311Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-08T02:47:18.311Z] GC before operation: completed in 97.245 ms, heap usage 101.827 MB -> 48.646 MB.
[2024-08-08T02:47:21.046Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:47:22.998Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:47:25.712Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:47:27.646Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:47:28.885Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:47:30.113Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:47:32.057Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:47:33.301Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:47:33.301Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:47:33.301Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:47:33.889Z] Movies recommended for you:
[2024-08-08T02:47:33.889Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:47:33.889Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:47:33.889Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15294.955 ms) ======
[2024-08-08T02:47:33.889Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-08T02:47:33.889Z] GC before operation: completed in 111.926 ms, heap usage 106.122 MB -> 48.935 MB.
[2024-08-08T02:47:35.825Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:47:38.560Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:47:41.289Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:47:43.229Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:47:44.464Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:47:45.701Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:47:46.938Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:47:48.165Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:47:48.165Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:47:48.165Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:47:48.759Z] Movies recommended for you:
[2024-08-08T02:47:48.759Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:47:48.759Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:47:48.759Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14767.208 ms) ======
[2024-08-08T02:47:48.759Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-08T02:47:48.759Z] GC before operation: completed in 124.425 ms, heap usage 109.328 MB -> 49.168 MB.
[2024-08-08T02:47:51.499Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:47:53.438Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:47:56.167Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:47:58.090Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:47:59.339Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:47:59.930Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:48:01.861Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:48:03.099Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:48:03.099Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:48:03.099Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:48:03.099Z] Movies recommended for you:
[2024-08-08T02:48:03.099Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:48:03.099Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:48:03.099Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14454.702 ms) ======
[2024-08-08T02:48:03.099Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-08T02:48:03.099Z] GC before operation: completed in 111.429 ms, heap usage 174.036 MB -> 49.154 MB.
[2024-08-08T02:48:05.631Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:48:08.365Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:48:10.322Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:48:13.049Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:48:14.301Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:48:16.262Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:48:17.504Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:48:18.751Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:48:19.346Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:48:19.346Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:48:19.346Z] Movies recommended for you:
[2024-08-08T02:48:19.346Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:48:19.346Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:48:19.346Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16048.042 ms) ======
[2024-08-08T02:48:19.346Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-08T02:48:19.346Z] GC before operation: completed in 99.633 ms, heap usage 119.822 MB -> 49.293 MB.
[2024-08-08T02:48:22.069Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:48:24.012Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:48:25.952Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:48:27.893Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:48:29.125Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:48:30.386Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:48:31.617Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:48:32.857Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:48:33.454Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:48:33.454Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:48:33.454Z] Movies recommended for you:
[2024-08-08T02:48:33.454Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:48:33.454Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:48:33.454Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13996.019 ms) ======
[2024-08-08T02:48:33.454Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-08T02:48:33.454Z] GC before operation: completed in 112.681 ms, heap usage 147.906 MB -> 49.542 MB.
[2024-08-08T02:48:36.175Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:48:37.410Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:48:40.130Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:48:42.073Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:48:43.304Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:48:44.546Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:48:45.789Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:48:47.020Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:48:47.755Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:48:47.755Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:48:47.755Z] Movies recommended for you:
[2024-08-08T02:48:47.755Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:48:47.755Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:48:47.755Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14176.499 ms) ======
[2024-08-08T02:48:47.755Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-08T02:48:47.755Z] GC before operation: completed in 133.420 ms, heap usage 156.354 MB -> 49.459 MB.
[2024-08-08T02:48:50.492Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:48:52.452Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:48:55.514Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:48:56.775Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:48:58.011Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:48:59.260Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:49:00.522Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:49:01.757Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:49:02.361Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:49:02.361Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:49:02.361Z] Movies recommended for you:
[2024-08-08T02:49:02.361Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:49:02.361Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:49:02.361Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14584.358 ms) ======
[2024-08-08T02:49:02.361Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-08T02:49:02.361Z] GC before operation: completed in 92.032 ms, heap usage 146.652 MB -> 49.475 MB.
[2024-08-08T02:49:04.289Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:49:06.225Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:49:08.948Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:49:10.881Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:49:12.132Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:49:13.377Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:49:15.321Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:49:16.557Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:49:16.557Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:49:16.557Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:49:16.557Z] Movies recommended for you:
[2024-08-08T02:49:16.557Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:49:16.557Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:49:16.557Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14291.070 ms) ======
[2024-08-08T02:49:16.557Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-08T02:49:17.152Z] GC before operation: completed in 147.375 ms, heap usage 198.788 MB -> 49.299 MB.
[2024-08-08T02:49:19.102Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:49:21.820Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:49:23.765Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:49:25.714Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:49:26.954Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:49:28.189Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:49:29.426Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:49:30.666Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:49:30.666Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:49:30.666Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:49:30.666Z] Movies recommended for you:
[2024-08-08T02:49:30.666Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:49:30.666Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:49:30.666Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13969.377 ms) ======
[2024-08-08T02:49:30.666Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-08T02:49:31.261Z] GC before operation: completed in 102.915 ms, heap usage 225.390 MB -> 49.573 MB.
[2024-08-08T02:49:33.201Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:49:35.149Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:49:37.086Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:49:39.035Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:49:40.294Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:49:41.536Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:49:43.121Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:49:43.717Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:49:43.717Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:49:43.717Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:49:44.311Z] Movies recommended for you:
[2024-08-08T02:49:44.311Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:49:44.311Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:49:44.311Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13118.536 ms) ======
[2024-08-08T02:49:44.311Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-08T02:49:44.311Z] GC before operation: completed in 136.473 ms, heap usage 118.062 MB -> 49.527 MB.
[2024-08-08T02:49:46.276Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:49:49.009Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:49:50.969Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:49:52.915Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:49:54.858Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:49:56.093Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:49:57.327Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:49:58.576Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:49:59.168Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:49:59.168Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:49:59.168Z] Movies recommended for you:
[2024-08-08T02:49:59.168Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:49:59.168Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:49:59.168Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14765.861 ms) ======
[2024-08-08T02:49:59.168Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-08T02:49:59.168Z] GC before operation: completed in 91.742 ms, heap usage 192.064 MB -> 49.438 MB.
[2024-08-08T02:50:01.122Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:50:03.057Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:50:05.778Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:50:07.710Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:50:09.647Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:50:10.242Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:50:12.182Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:50:13.426Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:50:13.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:50:13.426Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:50:13.426Z] Movies recommended for you:
[2024-08-08T02:50:13.426Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:50:13.426Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:50:13.426Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14430.872 ms) ======
[2024-08-08T02:50:13.426Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-08T02:50:13.426Z] GC before operation: completed in 139.999 ms, heap usage 149.350 MB -> 49.527 MB.
[2024-08-08T02:50:16.137Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:50:18.847Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:50:20.820Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:50:22.755Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:50:24.681Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:50:25.293Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:50:27.229Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:50:28.154Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:50:28.745Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:50:28.745Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:50:28.745Z] Movies recommended for you:
[2024-08-08T02:50:28.745Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:50:28.745Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:50:28.745Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14752.986 ms) ======
[2024-08-08T02:50:28.745Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-08T02:50:28.745Z] GC before operation: completed in 122.311 ms, heap usage 154.736 MB -> 49.649 MB.
[2024-08-08T02:50:30.686Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:50:33.417Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:50:35.367Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:50:36.594Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:50:38.528Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:50:39.760Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:50:41.001Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:50:42.233Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:50:42.233Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:50:42.233Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:50:42.823Z] Movies recommended for you:
[2024-08-08T02:50:42.823Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:50:42.823Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:50:42.823Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14062.564 ms) ======
[2024-08-08T02:50:42.823Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-08T02:50:42.823Z] GC before operation: completed in 126.819 ms, heap usage 149.734 MB -> 49.409 MB.
[2024-08-08T02:50:44.762Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:50:47.477Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:50:49.417Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:50:51.350Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:50:52.592Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:50:53.828Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:50:55.071Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:50:56.316Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:50:56.316Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:50:56.316Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:50:56.906Z] Movies recommended for you:
[2024-08-08T02:50:56.906Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:50:56.906Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:50:56.906Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13918.015 ms) ======
[2024-08-08T02:50:56.906Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-08T02:50:56.906Z] GC before operation: completed in 118.660 ms, heap usage 147.783 MB -> 49.514 MB.
[2024-08-08T02:50:59.628Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:51:01.622Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:51:04.334Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:51:06.278Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:51:08.215Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:51:08.803Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:51:10.739Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:51:12.005Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:51:12.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:51:12.005Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:51:12.005Z] Movies recommended for you:
[2024-08-08T02:51:12.005Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:51:12.005Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:51:12.005Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15526.210 ms) ======
[2024-08-08T02:51:12.005Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-08T02:51:12.682Z] GC before operation: completed in 134.649 ms, heap usage 135.130 MB -> 49.658 MB.
[2024-08-08T02:51:14.986Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T02:51:17.686Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T02:51:19.630Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T02:51:22.427Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T02:51:23.676Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T02:51:24.909Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T02:51:26.948Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T02:51:28.183Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T02:51:28.778Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-08T02:51:28.778Z] The best model improves the baseline by 14.34%.
[2024-08-08T02:51:28.778Z] Movies recommended for you:
[2024-08-08T02:51:28.778Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T02:51:28.778Z] There is no way to check that no silent failure occurred.
[2024-08-08T02:51:28.778Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16171.246 ms) ======
[2024-08-08T02:51:28.778Z] -----------------------------------
[2024-08-08T02:51:28.778Z] renaissance-movie-lens_0_PASSED
[2024-08-08T02:51:28.778Z] -----------------------------------
[2024-08-08T02:51:28.778Z]
[2024-08-08T02:51:28.778Z] TEST TEARDOWN:
[2024-08-08T02:51:28.778Z] Nothing to be done for teardown.
[2024-08-08T02:51:28.778Z] renaissance-movie-lens_0 Finish Time: Thu Aug 8 02:51:28 2024 Epoch Time (ms): 1723085488720