renaissance-movie-lens_0
[2024-08-22T00:23:27.489Z] Running test renaissance-movie-lens_0 ...
[2024-08-22T00:23:27.489Z] ===============================================
[2024-08-22T00:23:27.489Z] renaissance-movie-lens_0 Start Time: Thu Aug 22 00:23:26 2024 Epoch Time (ms): 1724286207009
[2024-08-22T00:23:27.489Z] variation: NoOptions
[2024-08-22T00:23:27.489Z] JVM_OPTIONS:
[2024-08-22T00:23:27.489Z] { \
[2024-08-22T00:23:27.489Z] echo ""; echo "TEST SETUP:"; \
[2024-08-22T00:23:27.489Z] echo "Nothing to be done for setup."; \
[2024-08-22T00:23:27.489Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17242848193106/renaissance-movie-lens_0"; \
[2024-08-22T00:23:27.489Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17242848193106/renaissance-movie-lens_0"; \
[2024-08-22T00:23:27.489Z] echo ""; echo "TESTING:"; \
[2024-08-22T00:23:27.489Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/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_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17242848193106/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-22T00:23:27.489Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17242848193106/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-22T00:23:27.489Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-22T00:23:27.489Z] echo "Nothing to be done for teardown."; \
[2024-08-22T00:23:27.489Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17242848193106/TestTargetResult";
[2024-08-22T00:23:27.489Z]
[2024-08-22T00:23:27.489Z] TEST SETUP:
[2024-08-22T00:23:27.489Z] Nothing to be done for setup.
[2024-08-22T00:23:27.489Z]
[2024-08-22T00:23:27.489Z] TESTING:
[2024-08-22T00:23:36.093Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-22T00:23:37.380Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-22T00:23:43.314Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-22T00:23:43.314Z] Training: 60056, validation: 20285, test: 19854
[2024-08-22T00:23:43.314Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-22T00:23:43.314Z] GC before operation: completed in 194.594 ms, heap usage 94.634 MB -> 36.944 MB.
[2024-08-22T00:23:53.888Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:24:00.153Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:24:06.099Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:24:11.181Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:24:14.760Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:24:17.753Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:24:20.634Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:24:22.789Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:24:23.433Z] 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.
[2024-08-22T00:24:23.433Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:24:24.065Z] Movies recommended for you:
[2024-08-22T00:24:24.066Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:24:24.066Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:24:24.066Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (40605.585 ms) ======
[2024-08-22T00:24:24.066Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-22T00:24:24.066Z] GC before operation: completed in 164.680 ms, heap usage 253.112 MB -> 54.552 MB.
[2024-08-22T00:24:28.886Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:24:32.643Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:24:37.404Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:24:41.377Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:24:44.418Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:24:46.529Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:24:48.700Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:24:50.768Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:24:51.490Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-22T00:24:51.490Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:24:51.490Z] Movies recommended for you:
[2024-08-22T00:24:51.490Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:24:51.490Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:24:51.490Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (27619.035 ms) ======
[2024-08-22T00:24:51.490Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-22T00:24:52.222Z] GC before operation: completed in 158.682 ms, heap usage 199.166 MB -> 48.955 MB.
[2024-08-22T00:24:56.242Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:25:01.195Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:25:06.825Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:25:11.777Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:25:13.083Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:25:16.034Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:25:18.975Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:25:20.307Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:25:20.307Z] 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.
[2024-08-22T00:25:20.307Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:25:20.913Z] Movies recommended for you:
[2024-08-22T00:25:20.913Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:25:20.913Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:25:20.913Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (28866.209 ms) ======
[2024-08-22T00:25:20.913Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-22T00:25:20.913Z] GC before operation: completed in 222.184 ms, heap usage 242.671 MB -> 49.277 MB.
[2024-08-22T00:25:24.805Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:25:28.568Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:25:32.317Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:25:36.076Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:25:37.381Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:25:40.258Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:25:42.386Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:25:44.398Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:25:45.026Z] 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.
[2024-08-22T00:25:45.026Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:25:45.026Z] Movies recommended for you:
[2024-08-22T00:25:45.026Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:25:45.026Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:25:45.026Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23942.474 ms) ======
[2024-08-22T00:25:45.026Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-22T00:25:45.026Z] GC before operation: completed in 133.797 ms, heap usage 266.199 MB -> 49.676 MB.
[2024-08-22T00:25:50.684Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:25:53.777Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:25:58.723Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:26:01.711Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:26:04.676Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:26:07.595Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:26:09.721Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:26:12.586Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:26:12.586Z] 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.
[2024-08-22T00:26:13.244Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:26:13.244Z] Movies recommended for you:
[2024-08-22T00:26:13.244Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:26:13.244Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:26:13.244Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (28056.951 ms) ======
[2024-08-22T00:26:13.244Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-22T00:26:13.244Z] GC before operation: completed in 164.349 ms, heap usage 264.517 MB -> 49.864 MB.
[2024-08-22T00:26:17.058Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:26:20.769Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:26:24.562Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:26:27.467Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:26:30.479Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:26:31.761Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:26:34.630Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:26:37.101Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:26:37.101Z] 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.
[2024-08-22T00:26:37.101Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:26:37.741Z] Movies recommended for you:
[2024-08-22T00:26:37.741Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:26:37.741Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:26:37.741Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (24246.934 ms) ======
[2024-08-22T00:26:37.741Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-22T00:26:37.741Z] GC before operation: completed in 164.023 ms, heap usage 267.622 MB -> 49.845 MB.
[2024-08-22T00:26:41.725Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:26:44.538Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:26:49.385Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:26:52.257Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:26:54.290Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:26:56.346Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:26:58.466Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:27:00.518Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:27:01.189Z] 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.
[2024-08-22T00:27:01.189Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:27:01.189Z] Movies recommended for you:
[2024-08-22T00:27:01.189Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:27:01.189Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:27:01.189Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23410.237 ms) ======
[2024-08-22T00:27:01.189Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-22T00:27:01.189Z] GC before operation: completed in 110.393 ms, heap usage 182.281 MB -> 49.927 MB.
[2024-08-22T00:27:04.013Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:27:07.830Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:27:10.736Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:27:14.665Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:27:16.791Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:27:18.089Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:27:20.205Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:27:22.738Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:27:23.370Z] 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.
[2024-08-22T00:27:23.370Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:27:23.370Z] Movies recommended for you:
[2024-08-22T00:27:23.370Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:27:23.370Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:27:23.370Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22157.317 ms) ======
[2024-08-22T00:27:23.370Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-22T00:27:23.370Z] GC before operation: completed in 129.845 ms, heap usage 212.347 MB -> 50.235 MB.
[2024-08-22T00:27:27.207Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:27:31.047Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:27:34.851Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:27:37.756Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:27:39.804Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:27:42.043Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:27:44.957Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:27:46.229Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:27:46.884Z] 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.
[2024-08-22T00:27:46.884Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:27:46.884Z] Movies recommended for you:
[2024-08-22T00:27:46.884Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:27:46.884Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:27:46.884Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (23325.786 ms) ======
[2024-08-22T00:27:46.884Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-22T00:27:46.884Z] GC before operation: completed in 97.298 ms, heap usage 127.640 MB -> 49.967 MB.
[2024-08-22T00:27:50.737Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:27:53.581Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:27:57.347Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:28:01.282Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:28:03.360Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:28:04.672Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:28:06.749Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:28:08.846Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:28:10.002Z] 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.
[2024-08-22T00:28:10.002Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:28:10.002Z] Movies recommended for you:
[2024-08-22T00:28:10.002Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:28:10.002Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:28:10.002Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (22692.269 ms) ======
[2024-08-22T00:28:10.002Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-22T00:28:10.002Z] GC before operation: completed in 137.350 ms, heap usage 236.062 MB -> 50.107 MB.
[2024-08-22T00:28:13.992Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:28:19.037Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:28:23.921Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:28:27.828Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:28:29.930Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:28:32.106Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:28:34.267Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:28:36.466Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:28:37.112Z] 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.
[2024-08-22T00:28:37.112Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:28:37.769Z] Movies recommended for you:
[2024-08-22T00:28:37.769Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:28:37.769Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:28:37.769Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27719.287 ms) ======
[2024-08-22T00:28:37.769Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-22T00:28:37.769Z] GC before operation: completed in 137.724 ms, heap usage 309.657 MB -> 49.925 MB.
[2024-08-22T00:28:40.649Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:28:44.466Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:28:48.361Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:28:52.193Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:28:54.296Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:28:56.879Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:28:58.895Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:29:00.918Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:29:00.918Z] 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.
[2024-08-22T00:29:00.918Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:29:00.918Z] Movies recommended for you:
[2024-08-22T00:29:00.918Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:29:00.918Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:29:00.918Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (23476.490 ms) ======
[2024-08-22T00:29:00.918Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-22T00:29:01.532Z] GC before operation: completed in 161.938 ms, heap usage 114.759 MB -> 49.937 MB.
[2024-08-22T00:29:04.337Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:29:07.181Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:29:10.996Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:29:13.835Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:29:15.893Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:29:17.207Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:29:20.080Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:29:23.171Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:29:23.171Z] 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.
[2024-08-22T00:29:23.171Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:29:23.802Z] Movies recommended for you:
[2024-08-22T00:29:23.802Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:29:23.802Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:29:23.802Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22245.178 ms) ======
[2024-08-22T00:29:23.802Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-22T00:29:23.802Z] GC before operation: completed in 98.650 ms, heap usage 354.223 MB -> 53.553 MB.
[2024-08-22T00:29:26.667Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:29:30.496Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:29:35.280Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:29:39.108Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:29:41.421Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:29:43.465Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:29:46.349Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:29:47.639Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:29:48.246Z] 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.
[2024-08-22T00:29:48.246Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:29:48.246Z] Movies recommended for you:
[2024-08-22T00:29:48.246Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:29:48.246Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:29:48.246Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (24654.752 ms) ======
[2024-08-22T00:29:48.246Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-22T00:29:48.246Z] GC before operation: completed in 166.975 ms, heap usage 197.744 MB -> 49.945 MB.
[2024-08-22T00:29:52.147Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:29:56.048Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:29:59.808Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:30:02.706Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:30:05.595Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:30:06.942Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:30:09.952Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:30:12.825Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:30:12.825Z] 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.
[2024-08-22T00:30:12.825Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:30:12.825Z] Movies recommended for you:
[2024-08-22T00:30:12.825Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:30:12.825Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:30:12.825Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (24530.094 ms) ======
[2024-08-22T00:30:12.825Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-22T00:30:13.457Z] GC before operation: completed in 207.962 ms, heap usage 380.753 MB -> 53.460 MB.
[2024-08-22T00:30:17.289Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:30:22.058Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:30:24.949Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:30:28.192Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:30:31.117Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:30:32.470Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:30:35.404Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:30:37.436Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:30:38.130Z] 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.
[2024-08-22T00:30:38.130Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:30:38.130Z] Movies recommended for you:
[2024-08-22T00:30:38.130Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:30:38.130Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:30:38.130Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (25086.124 ms) ======
[2024-08-22T00:30:38.130Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-22T00:30:38.130Z] GC before operation: completed in 164.040 ms, heap usage 267.191 MB -> 50.336 MB.
[2024-08-22T00:30:42.006Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:30:45.888Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:30:49.940Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:30:53.800Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:30:55.831Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:30:57.886Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:30:59.970Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:31:02.143Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:31:02.796Z] 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.
[2024-08-22T00:31:02.796Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:31:03.444Z] Movies recommended for you:
[2024-08-22T00:31:03.444Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:31:03.444Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:31:03.444Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (24704.809 ms) ======
[2024-08-22T00:31:03.444Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-22T00:31:03.444Z] GC before operation: completed in 385.931 ms, heap usage 88.579 MB -> 49.960 MB.
[2024-08-22T00:31:07.190Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:31:10.235Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:31:13.698Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:31:16.629Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:31:17.897Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:31:19.934Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:31:22.904Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:31:24.935Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:31:24.935Z] 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.
[2024-08-22T00:31:25.578Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:31:25.578Z] Movies recommended for you:
[2024-08-22T00:31:25.578Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:31:25.578Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:31:25.578Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (21870.414 ms) ======
[2024-08-22T00:31:25.578Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-22T00:31:25.578Z] GC before operation: completed in 141.190 ms, heap usage 64.224 MB -> 52.982 MB.
[2024-08-22T00:31:29.359Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:31:33.424Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:31:36.405Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:31:39.188Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:31:41.286Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:31:43.417Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:31:45.564Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:31:47.644Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:31:47.644Z] 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.
[2024-08-22T00:31:47.644Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:31:47.644Z] Movies recommended for you:
[2024-08-22T00:31:47.644Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:31:47.644Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:31:47.644Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22162.568 ms) ======
[2024-08-22T00:31:47.644Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-22T00:31:47.644Z] GC before operation: completed in 98.884 ms, heap usage 288.719 MB -> 50.396 MB.
[2024-08-22T00:31:50.480Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T00:31:54.226Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T00:31:58.296Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T00:32:01.463Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T00:32:03.561Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T00:32:05.317Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T00:32:07.454Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T00:32:09.667Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T00:32:09.667Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-22T00:32:09.667Z] The best model improves the baseline by 14.34%.
[2024-08-22T00:32:09.667Z] Movies recommended for you:
[2024-08-22T00:32:09.667Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T00:32:09.667Z] There is no way to check that no silent failure occurred.
[2024-08-22T00:32:09.667Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (22158.205 ms) ======
[2024-08-22T00:32:11.131Z] -----------------------------------
[2024-08-22T00:32:11.131Z] renaissance-movie-lens_0_PASSED
[2024-08-22T00:32:11.131Z] -----------------------------------
[2024-08-22T00:32:11.131Z]
[2024-08-22T00:32:11.131Z] TEST TEARDOWN:
[2024-08-22T00:32:11.131Z] Nothing to be done for teardown.
[2024-08-22T00:32:11.131Z] renaissance-movie-lens_0 Finish Time: Thu Aug 22 00:32:10 2024 Epoch Time (ms): 1724286730710