renaissance-movie-lens_0
[2024-08-21T20:43:19.105Z] Running test renaissance-movie-lens_0 ...
[2024-08-21T20:43:19.105Z] ===============================================
[2024-08-21T20:43:19.105Z] renaissance-movie-lens_0 Start Time: Wed Aug 21 20:43:18 2024 Epoch Time (ms): 1724272998996
[2024-08-21T20:43:19.105Z] variation: NoOptions
[2024-08-21T20:43:19.105Z] JVM_OPTIONS:
[2024-08-21T20:43:19.105Z] { \
[2024-08-21T20:43:19.105Z] echo ""; echo "TEST SETUP:"; \
[2024-08-21T20:43:19.105Z] echo "Nothing to be done for setup."; \
[2024-08-21T20:43:19.105Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242721506809/renaissance-movie-lens_0"; \
[2024-08-21T20:43:19.105Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242721506809/renaissance-movie-lens_0"; \
[2024-08-21T20:43:19.105Z] echo ""; echo "TESTING:"; \
[2024-08-21T20:43:19.105Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_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_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242721506809/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-21T20:43:19.105Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242721506809/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-21T20:43:19.105Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-21T20:43:19.105Z] echo "Nothing to be done for teardown."; \
[2024-08-21T20:43:19.105Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242721506809/TestTargetResult";
[2024-08-21T20:43:19.105Z]
[2024-08-21T20:43:19.105Z] TEST SETUP:
[2024-08-21T20:43:19.105Z] Nothing to be done for setup.
[2024-08-21T20:43:19.105Z]
[2024-08-21T20:43:19.105Z] TESTING:
[2024-08-21T20:43:23.119Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-21T20:43:24.036Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-21T20:43:26.954Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-21T20:43:26.954Z] Training: 60056, validation: 20285, test: 19854
[2024-08-21T20:43:26.954Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-21T20:43:26.954Z] GC before operation: completed in 60.827 ms, heap usage 165.573 MB -> 37.422 MB.
[2024-08-21T20:43:32.870Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:43:35.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:43:38.723Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:43:40.610Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:43:42.499Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:43:44.387Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:43:45.307Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:43:47.198Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:43:47.198Z] 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.
[2024-08-21T20:43:47.198Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:43:47.198Z] Movies recommended for you:
[2024-08-21T20:43:47.198Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:43:47.198Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:43:47.198Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20158.112 ms) ======
[2024-08-21T20:43:47.198Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-21T20:43:47.198Z] GC before operation: completed in 89.411 ms, heap usage 66.447 MB -> 56.865 MB.
[2024-08-21T20:43:50.118Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:43:52.011Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:43:54.937Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:43:56.830Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:43:58.720Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:43:59.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:44:01.527Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:44:02.446Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:44:03.364Z] 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.
[2024-08-21T20:44:03.364Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:44:03.364Z] Movies recommended for you:
[2024-08-21T20:44:03.364Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:44:03.364Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:44:03.364Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15503.863 ms) ======
[2024-08-21T20:44:03.364Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-21T20:44:03.364Z] GC before operation: completed in 121.257 ms, heap usage 301.309 MB -> 49.788 MB.
[2024-08-21T20:44:05.251Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:44:07.137Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:44:10.051Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:44:11.935Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:44:13.020Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:44:14.910Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:44:15.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:44:16.748Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:44:17.666Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-21T20:44:17.666Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:44:17.666Z] Movies recommended for you:
[2024-08-21T20:44:17.666Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:44:17.666Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:44:17.666Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14371.962 ms) ======
[2024-08-21T20:44:17.666Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-21T20:44:17.667Z] GC before operation: completed in 85.702 ms, heap usage 208.416 MB -> 50.060 MB.
[2024-08-21T20:44:19.555Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:44:21.444Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:44:24.370Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:44:26.268Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:44:28.347Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:44:28.347Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:44:30.232Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:44:31.149Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:44:31.149Z] 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.
[2024-08-21T20:44:31.149Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:44:32.067Z] Movies recommended for you:
[2024-08-21T20:44:32.067Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:44:32.067Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:44:32.067Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13940.719 ms) ======
[2024-08-21T20:44:32.067Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-21T20:44:32.067Z] GC before operation: completed in 86.835 ms, heap usage 89.419 MB -> 50.198 MB.
[2024-08-21T20:44:33.953Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:44:35.840Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:44:37.727Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:44:40.680Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:44:41.748Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:44:42.667Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:44:44.552Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:44:45.470Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:44:46.389Z] 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.
[2024-08-21T20:44:46.389Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:44:46.389Z] Movies recommended for you:
[2024-08-21T20:44:46.389Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:44:46.389Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:44:46.389Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14456.050 ms) ======
[2024-08-21T20:44:46.389Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-21T20:44:46.389Z] GC before operation: completed in 77.783 ms, heap usage 115.847 MB -> 50.542 MB.
[2024-08-21T20:44:48.277Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:44:50.167Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:44:52.055Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:44:54.972Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:44:55.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:44:56.812Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:44:58.701Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:44:59.618Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:44:59.618Z] 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.
[2024-08-21T20:44:59.618Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:44:59.618Z] Movies recommended for you:
[2024-08-21T20:44:59.618Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:44:59.618Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:44:59.618Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13647.874 ms) ======
[2024-08-21T20:44:59.618Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-21T20:44:59.618Z] GC before operation: completed in 88.403 ms, heap usage 393.219 MB -> 53.958 MB.
[2024-08-21T20:45:02.538Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:45:04.424Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:45:06.314Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:45:08.203Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:45:09.155Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:45:11.042Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:45:11.961Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:45:13.850Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:45:13.850Z] 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.
[2024-08-21T20:45:13.850Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:45:13.850Z] Movies recommended for you:
[2024-08-21T20:45:13.850Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:45:13.850Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:45:13.850Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13869.958 ms) ======
[2024-08-21T20:45:13.850Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-21T20:45:13.850Z] GC before operation: completed in 78.485 ms, heap usage 180.616 MB -> 50.750 MB.
[2024-08-21T20:45:15.739Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:45:17.628Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:45:20.550Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:45:22.439Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:45:23.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:45:25.274Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:45:26.198Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:45:27.116Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:45:27.116Z] 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.
[2024-08-21T20:45:27.116Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:45:27.116Z] Movies recommended for you:
[2024-08-21T20:45:27.116Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:45:27.116Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:45:27.116Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13580.081 ms) ======
[2024-08-21T20:45:27.116Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-21T20:45:28.036Z] GC before operation: completed in 83.399 ms, heap usage 101.402 MB -> 50.983 MB.
[2024-08-21T20:45:29.922Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:45:31.812Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:45:33.702Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:45:35.624Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:45:36.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:45:38.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:45:39.349Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:45:40.269Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:45:41.186Z] 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.
[2024-08-21T20:45:41.186Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:45:41.186Z] Movies recommended for you:
[2024-08-21T20:45:41.186Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:45:41.186Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:45:41.186Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13428.848 ms) ======
[2024-08-21T20:45:41.186Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-21T20:45:41.186Z] GC before operation: completed in 69.932 ms, heap usage 88.478 MB -> 50.722 MB.
[2024-08-21T20:45:43.074Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:45:45.010Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:45:46.896Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:45:48.783Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:45:50.670Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:45:51.616Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:45:52.535Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:45:54.420Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:45:54.420Z] 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.
[2024-08-21T20:45:54.420Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:45:54.420Z] Movies recommended for you:
[2024-08-21T20:45:54.420Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:45:54.420Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:45:54.420Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13276.863 ms) ======
[2024-08-21T20:45:54.420Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-21T20:45:54.420Z] GC before operation: completed in 78.442 ms, heap usage 76.574 MB -> 50.754 MB.
[2024-08-21T20:45:56.478Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:45:58.363Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:46:00.251Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:46:02.138Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:46:04.024Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:46:04.942Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:46:05.860Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:46:07.747Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:46:07.747Z] 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.
[2024-08-21T20:46:07.747Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:46:07.747Z] Movies recommended for you:
[2024-08-21T20:46:07.747Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:46:07.747Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:46:07.747Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13451.630 ms) ======
[2024-08-21T20:46:07.747Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-21T20:46:07.747Z] GC before operation: completed in 71.238 ms, heap usage 88.880 MB -> 50.591 MB.
[2024-08-21T20:46:09.633Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:46:11.520Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:46:14.454Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:46:16.379Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:46:17.297Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:46:19.184Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:46:20.102Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:46:21.020Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:46:21.939Z] 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.
[2024-08-21T20:46:21.939Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:46:21.939Z] Movies recommended for you:
[2024-08-21T20:46:21.939Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:46:21.939Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:46:21.939Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13773.880 ms) ======
[2024-08-21T20:46:21.939Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-21T20:46:21.939Z] GC before operation: completed in 66.145 ms, heap usage 86.471 MB -> 50.673 MB.
[2024-08-21T20:46:23.538Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:46:25.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:46:27.634Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:46:29.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:46:31.418Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:46:32.338Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:46:33.256Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:46:35.143Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:46:35.143Z] 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.
[2024-08-21T20:46:35.143Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:46:35.143Z] Movies recommended for you:
[2024-08-21T20:46:35.143Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:46:35.143Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:46:35.143Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13584.616 ms) ======
[2024-08-21T20:46:35.143Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-21T20:46:35.143Z] GC before operation: completed in 77.226 ms, heap usage 121.800 MB -> 50.965 MB.
[2024-08-21T20:46:37.046Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:46:39.963Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:46:41.850Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:46:43.738Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:46:44.657Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:46:45.576Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:46:47.463Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:46:48.382Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:46:48.382Z] 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.
[2024-08-21T20:46:48.382Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:46:48.382Z] Movies recommended for you:
[2024-08-21T20:46:48.382Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:46:48.382Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:46:48.382Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13358.941 ms) ======
[2024-08-21T20:46:48.382Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-21T20:46:49.301Z] GC before operation: completed in 67.059 ms, heap usage 87.311 MB -> 50.704 MB.
[2024-08-21T20:46:51.189Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:46:53.095Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:46:54.985Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:46:56.874Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:46:57.796Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:46:58.715Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:47:00.603Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:47:01.576Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:47:01.576Z] 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.
[2024-08-21T20:47:01.576Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:47:02.496Z] Movies recommended for you:
[2024-08-21T20:47:02.496Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:47:02.496Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:47:02.496Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13133.304 ms) ======
[2024-08-21T20:47:02.496Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-21T20:47:02.496Z] GC before operation: completed in 84.063 ms, heap usage 340.481 MB -> 54.686 MB.
[2024-08-21T20:47:04.388Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:47:06.276Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:47:08.165Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:47:10.053Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:47:10.976Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:47:12.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:47:13.784Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:47:15.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:47:15.691Z] 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.
[2024-08-21T20:47:15.691Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:47:15.691Z] Movies recommended for you:
[2024-08-21T20:47:15.691Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:47:15.691Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:47:15.691Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13468.670 ms) ======
[2024-08-21T20:47:15.691Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-21T20:47:15.691Z] GC before operation: completed in 71.678 ms, heap usage 759.335 MB -> 60.703 MB.
[2024-08-21T20:47:17.578Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:47:19.466Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:47:22.366Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:47:24.253Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:47:25.170Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:47:26.091Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:47:27.981Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:47:28.899Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:47:28.899Z] 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.
[2024-08-21T20:47:28.899Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:47:28.899Z] Movies recommended for you:
[2024-08-21T20:47:28.899Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:47:28.899Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:47:28.899Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13432.484 ms) ======
[2024-08-21T20:47:28.900Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-21T20:47:28.900Z] GC before operation: completed in 68.544 ms, heap usage 271.672 MB -> 53.451 MB.
[2024-08-21T20:47:30.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:47:33.731Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:47:35.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:47:37.507Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:47:38.427Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:47:39.348Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:47:41.235Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:47:42.159Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:47:42.159Z] 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.
[2024-08-21T20:47:42.159Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:47:42.159Z] Movies recommended for you:
[2024-08-21T20:47:42.159Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:47:42.159Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:47:42.159Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13214.970 ms) ======
[2024-08-21T20:47:42.159Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-21T20:47:42.159Z] GC before operation: completed in 67.498 ms, heap usage 165.028 MB -> 53.174 MB.
[2024-08-21T20:47:45.076Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:47:46.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:47:48.846Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:47:50.735Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:47:52.625Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:47:53.543Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:47:54.460Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:47:56.494Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:47:56.494Z] 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.
[2024-08-21T20:47:56.494Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:47:56.494Z] Movies recommended for you:
[2024-08-21T20:47:56.494Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:47:56.494Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:47:56.494Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13760.362 ms) ======
[2024-08-21T20:47:56.494Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-21T20:47:56.494Z] GC before operation: completed in 72.885 ms, heap usage 605.375 MB -> 56.874 MB.
[2024-08-21T20:47:58.384Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T20:48:00.271Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T20:48:02.159Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T20:48:04.067Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T20:48:04.985Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T20:48:06.873Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T20:48:07.799Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T20:48:08.717Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T20:48:09.638Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-21T20:48:09.638Z] The best model improves the baseline by 14.52%.
[2024-08-21T20:48:09.638Z] Movies recommended for you:
[2024-08-21T20:48:09.638Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T20:48:09.638Z] There is no way to check that no silent failure occurred.
[2024-08-21T20:48:09.638Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13042.422 ms) ======
[2024-08-21T20:48:09.638Z] -----------------------------------
[2024-08-21T20:48:09.638Z] renaissance-movie-lens_0_PASSED
[2024-08-21T20:48:09.638Z] -----------------------------------
[2024-08-21T20:48:09.638Z]
[2024-08-21T20:48:09.638Z] TEST TEARDOWN:
[2024-08-21T20:48:09.638Z] Nothing to be done for teardown.
[2024-08-21T20:48:09.638Z] renaissance-movie-lens_0 Finish Time: Wed Aug 21 20:48:09 2024 Epoch Time (ms): 1724273289393