renaissance-movie-lens_0
[2024-11-20T23:59:27.368Z] Running test renaissance-movie-lens_0 ...
[2024-11-20T23:59:27.368Z] ===============================================
[2024-11-20T23:59:27.368Z] renaissance-movie-lens_0 Start Time: Wed Nov 20 23:59:27 2024 Epoch Time (ms): 1732147167207
[2024-11-20T23:59:27.368Z] variation: NoOptions
[2024-11-20T23:59:27.368Z] JVM_OPTIONS:
[2024-11-20T23:59:27.368Z] { \
[2024-11-20T23:59:27.368Z] echo ""; echo "TEST SETUP:"; \
[2024-11-20T23:59:27.368Z] echo "Nothing to be done for setup."; \
[2024-11-20T23:59:27.368Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_173214619237/renaissance-movie-lens_0"; \
[2024-11-20T23:59:27.368Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_173214619237/renaissance-movie-lens_0"; \
[2024-11-20T23:59:27.368Z] echo ""; echo "TESTING:"; \
[2024-11-20T23:59:27.368Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_173214619237/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-20T23:59:27.368Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_173214619237/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-20T23:59:27.368Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-20T23:59:27.368Z] echo "Nothing to be done for teardown."; \
[2024-11-20T23:59:27.368Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_173214619237/TestTargetResult";
[2024-11-20T23:59:27.368Z]
[2024-11-20T23:59:27.368Z] TEST SETUP:
[2024-11-20T23:59:27.368Z] Nothing to be done for setup.
[2024-11-20T23:59:27.368Z]
[2024-11-20T23:59:27.368Z] TESTING:
[2024-11-20T23:59:31.581Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-20T23:59:33.565Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-20T23:59:36.632Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-20T23:59:36.632Z] Training: 60056, validation: 20285, test: 19854
[2024-11-20T23:59:36.632Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-20T23:59:36.632Z] GC before operation: completed in 69.613 ms, heap usage 81.324 MB -> 36.478 MB.
[2024-11-20T23:59:43.244Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T23:59:46.337Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T23:59:49.402Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T23:59:52.464Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T23:59:54.451Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T23:59:56.436Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T23:59:58.424Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T23:59:59.391Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T23:59:59.391Z] 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.
[2024-11-21T00:00:00.356Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:00:00.356Z] Movies recommended for you:
[2024-11-21T00:00:00.356Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:00:00.356Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:00:00.356Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22956.263 ms) ======
[2024-11-21T00:00:00.356Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-21T00:00:00.356Z] GC before operation: completed in 80.334 ms, heap usage 179.162 MB -> 48.173 MB.
[2024-11-21T00:00:02.358Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:00:05.417Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:00:07.401Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:00:10.463Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:00:11.431Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:00:13.437Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:00:15.440Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:00:16.408Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:00:16.408Z] 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.
[2024-11-21T00:00:16.408Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:00:17.372Z] Movies recommended for you:
[2024-11-21T00:00:17.372Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:00:17.372Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:00:17.372Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16861.285 ms) ======
[2024-11-21T00:00:17.372Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-21T00:00:17.372Z] GC before operation: completed in 99.923 ms, heap usage 70.171 MB -> 48.916 MB.
[2024-11-21T00:00:19.354Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:00:22.414Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:00:24.393Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:00:26.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:00:28.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:00:30.346Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:00:31.311Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:00:32.285Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:00:33.252Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-21T00:00:33.252Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:00:33.252Z] Movies recommended for you:
[2024-11-21T00:00:33.252Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:00:33.252Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:00:33.252Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16083.095 ms) ======
[2024-11-21T00:00:33.252Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-21T00:00:33.252Z] GC before operation: completed in 92.745 ms, heap usage 316.191 MB -> 49.446 MB.
[2024-11-21T00:00:36.306Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:00:38.290Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:00:40.271Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:00:43.250Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:00:44.238Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:00:46.221Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:00:47.187Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:00:49.235Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:00:49.235Z] 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.
[2024-11-21T00:00:49.235Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:00:49.235Z] Movies recommended for you:
[2024-11-21T00:00:49.235Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:00:49.235Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:00:49.235Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16044.266 ms) ======
[2024-11-21T00:00:49.235Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-21T00:00:49.235Z] GC before operation: completed in 90.793 ms, heap usage 325.018 MB -> 49.821 MB.
[2024-11-21T00:00:52.293Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:00:54.275Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:00:57.342Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:00:59.326Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:01:00.292Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:01:02.279Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:01:03.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:01:05.229Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:01:05.229Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-21T00:01:05.229Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:01:05.229Z] Movies recommended for you:
[2024-11-21T00:01:05.229Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:01:05.229Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:01:05.229Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15761.048 ms) ======
[2024-11-21T00:01:05.229Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-21T00:01:05.229Z] GC before operation: completed in 84.385 ms, heap usage 187.690 MB -> 49.852 MB.
[2024-11-21T00:01:07.220Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:01:09.203Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:01:11.193Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:01:13.180Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:01:15.168Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:01:16.134Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:01:18.116Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:01:19.083Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:01:19.083Z] 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.
[2024-11-21T00:01:19.083Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:01:19.083Z] Movies recommended for you:
[2024-11-21T00:01:19.083Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:01:19.083Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:01:19.083Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14251.549 ms) ======
[2024-11-21T00:01:19.083Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-21T00:01:20.050Z] GC before operation: completed in 98.225 ms, heap usage 247.825 MB -> 49.879 MB.
[2024-11-21T00:01:22.036Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:01:24.024Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:01:26.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:01:28.003Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:01:29.988Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:01:30.955Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:01:32.937Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:01:33.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:01:33.904Z] 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.
[2024-11-21T00:01:34.871Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:01:34.871Z] Movies recommended for you:
[2024-11-21T00:01:34.871Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:01:34.871Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:01:34.871Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14901.651 ms) ======
[2024-11-21T00:01:34.871Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-21T00:01:34.871Z] GC before operation: completed in 91.123 ms, heap usage 266.279 MB -> 50.003 MB.
[2024-11-21T00:01:36.854Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:01:38.842Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:01:40.935Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:01:42.928Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:01:44.961Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:01:45.928Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:01:46.896Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:01:48.887Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:01:48.887Z] 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.
[2024-11-21T00:01:48.887Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:01:48.887Z] Movies recommended for you:
[2024-11-21T00:01:48.887Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:01:48.887Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:01:48.887Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14167.755 ms) ======
[2024-11-21T00:01:48.887Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-21T00:01:48.887Z] GC before operation: completed in 88.164 ms, heap usage 249.589 MB -> 50.304 MB.
[2024-11-21T00:01:50.871Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:01:52.858Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:01:55.915Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:01:56.880Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:01:58.864Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:01:59.829Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:02:00.795Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:02:02.776Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:02:02.776Z] 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.
[2024-11-21T00:02:02.776Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:02:02.776Z] Movies recommended for you:
[2024-11-21T00:02:02.776Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:02:02.776Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:02:02.776Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14084.264 ms) ======
[2024-11-21T00:02:02.776Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-21T00:02:02.776Z] GC before operation: completed in 82.520 ms, heap usage 175.379 MB -> 50.024 MB.
[2024-11-21T00:02:05.832Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:02:07.813Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:02:09.796Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:02:11.797Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:02:12.762Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:02:14.743Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:02:15.710Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:02:16.678Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:02:17.645Z] 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.
[2024-11-21T00:02:17.645Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:02:17.645Z] Movies recommended for you:
[2024-11-21T00:02:17.645Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:02:17.645Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:02:17.645Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14375.958 ms) ======
[2024-11-21T00:02:17.645Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-21T00:02:17.645Z] GC before operation: completed in 87.775 ms, heap usage 266.956 MB -> 50.229 MB.
[2024-11-21T00:02:19.628Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:02:21.611Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:02:24.672Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:02:26.656Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:02:27.647Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:02:28.613Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:02:30.598Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:02:31.565Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:02:31.565Z] 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.
[2024-11-21T00:02:31.565Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:02:31.565Z] Movies recommended for you:
[2024-11-21T00:02:31.565Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:02:31.565Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:02:31.565Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14336.615 ms) ======
[2024-11-21T00:02:31.565Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-21T00:02:31.565Z] GC before operation: completed in 79.427 ms, heap usage 187.057 MB -> 49.858 MB.
[2024-11-21T00:02:34.629Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:02:36.616Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:02:38.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:02:40.729Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:02:41.696Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:02:42.664Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:02:43.630Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:02:46.366Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:02:46.366Z] 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.
[2024-11-21T00:02:46.366Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:02:46.366Z] Movies recommended for you:
[2024-11-21T00:02:46.366Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:02:46.366Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:02:46.367Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13873.971 ms) ======
[2024-11-21T00:02:46.367Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-21T00:02:46.367Z] GC before operation: completed in 83.690 ms, heap usage 240.243 MB -> 50.130 MB.
[2024-11-21T00:02:48.347Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:02:50.332Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:02:52.317Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:02:54.317Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:02:55.457Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:02:57.442Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:02:58.406Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:02:59.372Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:03:00.337Z] 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.
[2024-11-21T00:03:00.337Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:03:00.337Z] Movies recommended for you:
[2024-11-21T00:03:00.337Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:03:00.337Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:03:00.337Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14237.815 ms) ======
[2024-11-21T00:03:00.337Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-21T00:03:00.337Z] GC before operation: completed in 83.664 ms, heap usage 141.611 MB -> 50.201 MB.
[2024-11-21T00:03:02.320Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:03:04.301Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:03:06.289Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:03:08.275Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:03:10.257Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:03:11.225Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:03:12.194Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:03:13.161Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:03:14.128Z] 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.
[2024-11-21T00:03:14.128Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:03:14.128Z] Movies recommended for you:
[2024-11-21T00:03:14.128Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:03:14.128Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:03:14.128Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13800.415 ms) ======
[2024-11-21T00:03:14.128Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-21T00:03:14.128Z] GC before operation: completed in 81.261 ms, heap usage 105.329 MB -> 49.877 MB.
[2024-11-21T00:03:16.111Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:03:18.276Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:03:20.261Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:03:22.247Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:03:24.231Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:03:25.196Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:03:26.166Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:03:28.151Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:03:28.151Z] 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.
[2024-11-21T00:03:28.151Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:03:28.151Z] Movies recommended for you:
[2024-11-21T00:03:28.151Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:03:28.152Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:03:28.152Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14182.892 ms) ======
[2024-11-21T00:03:28.152Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-21T00:03:28.152Z] GC before operation: completed in 84.171 ms, heap usage 170.980 MB -> 50.175 MB.
[2024-11-21T00:03:30.138Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:03:33.198Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:03:35.180Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:03:37.165Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:03:38.141Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:03:39.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:03:41.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:03:42.183Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:03:42.183Z] 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.
[2024-11-21T00:03:42.183Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:03:42.183Z] Movies recommended for you:
[2024-11-21T00:03:42.183Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:03:42.183Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:03:42.183Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14008.151 ms) ======
[2024-11-21T00:03:42.183Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-21T00:03:42.183Z] GC before operation: completed in 81.469 ms, heap usage 196.629 MB -> 50.205 MB.
[2024-11-21T00:03:45.262Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:03:47.246Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:03:49.235Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:03:51.229Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:03:53.212Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:03:54.183Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:03:55.162Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:03:57.149Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:03:57.149Z] 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.
[2024-11-21T00:03:57.149Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:03:57.149Z] Movies recommended for you:
[2024-11-21T00:03:57.149Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:03:57.149Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:03:57.149Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14816.907 ms) ======
[2024-11-21T00:03:57.149Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-21T00:03:57.149Z] GC before operation: completed in 91.939 ms, heap usage 263.066 MB -> 50.149 MB.
[2024-11-21T00:03:59.135Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:04:02.207Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:04:04.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:04:06.187Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:04:07.152Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:04:08.119Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:04:10.101Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:04:11.068Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:04:11.068Z] 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.
[2024-11-21T00:04:11.068Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:04:11.068Z] Movies recommended for you:
[2024-11-21T00:04:11.068Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:04:11.068Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:04:11.068Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13995.164 ms) ======
[2024-11-21T00:04:11.068Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-21T00:04:11.068Z] GC before operation: completed in 84.467 ms, heap usage 345.316 MB -> 50.252 MB.
[2024-11-21T00:04:13.056Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:04:15.040Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:04:18.142Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:04:20.141Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:04:21.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:04:22.080Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:04:24.067Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:04:25.040Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:04:25.040Z] 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.
[2024-11-21T00:04:25.040Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:04:25.040Z] Movies recommended for you:
[2024-11-21T00:04:25.040Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:04:25.040Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:04:25.040Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13923.847 ms) ======
[2024-11-21T00:04:25.040Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-21T00:04:25.040Z] GC before operation: completed in 89.191 ms, heap usage 59.178 MB -> 50.163 MB.
[2024-11-21T00:04:28.106Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T00:04:30.092Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T00:04:32.078Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T00:04:34.063Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T00:04:35.031Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T00:04:35.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T00:04:37.985Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T00:04:38.952Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T00:04:38.953Z] 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.
[2024-11-21T00:04:38.953Z] The best model improves the baseline by 14.52%.
[2024-11-21T00:04:38.953Z] Movies recommended for you:
[2024-11-21T00:04:38.953Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T00:04:38.953Z] There is no way to check that no silent failure occurred.
[2024-11-21T00:04:38.953Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14013.871 ms) ======
[2024-11-21T00:04:39.919Z] -----------------------------------
[2024-11-21T00:04:39.919Z] renaissance-movie-lens_0_PASSED
[2024-11-21T00:04:39.919Z] -----------------------------------
[2024-11-21T00:04:39.919Z]
[2024-11-21T00:04:39.919Z] TEST TEARDOWN:
[2024-11-21T00:04:39.919Z] Nothing to be done for teardown.
[2024-11-21T00:04:39.919Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 00:04:39 2024 Epoch Time (ms): 1732147479355