renaissance-movie-lens_0
[2024-08-28T21:41:42.817Z] Running test renaissance-movie-lens_0 ...
[2024-08-28T21:41:42.817Z] ===============================================
[2024-08-28T21:41:42.817Z] renaissance-movie-lens_0 Start Time: Wed Aug 28 21:41:42 2024 Epoch Time (ms): 1724881302547
[2024-08-28T21:41:42.817Z] variation: NoOptions
[2024-08-28T21:41:42.817Z] JVM_OPTIONS:
[2024-08-28T21:41:42.817Z] { \
[2024-08-28T21:41:42.817Z] echo ""; echo "TEST SETUP:"; \
[2024-08-28T21:41:42.817Z] echo "Nothing to be done for setup."; \
[2024-08-28T21:41:42.817Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17248787458810/renaissance-movie-lens_0"; \
[2024-08-28T21:41:42.817Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17248787458810/renaissance-movie-lens_0"; \
[2024-08-28T21:41:42.817Z] echo ""; echo "TESTING:"; \
[2024-08-28T21:41:42.817Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-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_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17248787458810/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-28T21:41:42.817Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17248787458810/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-28T21:41:42.817Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-28T21:41:42.817Z] echo "Nothing to be done for teardown."; \
[2024-08-28T21:41:42.817Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17248787458810/TestTargetResult";
[2024-08-28T21:41:42.817Z]
[2024-08-28T21:41:42.817Z] TEST SETUP:
[2024-08-28T21:41:42.817Z] Nothing to be done for setup.
[2024-08-28T21:41:42.817Z]
[2024-08-28T21:41:42.817Z] TESTING:
[2024-08-28T21:41:48.539Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-28T21:41:55.552Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-28T21:42:08.193Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-28T21:42:09.020Z] Training: 60056, validation: 20285, test: 19854
[2024-08-28T21:42:09.020Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-28T21:42:09.020Z] GC before operation: completed in 195.906 ms, heap usage 67.594 MB -> 37.128 MB.
[2024-08-28T21:42:35.368Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:42:49.548Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:43:06.068Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:43:16.243Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:43:23.424Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:43:30.728Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:43:36.548Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:43:43.653Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:43:43.653Z] 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.
[2024-08-28T21:43:44.477Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:43:44.477Z] Movies recommended for you:
[2024-08-28T21:43:44.477Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:43:44.477Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:43:44.477Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (95748.962 ms) ======
[2024-08-28T21:43:44.477Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-28T21:43:45.280Z] GC before operation: completed in 396.283 ms, heap usage 270.192 MB -> 54.985 MB.
[2024-08-28T21:43:57.261Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:44:04.400Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:44:14.686Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:44:23.186Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:44:27.823Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:44:33.666Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:44:38.850Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:44:43.476Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:44:44.288Z] 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.
[2024-08-28T21:44:45.092Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:44:45.092Z] Movies recommended for you:
[2024-08-28T21:44:45.092Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:44:45.092Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:44:45.092Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (60026.681 ms) ======
[2024-08-28T21:44:45.092Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-28T21:44:45.092Z] GC before operation: completed in 191.584 ms, heap usage 106.344 MB -> 51.370 MB.
[2024-08-28T21:44:53.630Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:45:02.229Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:45:09.336Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:45:17.880Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:45:23.800Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:45:28.416Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:45:34.204Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:45:39.972Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:45:40.778Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-28T21:45:40.778Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:45:40.778Z] Movies recommended for you:
[2024-08-28T21:45:40.778Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:45:40.778Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:45:40.778Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (55886.998 ms) ======
[2024-08-28T21:45:40.778Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-28T21:45:41.583Z] GC before operation: completed in 327.623 ms, heap usage 224.732 MB -> 49.926 MB.
[2024-08-28T21:45:52.360Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:46:00.968Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:46:11.130Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:46:19.659Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:46:25.454Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:46:31.290Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:46:35.924Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:46:41.725Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:46:41.725Z] 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.
[2024-08-28T21:46:41.725Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:46:42.528Z] Movies recommended for you:
[2024-08-28T21:46:42.528Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:46:42.528Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:46:42.528Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60876.122 ms) ======
[2024-08-28T21:46:42.528Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-28T21:46:42.528Z] GC before operation: completed in 220.490 ms, heap usage 412.725 MB -> 53.616 MB.
[2024-08-28T21:46:49.553Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:46:59.725Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:47:08.796Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:47:17.327Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:47:25.934Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:47:31.755Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:47:37.532Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:47:42.166Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:47:43.808Z] 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.
[2024-08-28T21:47:43.808Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:47:43.808Z] Movies recommended for you:
[2024-08-28T21:47:43.808Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:47:43.808Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:47:43.808Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (61404.317 ms) ======
[2024-08-28T21:47:43.808Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-28T21:47:44.624Z] GC before operation: completed in 358.614 ms, heap usage 393.320 MB -> 53.774 MB.
[2024-08-28T21:47:56.698Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:48:05.396Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:48:20.260Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:48:30.626Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:48:37.672Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:48:46.201Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:48:54.707Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:49:01.857Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:49:03.527Z] 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.
[2024-08-28T21:49:03.527Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:49:04.331Z] Movies recommended for you:
[2024-08-28T21:49:04.331Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:49:04.331Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:49:04.331Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (79654.649 ms) ======
[2024-08-28T21:49:04.331Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-28T21:49:04.331Z] GC before operation: completed in 453.038 ms, heap usage 287.158 MB -> 50.408 MB.
[2024-08-28T21:49:16.502Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:49:28.605Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:49:45.392Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:49:59.734Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:50:10.185Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:50:20.565Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:50:29.393Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:50:38.124Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:50:38.933Z] 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.
[2024-08-28T21:50:38.933Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:50:38.934Z] Movies recommended for you:
[2024-08-28T21:50:38.934Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:50:38.934Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:50:38.934Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (94779.990 ms) ======
[2024-08-28T21:50:38.934Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-28T21:50:39.776Z] GC before operation: completed in 309.215 ms, heap usage 405.688 MB -> 53.878 MB.
[2024-08-28T21:50:52.714Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:51:09.608Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:51:24.025Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:51:38.513Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:51:44.509Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:51:53.189Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:51:59.122Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:52:07.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:52:09.646Z] 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.
[2024-08-28T21:52:09.646Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:52:09.646Z] Movies recommended for you:
[2024-08-28T21:52:09.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:52:09.646Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:52:09.646Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (90469.036 ms) ======
[2024-08-28T21:52:09.646Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-28T21:52:10.468Z] GC before operation: completed in 381.566 ms, heap usage 245.621 MB -> 50.841 MB.
[2024-08-28T21:52:23.414Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:52:37.906Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:52:52.388Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:53:02.866Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:53:10.185Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:53:17.501Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:53:26.277Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:53:35.742Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:53:37.464Z] 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.
[2024-08-28T21:53:37.464Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:53:37.464Z] Movies recommended for you:
[2024-08-28T21:53:37.464Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:53:37.464Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:53:37.464Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (87386.100 ms) ======
[2024-08-28T21:53:37.464Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-28T21:53:38.317Z] GC before operation: completed in 394.617 ms, heap usage 313.492 MB -> 50.747 MB.
[2024-08-28T21:53:52.813Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:54:09.759Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:54:24.527Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:54:39.077Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:54:46.387Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:54:54.290Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:55:03.147Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:55:11.953Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:55:13.681Z] 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.
[2024-08-28T21:55:13.681Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:55:14.499Z] Movies recommended for you:
[2024-08-28T21:55:14.499Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:55:14.499Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:55:14.499Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (96269.058 ms) ======
[2024-08-28T21:55:14.499Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-28T21:55:14.499Z] GC before operation: completed in 455.829 ms, heap usage 183.933 MB -> 50.705 MB.
[2024-08-28T21:55:28.982Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:55:41.196Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:55:55.511Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:56:07.669Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:56:17.005Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:56:24.341Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:56:34.846Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:56:45.156Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:56:45.981Z] 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.
[2024-08-28T21:56:45.981Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:56:46.797Z] Movies recommended for you:
[2024-08-28T21:56:46.797Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:56:46.797Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:56:46.797Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (91575.269 ms) ======
[2024-08-28T21:56:46.797Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-28T21:56:46.797Z] GC before operation: completed in 414.975 ms, heap usage 405.324 MB -> 53.923 MB.
[2024-08-28T21:57:03.489Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:57:17.793Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:57:34.486Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:57:48.841Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:57:59.177Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:58:08.008Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:58:15.251Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:58:24.101Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:58:24.925Z] 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.
[2024-08-28T21:58:24.925Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:58:25.745Z] Movies recommended for you:
[2024-08-28T21:58:25.745Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:58:25.745Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:58:25.745Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (98836.348 ms) ======
[2024-08-28T21:58:25.745Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-28T21:58:25.745Z] GC before operation: completed in 410.721 ms, heap usage 242.411 MB -> 50.690 MB.
[2024-08-28T21:58:40.217Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:58:54.945Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:59:09.350Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:59:25.969Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:59:34.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:59:41.697Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:59:50.158Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:59:58.609Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:59:59.387Z] 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.
[2024-08-28T21:59:59.387Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:00:00.207Z] Movies recommended for you:
[2024-08-28T22:00:00.207Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:00:00.207Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:00:00.207Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (94159.435 ms) ======
[2024-08-28T22:00:00.207Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-28T22:00:00.997Z] GC before operation: completed in 398.597 ms, heap usage 178.091 MB -> 50.809 MB.
[2024-08-28T22:00:12.977Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T22:00:26.985Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T22:00:43.445Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T22:00:55.361Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T22:01:03.849Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T22:01:12.342Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T22:01:18.092Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T22:01:25.101Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T22:01:25.940Z] 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.
[2024-08-28T22:01:25.940Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:01:25.940Z] Movies recommended for you:
[2024-08-28T22:01:25.940Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:01:25.940Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:01:25.940Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (85503.185 ms) ======
[2024-08-28T22:01:25.940Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-28T22:01:26.752Z] GC before operation: completed in 411.172 ms, heap usage 405.519 MB -> 53.958 MB.
[2024-08-28T22:01:37.168Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T22:01:51.275Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T22:02:03.134Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T22:02:15.021Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T22:02:21.992Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T22:02:27.733Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T22:02:36.184Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T22:02:43.845Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T22:02:45.501Z] 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.
[2024-08-28T22:02:45.501Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:02:46.297Z] Movies recommended for you:
[2024-08-28T22:02:46.297Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:02:46.297Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:02:46.297Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (79485.104 ms) ======
[2024-08-28T22:02:46.297Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-28T22:02:46.297Z] GC before operation: completed in 449.528 ms, heap usage 244.091 MB -> 50.783 MB.
[2024-08-28T22:03:00.254Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T22:03:12.141Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T22:03:26.198Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T22:03:38.220Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T22:03:45.240Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T22:03:52.263Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T22:04:01.341Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T22:04:08.368Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T22:04:10.045Z] 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.
[2024-08-28T22:04:10.045Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:04:10.854Z] Movies recommended for you:
[2024-08-28T22:04:10.854Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:04:10.854Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:04:10.854Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (83973.812 ms) ======
[2024-08-28T22:04:10.854Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-28T22:04:10.854Z] GC before operation: completed in 446.239 ms, heap usage 191.492 MB -> 50.814 MB.
[2024-08-28T22:04:27.340Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T22:04:41.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T22:04:55.632Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T22:05:05.752Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T22:05:12.882Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T22:05:21.997Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T22:05:30.556Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T22:05:39.374Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T22:05:40.197Z] 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.
[2024-08-28T22:05:41.022Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:05:41.022Z] Movies recommended for you:
[2024-08-28T22:05:41.022Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:05:41.022Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:05:41.022Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (90160.720 ms) ======
[2024-08-28T22:05:41.022Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-28T22:05:41.841Z] GC before operation: completed in 489.385 ms, heap usage 395.653 MB -> 54.030 MB.
[2024-08-28T22:05:54.057Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T22:06:10.834Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T22:06:27.618Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T22:06:42.581Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T22:06:51.291Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T22:06:58.631Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T22:07:09.067Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T22:07:16.274Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T22:07:18.017Z] 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.
[2024-08-28T22:07:18.017Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:07:18.017Z] Movies recommended for you:
[2024-08-28T22:07:18.017Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:07:18.017Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:07:18.017Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (96740.041 ms) ======
[2024-08-28T22:07:18.017Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-28T22:07:18.850Z] GC before operation: completed in 624.342 ms, heap usage 241.131 MB -> 49.137 MB.
[2024-08-28T22:07:33.308Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T22:07:43.697Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T22:07:58.930Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T22:08:11.310Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T22:08:20.172Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T22:08:27.466Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T22:08:36.280Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T22:08:42.250Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T22:08:44.026Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-28T22:08:44.026Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:08:44.026Z] Movies recommended for you:
[2024-08-28T22:08:44.026Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:08:44.026Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:08:44.026Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (85250.509 ms) ======
[2024-08-28T22:08:44.026Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-28T22:08:44.844Z] GC before operation: completed in 382.350 ms, heap usage 410.257 MB -> 52.605 MB.
[2024-08-28T22:08:59.286Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T22:09:11.550Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T22:09:26.765Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T22:09:39.193Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T22:09:47.846Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T22:09:54.958Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T22:10:02.112Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T22:10:10.686Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T22:10:12.353Z] 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.
[2024-08-28T22:10:12.353Z] The best model improves the baseline by 14.52%.
[2024-08-28T22:10:12.353Z] Movies recommended for you:
[2024-08-28T22:10:12.353Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T22:10:12.353Z] There is no way to check that no silent failure occurred.
[2024-08-28T22:10:12.353Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (87988.934 ms) ======
[2024-08-28T22:10:15.893Z] -----------------------------------
[2024-08-28T22:10:15.893Z] renaissance-movie-lens_0_PASSED
[2024-08-28T22:10:15.893Z] -----------------------------------
[2024-08-28T22:10:15.893Z]
[2024-08-28T22:10:15.893Z] TEST TEARDOWN:
[2024-08-28T22:10:15.893Z] Nothing to be done for teardown.
[2024-08-28T22:10:15.893Z] renaissance-movie-lens_0 Finish Time: Wed Aug 28 22:10:15 2024 Epoch Time (ms): 1724883015102