renaissance-movie-lens_0
[2024-08-07T22:23:30.130Z] Running test renaissance-movie-lens_0 ...
[2024-08-07T22:23:30.130Z] ===============================================
[2024-08-07T22:23:30.130Z] renaissance-movie-lens_0 Start Time: Wed Aug 7 22:23:30 2024 Epoch Time (ms): 1723069410009
[2024-08-07T22:23:30.130Z] variation: NoOptions
[2024-08-07T22:23:30.130Z] JVM_OPTIONS:
[2024-08-07T22:23:30.130Z] { \
[2024-08-07T22:23:30.130Z] echo ""; echo "TEST SETUP:"; \
[2024-08-07T22:23:30.130Z] echo "Nothing to be done for setup."; \
[2024-08-07T22:23:30.130Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230685574216/renaissance-movie-lens_0"; \
[2024-08-07T22:23:30.130Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230685574216/renaissance-movie-lens_0"; \
[2024-08-07T22:23:30.130Z] echo ""; echo "TESTING:"; \
[2024-08-07T22:23:30.130Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230685574216/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-07T22:23:30.130Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230685574216/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-07T22:23:30.130Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-07T22:23:30.130Z] echo "Nothing to be done for teardown."; \
[2024-08-07T22:23:30.130Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230685574216/TestTargetResult";
[2024-08-07T22:23:30.130Z]
[2024-08-07T22:23:30.130Z] TEST SETUP:
[2024-08-07T22:23:30.130Z] Nothing to be done for setup.
[2024-08-07T22:23:30.130Z]
[2024-08-07T22:23:30.130Z] TESTING:
[2024-08-07T22:23:33.076Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-07T22:23:34.988Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-07T22:23:38.106Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-07T22:23:38.106Z] Training: 60056, validation: 20285, test: 19854
[2024-08-07T22:23:38.106Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-07T22:23:38.106Z] GC before operation: completed in 74.106 ms, heap usage 80.094 MB -> 37.280 MB.
[2024-08-07T22:23:43.366Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:23:46.319Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:23:49.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:23:52.240Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:23:53.169Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:23:55.090Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:23:56.019Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:23:57.929Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:23:57.929Z] 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.
[2024-08-07T22:23:57.929Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:23:57.929Z] Movies recommended for you:
[2024-08-07T22:23:57.929Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:23:57.929Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:23:57.929Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (19905.956 ms) ======
[2024-08-07T22:23:57.929Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-07T22:23:57.929Z] GC before operation: completed in 73.141 ms, heap usage 194.174 MB -> 49.856 MB.
[2024-08-07T22:24:00.890Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:24:02.803Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:24:05.751Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:24:08.357Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:24:09.288Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:24:10.216Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:24:12.126Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:24:13.055Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:24:14.012Z] 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.
[2024-08-07T22:24:14.012Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:24:14.012Z] Movies recommended for you:
[2024-08-07T22:24:14.012Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:24:14.012Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:24:14.012Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15404.002 ms) ======
[2024-08-07T22:24:14.012Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-07T22:24:14.012Z] GC before operation: completed in 59.405 ms, heap usage 94.193 MB -> 49.691 MB.
[2024-08-07T22:24:15.923Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:24:17.841Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:24:19.919Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:24:21.833Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:24:23.741Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:24:24.672Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:24:26.581Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:24:27.510Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:24:27.510Z] 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.
[2024-08-07T22:24:27.510Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:24:27.510Z] Movies recommended for you:
[2024-08-07T22:24:27.510Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:24:27.510Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:24:27.510Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14079.310 ms) ======
[2024-08-07T22:24:27.510Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-07T22:24:27.510Z] GC before operation: completed in 63.764 ms, heap usage 116.638 MB -> 50.073 MB.
[2024-08-07T22:24:30.457Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:24:31.386Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:24:34.331Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:24:36.244Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:24:37.231Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:24:38.160Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:24:40.068Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:24:41.001Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:24:41.001Z] 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.
[2024-08-07T22:24:41.001Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:24:41.001Z] Movies recommended for you:
[2024-08-07T22:24:41.001Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:24:41.001Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:24:41.001Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13414.113 ms) ======
[2024-08-07T22:24:41.001Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-07T22:24:41.001Z] GC before operation: completed in 73.005 ms, heap usage 435.456 MB -> 54.125 MB.
[2024-08-07T22:24:42.912Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:24:45.865Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:24:47.775Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:24:49.685Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:24:50.616Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:24:52.523Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:24:53.453Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:24:54.384Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:24:55.315Z] 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.
[2024-08-07T22:24:55.315Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:24:55.315Z] Movies recommended for you:
[2024-08-07T22:24:55.315Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:24:55.315Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:24:55.315Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13772.264 ms) ======
[2024-08-07T22:24:55.315Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-07T22:24:55.315Z] GC before operation: completed in 87.236 ms, heap usage 93.143 MB -> 50.521 MB.
[2024-08-07T22:24:57.225Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:24:59.137Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:25:01.059Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:25:02.970Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:25:03.899Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:25:05.808Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:25:06.737Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:25:07.668Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:25:08.596Z] 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.
[2024-08-07T22:25:08.596Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:25:08.596Z] Movies recommended for you:
[2024-08-07T22:25:08.596Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:25:08.596Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:25:08.596Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13084.600 ms) ======
[2024-08-07T22:25:08.596Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-07T22:25:08.596Z] GC before operation: completed in 106.827 ms, heap usage 122.092 MB -> 50.544 MB.
[2024-08-07T22:25:10.504Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:25:12.418Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:25:14.327Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:25:16.235Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:25:17.165Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:25:19.074Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:25:20.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:25:20.933Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:25:21.863Z] 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.
[2024-08-07T22:25:21.863Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:25:21.863Z] Movies recommended for you:
[2024-08-07T22:25:21.863Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:25:21.863Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:25:21.863Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13206.375 ms) ======
[2024-08-07T22:25:21.863Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-07T22:25:21.863Z] GC before operation: completed in 97.976 ms, heap usage 116.191 MB -> 50.795 MB.
[2024-08-07T22:25:23.772Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:25:25.679Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:25:28.301Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:25:29.268Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:25:31.180Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:25:32.109Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:25:33.037Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:25:33.975Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:25:34.905Z] 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.
[2024-08-07T22:25:34.905Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:25:34.905Z] Movies recommended for you:
[2024-08-07T22:25:34.905Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:25:34.905Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:25:34.905Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12901.073 ms) ======
[2024-08-07T22:25:34.905Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-07T22:25:34.905Z] GC before operation: completed in 79.695 ms, heap usage 89.412 MB -> 50.980 MB.
[2024-08-07T22:25:36.895Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:25:38.802Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:25:40.712Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:25:42.625Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:25:43.554Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:25:44.482Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:25:46.390Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:25:47.323Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:25:47.323Z] 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.
[2024-08-07T22:25:47.323Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:25:47.323Z] Movies recommended for you:
[2024-08-07T22:25:47.323Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:25:47.323Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:25:47.323Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12793.625 ms) ======
[2024-08-07T22:25:47.323Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-07T22:25:47.323Z] GC before operation: completed in 68.943 ms, heap usage 60.556 MB -> 54.395 MB.
[2024-08-07T22:25:49.231Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:25:51.139Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:25:53.049Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:25:54.957Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:25:55.885Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:25:57.802Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:25:58.734Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:25:59.662Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:26:00.591Z] 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.
[2024-08-07T22:26:00.591Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:26:00.591Z] Movies recommended for you:
[2024-08-07T22:26:00.591Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:26:00.591Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:26:00.591Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12640.211 ms) ======
[2024-08-07T22:26:00.591Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-07T22:26:00.591Z] GC before operation: completed in 88.375 ms, heap usage 352.163 MB -> 51.098 MB.
[2024-08-07T22:26:02.498Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:26:04.405Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:26:06.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:26:08.244Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:26:09.175Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:26:10.104Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:26:12.012Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:26:12.943Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:26:12.943Z] 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.
[2024-08-07T22:26:12.943Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:26:12.943Z] Movies recommended for you:
[2024-08-07T22:26:12.943Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:26:12.943Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:26:12.943Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12807.415 ms) ======
[2024-08-07T22:26:12.943Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-07T22:26:12.943Z] GC before operation: completed in 83.772 ms, heap usage 90.112 MB -> 50.485 MB.
[2024-08-07T22:26:14.849Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:26:16.759Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:26:18.666Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:26:20.575Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:26:21.506Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:26:23.446Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:26:24.375Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:26:25.304Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:26:25.304Z] 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.
[2024-08-07T22:26:26.232Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:26:26.232Z] Movies recommended for you:
[2024-08-07T22:26:26.232Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:26:26.232Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:26:26.232Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12662.441 ms) ======
[2024-08-07T22:26:26.232Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-07T22:26:26.232Z] GC before operation: completed in 82.957 ms, heap usage 88.922 MB -> 50.687 MB.
[2024-08-07T22:26:28.143Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:26:30.054Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:26:31.964Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:26:33.900Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:26:34.830Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:26:35.766Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:26:37.706Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:26:39.327Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:26:39.327Z] 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.
[2024-08-07T22:26:39.327Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:26:39.327Z] Movies recommended for you:
[2024-08-07T22:26:39.327Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:26:39.327Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:26:39.327Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13138.947 ms) ======
[2024-08-07T22:26:39.327Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-07T22:26:39.327Z] GC before operation: completed in 70.218 ms, heap usage 302.181 MB -> 51.093 MB.
[2024-08-07T22:26:40.595Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:26:42.574Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:26:45.528Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:26:46.458Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:26:48.418Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:26:49.355Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:26:50.287Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:26:52.199Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:26:52.199Z] 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.
[2024-08-07T22:26:52.199Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:26:52.199Z] Movies recommended for you:
[2024-08-07T22:26:52.199Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:26:52.199Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:26:52.199Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12889.826 ms) ======
[2024-08-07T22:26:52.199Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-07T22:26:52.199Z] GC before operation: completed in 67.379 ms, heap usage 157.230 MB -> 50.735 MB.
[2024-08-07T22:26:54.146Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:26:56.055Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:26:57.972Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:26:59.890Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:27:00.822Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:27:01.752Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:27:03.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:27:04.606Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:27:04.606Z] 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.
[2024-08-07T22:27:04.606Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:27:04.606Z] Movies recommended for you:
[2024-08-07T22:27:04.606Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:27:04.606Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:27:04.606Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12745.830 ms) ======
[2024-08-07T22:27:04.606Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-07T22:27:04.606Z] GC before operation: completed in 86.596 ms, heap usage 87.520 MB -> 50.762 MB.
[2024-08-07T22:27:06.519Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:27:08.435Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:27:10.348Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:27:12.270Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:27:13.201Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:27:15.113Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:27:16.044Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:27:16.975Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:27:16.976Z] 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.
[2024-08-07T22:27:16.976Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:27:17.908Z] Movies recommended for you:
[2024-08-07T22:27:17.908Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:27:17.908Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:27:17.908Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12537.999 ms) ======
[2024-08-07T22:27:17.908Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-07T22:27:17.908Z] GC before operation: completed in 80.187 ms, heap usage 87.499 MB -> 50.942 MB.
[2024-08-07T22:27:19.819Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:27:21.842Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:27:22.822Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:27:24.736Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:27:26.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:27:27.576Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:27:28.504Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:27:29.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:27:30.371Z] 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.
[2024-08-07T22:27:30.371Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:27:30.371Z] Movies recommended for you:
[2024-08-07T22:27:30.372Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:27:30.372Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:27:30.372Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12580.854 ms) ======
[2024-08-07T22:27:30.372Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-07T22:27:30.372Z] GC before operation: completed in 75.928 ms, heap usage 89.107 MB -> 50.812 MB.
[2024-08-07T22:27:32.284Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:27:34.200Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:27:36.108Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:27:38.045Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:27:38.975Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:27:39.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:27:41.821Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:27:42.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:27:42.752Z] 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.
[2024-08-07T22:27:42.752Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:27:42.752Z] Movies recommended for you:
[2024-08-07T22:27:42.752Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:27:42.752Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:27:42.752Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12664.565 ms) ======
[2024-08-07T22:27:42.752Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-07T22:27:42.752Z] GC before operation: completed in 78.308 ms, heap usage 442.106 MB -> 54.386 MB.
[2024-08-07T22:27:44.661Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:27:46.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:27:48.487Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:27:50.946Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:27:51.878Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:27:52.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:27:53.742Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:27:54.673Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:27:55.605Z] 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.
[2024-08-07T22:27:55.605Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:27:55.605Z] Movies recommended for you:
[2024-08-07T22:27:55.605Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:27:55.605Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:27:55.605Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12483.764 ms) ======
[2024-08-07T22:27:55.605Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-07T22:27:55.605Z] GC before operation: completed in 86.915 ms, heap usage 370.144 MB -> 51.256 MB.
[2024-08-07T22:27:57.522Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T22:27:59.441Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T22:28:01.356Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T22:28:03.267Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T22:28:04.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T22:28:05.131Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T22:28:07.046Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T22:28:07.978Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T22:28:07.978Z] 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.
[2024-08-07T22:28:07.978Z] The best model improves the baseline by 14.52%.
[2024-08-07T22:28:07.978Z] Movies recommended for you:
[2024-08-07T22:28:07.978Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T22:28:07.978Z] There is no way to check that no silent failure occurred.
[2024-08-07T22:28:07.978Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12620.699 ms) ======
[2024-08-07T22:28:08.910Z] -----------------------------------
[2024-08-07T22:28:08.910Z] renaissance-movie-lens_0_PASSED
[2024-08-07T22:28:08.910Z] -----------------------------------
[2024-08-07T22:28:08.910Z]
[2024-08-07T22:28:08.910Z] TEST TEARDOWN:
[2024-08-07T22:28:08.910Z] Nothing to be done for teardown.
[2024-08-07T22:28:08.910Z] renaissance-movie-lens_0 Finish Time: Wed Aug 7 22:28:08 2024 Epoch Time (ms): 1723069688193