renaissance-movie-lens_0
[2024-08-21T21:23:14.706Z] Running test renaissance-movie-lens_0 ...
[2024-08-21T21:23:14.706Z] ===============================================
[2024-08-21T21:23:14.706Z] renaissance-movie-lens_0 Start Time: Wed Aug 21 21:23:14 2024 Epoch Time (ms): 1724275394047
[2024-08-21T21:23:14.706Z] variation: NoOptions
[2024-08-21T21:23:14.706Z] JVM_OPTIONS:
[2024-08-21T21:23:14.706Z] { \
[2024-08-21T21:23:14.707Z] echo ""; echo "TEST SETUP:"; \
[2024-08-21T21:23:14.707Z] echo "Nothing to be done for setup."; \
[2024-08-21T21:23:14.707Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242744846193/renaissance-movie-lens_0"; \
[2024-08-21T21:23:14.707Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242744846193/renaissance-movie-lens_0"; \
[2024-08-21T21:23:14.707Z] echo ""; echo "TESTING:"; \
[2024-08-21T21:23:14.707Z] "/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_17242744846193/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-21T21:23:14.707Z] 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_17242744846193/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-21T21:23:14.707Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-21T21:23:14.707Z] echo "Nothing to be done for teardown."; \
[2024-08-21T21:23:14.707Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17242744846193/TestTargetResult";
[2024-08-21T21:23:14.707Z]
[2024-08-21T21:23:14.707Z] TEST SETUP:
[2024-08-21T21:23:14.707Z] Nothing to be done for setup.
[2024-08-21T21:23:14.707Z]
[2024-08-21T21:23:14.707Z] TESTING:
[2024-08-21T21:23:17.628Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-21T21:23:20.554Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-21T21:23:23.473Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-21T21:23:23.473Z] Training: 60056, validation: 20285, test: 19854
[2024-08-21T21:23:23.473Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-21T21:23:23.473Z] GC before operation: completed in 79.716 ms, heap usage 98.837 MB -> 36.438 MB.
[2024-08-21T21:23:29.981Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:23:34.014Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:23:36.935Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:23:39.860Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:23:41.833Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:23:43.724Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:23:45.623Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:23:47.513Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:23:47.513Z] 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.
[2024-08-21T21:23:47.513Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:23:47.513Z] Movies recommended for you:
[2024-08-21T21:23:47.513Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:23:47.513Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:23:47.513Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23919.807 ms) ======
[2024-08-21T21:23:47.513Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-21T21:23:47.513Z] GC before operation: completed in 103.977 ms, heap usage 189.524 MB -> 48.171 MB.
[2024-08-21T21:23:50.436Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:23:53.360Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:23:56.325Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:23:59.235Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:24:00.314Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:24:01.237Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:24:03.131Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:24:05.029Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:24:05.029Z] 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.
[2024-08-21T21:24:05.029Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:24:05.029Z] Movies recommended for you:
[2024-08-21T21:24:05.029Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:24:05.029Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:24:05.029Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17676.147 ms) ======
[2024-08-21T21:24:05.029Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-21T21:24:05.950Z] GC before operation: completed in 104.160 ms, heap usage 203.779 MB -> 49.024 MB.
[2024-08-21T21:24:07.849Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:24:10.773Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:24:13.707Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:24:15.602Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:24:16.522Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:24:18.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:24:20.304Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:24:21.238Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:24:21.238Z] 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.
[2024-08-21T21:24:21.238Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:24:22.159Z] Movies recommended for you:
[2024-08-21T21:24:22.159Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:24:22.159Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:24:22.159Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16326.078 ms) ======
[2024-08-21T21:24:22.159Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-21T21:24:22.159Z] GC before operation: completed in 96.080 ms, heap usage 125.942 MB -> 49.271 MB.
[2024-08-21T21:24:24.051Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:24:26.974Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:24:28.865Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:24:31.787Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:24:33.680Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:24:34.601Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:24:36.492Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:24:37.413Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:24:38.337Z] 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.
[2024-08-21T21:24:38.337Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:24:38.337Z] Movies recommended for you:
[2024-08-21T21:24:38.337Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:24:38.337Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:24:38.337Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16380.109 ms) ======
[2024-08-21T21:24:38.337Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-21T21:24:38.337Z] GC before operation: completed in 98.749 ms, heap usage 127.711 MB -> 49.580 MB.
[2024-08-21T21:24:41.259Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:24:43.152Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:24:46.091Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:24:47.984Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:24:49.876Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:24:50.797Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:24:53.364Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:24:54.493Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:24:54.493Z] 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.
[2024-08-21T21:24:54.493Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:24:54.493Z] Movies recommended for you:
[2024-08-21T21:24:54.493Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:24:54.493Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:24:54.493Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16004.096 ms) ======
[2024-08-21T21:24:54.493Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-21T21:24:54.493Z] GC before operation: completed in 97.595 ms, heap usage 206.677 MB -> 49.811 MB.
[2024-08-21T21:24:56.380Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:24:59.304Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:25:01.194Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:25:03.081Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:25:04.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:25:05.891Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:25:07.782Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:25:08.703Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:25:08.703Z] 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.
[2024-08-21T21:25:08.703Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:25:09.621Z] Movies recommended for you:
[2024-08-21T21:25:09.621Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:25:09.621Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:25:09.621Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14684.423 ms) ======
[2024-08-21T21:25:09.621Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-21T21:25:09.621Z] GC before operation: completed in 98.894 ms, heap usage 276.188 MB -> 49.844 MB.
[2024-08-21T21:25:11.506Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:25:14.427Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:25:16.320Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:25:18.206Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:25:20.101Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:25:21.028Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:25:22.914Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:25:23.833Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:25:24.752Z] 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.
[2024-08-21T21:25:24.752Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:25:24.752Z] Movies recommended for you:
[2024-08-21T21:25:24.752Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:25:24.752Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:25:24.752Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15158.313 ms) ======
[2024-08-21T21:25:24.752Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-21T21:25:24.752Z] GC before operation: completed in 98.200 ms, heap usage 285.690 MB -> 49.974 MB.
[2024-08-21T21:25:26.640Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:25:29.567Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:25:31.456Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:25:33.354Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:25:35.244Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:25:36.167Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:25:38.068Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:25:38.988Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:25:39.909Z] 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.
[2024-08-21T21:25:39.909Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:25:39.909Z] Movies recommended for you:
[2024-08-21T21:25:39.909Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:25:39.909Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:25:39.909Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15254.422 ms) ======
[2024-08-21T21:25:39.909Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-21T21:25:39.909Z] GC before operation: completed in 96.669 ms, heap usage 63.981 MB -> 50.068 MB.
[2024-08-21T21:25:41.803Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:25:44.729Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:25:46.620Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:25:48.510Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:25:50.402Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:25:51.323Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:25:53.218Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:25:54.139Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:25:54.139Z] 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.
[2024-08-21T21:25:54.139Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:25:54.139Z] Movies recommended for you:
[2024-08-21T21:25:54.139Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:25:54.139Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:25:54.139Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14597.417 ms) ======
[2024-08-21T21:25:54.139Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-21T21:25:54.139Z] GC before operation: completed in 90.323 ms, heap usage 187.032 MB -> 50.012 MB.
[2024-08-21T21:25:57.029Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:25:58.920Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:01.840Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:03.733Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:04.654Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:06.544Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:07.465Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:08.386Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:09.307Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-21T21:26:09.307Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:26:09.307Z] Movies recommended for you:
[2024-08-21T21:26:09.307Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:09.307Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:09.307Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14688.965 ms) ======
[2024-08-21T21:26:09.307Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-21T21:26:09.307Z] GC before operation: completed in 94.136 ms, heap usage 205.196 MB -> 50.158 MB.
[2024-08-21T21:26:12.238Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:14.141Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:16.037Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:17.927Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:19.817Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:20.736Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:22.667Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:23.586Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:23.586Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-21T21:26:23.586Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:26:23.586Z] Movies recommended for you:
[2024-08-21T21:26:23.586Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:23.586Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:23.586Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14557.293 ms) ======
[2024-08-21T21:26:23.586Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-21T21:26:23.586Z] GC before operation: completed in 90.382 ms, heap usage 181.870 MB -> 49.935 MB.
[2024-08-21T21:26:26.503Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:28.400Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:31.326Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:33.216Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:34.135Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:36.021Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:36.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:38.829Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:38.829Z] 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.
[2024-08-21T21:26:38.829Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:26:38.829Z] Movies recommended for you:
[2024-08-21T21:26:38.829Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:38.829Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:38.829Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14961.239 ms) ======
[2024-08-21T21:26:38.829Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-21T21:26:38.829Z] GC before operation: completed in 93.282 ms, heap usage 128.482 MB -> 49.987 MB.
[2024-08-21T21:26:41.745Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:43.633Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:45.521Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:47.411Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:49.301Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:50.221Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:52.111Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:53.029Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:53.952Z] 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.
[2024-08-21T21:26:53.952Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:26:53.952Z] Movies recommended for you:
[2024-08-21T21:26:53.952Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:53.952Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:53.952Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14738.305 ms) ======
[2024-08-21T21:26:53.952Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-21T21:26:53.952Z] GC before operation: completed in 99.481 ms, heap usage 177.306 MB -> 50.277 MB.
[2024-08-21T21:26:55.871Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:58.789Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:00.680Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:02.577Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:04.467Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:05.387Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:06.308Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:08.197Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:08.197Z] 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.
[2024-08-21T21:27:08.197Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:27:08.197Z] Movies recommended for you:
[2024-08-21T21:27:08.197Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:08.197Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:08.197Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14496.077 ms) ======
[2024-08-21T21:27:08.197Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-21T21:27:08.197Z] GC before operation: completed in 97.632 ms, heap usage 200.203 MB -> 49.982 MB.
[2024-08-21T21:27:11.124Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:13.013Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:15.932Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:17.822Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:18.742Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:19.661Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:21.549Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:22.470Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:23.391Z] 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.
[2024-08-21T21:27:23.391Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:27:23.391Z] Movies recommended for you:
[2024-08-21T21:27:23.391Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:23.391Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:23.391Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14611.235 ms) ======
[2024-08-21T21:27:23.391Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-21T21:27:23.391Z] GC before operation: completed in 91.135 ms, heap usage 281.409 MB -> 50.257 MB.
[2024-08-21T21:27:25.292Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:28.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:30.102Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:32.001Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:33.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:34.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:36.715Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:37.637Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:37.637Z] 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.
[2024-08-21T21:27:37.637Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:27:38.557Z] Movies recommended for you:
[2024-08-21T21:27:38.557Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:38.557Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:38.557Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14926.603 ms) ======
[2024-08-21T21:27:38.557Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-21T21:27:38.557Z] GC before operation: completed in 91.936 ms, heap usage 271.462 MB -> 50.296 MB.
[2024-08-21T21:27:40.443Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:42.332Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:45.248Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:47.140Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:48.061Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:48.979Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:50.870Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:51.790Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:51.790Z] 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.
[2024-08-21T21:27:51.790Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:27:52.708Z] Movies recommended for you:
[2024-08-21T21:27:52.708Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:52.708Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:52.708Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14041.792 ms) ======
[2024-08-21T21:27:52.708Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-21T21:27:52.708Z] GC before operation: completed in 103.702 ms, heap usage 128.982 MB -> 50.034 MB.
[2024-08-21T21:27:55.430Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:56.461Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:59.378Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:28:01.264Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:28:02.183Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:03.101Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:04.990Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:05.910Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:06.832Z] 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.
[2024-08-21T21:28:06.832Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:28:06.832Z] Movies recommended for you:
[2024-08-21T21:28:06.832Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:06.832Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:06.832Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14246.460 ms) ======
[2024-08-21T21:28:06.832Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-21T21:28:06.832Z] GC before operation: completed in 86.575 ms, heap usage 196.933 MB -> 50.131 MB.
[2024-08-21T21:28:08.891Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:28:10.784Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:28:13.714Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:28:15.607Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:28:16.526Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:17.446Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:19.337Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:20.265Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:20.265Z] 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.
[2024-08-21T21:28:20.265Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:28:20.265Z] Movies recommended for you:
[2024-08-21T21:28:20.265Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:20.265Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:20.265Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14000.809 ms) ======
[2024-08-21T21:28:20.265Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-21T21:28:21.192Z] GC before operation: completed in 95.437 ms, heap usage 196.255 MB -> 50.343 MB.
[2024-08-21T21:28:23.083Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:28:26.005Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:28:27.894Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:28:29.787Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:28:30.707Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:32.599Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:33.520Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:35.416Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:35.417Z] 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.
[2024-08-21T21:28:35.417Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:28:35.417Z] Movies recommended for you:
[2024-08-21T21:28:35.417Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:35.417Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:35.417Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14785.655 ms) ======
[2024-08-21T21:28:36.339Z] -----------------------------------
[2024-08-21T21:28:36.339Z] renaissance-movie-lens_0_PASSED
[2024-08-21T21:28:36.339Z] -----------------------------------
[2024-08-21T21:28:36.339Z]
[2024-08-21T21:28:36.339Z] TEST TEARDOWN:
[2024-08-21T21:28:36.339Z] Nothing to be done for teardown.
[2024-08-21T21:28:36.339Z] renaissance-movie-lens_0 Finish Time: Wed Aug 21 21:28:35 2024 Epoch Time (ms): 1724275715620