renaissance-movie-lens_0
[2024-08-23T21:00:46.157Z] Running test renaissance-movie-lens_0 ...
[2024-08-23T21:00:46.157Z] ===============================================
[2024-08-23T21:00:46.157Z] renaissance-movie-lens_0 Start Time: Fri Aug 23 21:00:45 2024 Epoch Time (ms): 1724446845342
[2024-08-23T21:00:46.157Z] variation: NoOptions
[2024-08-23T21:00:46.157Z] JVM_OPTIONS:
[2024-08-23T21:00:46.157Z] { \
[2024-08-23T21:00:46.157Z] echo ""; echo "TEST SETUP:"; \
[2024-08-23T21:00:46.157Z] echo "Nothing to be done for setup."; \
[2024-08-23T21:00:46.157Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17244458861675/renaissance-movie-lens_0"; \
[2024-08-23T21:00:46.157Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17244458861675/renaissance-movie-lens_0"; \
[2024-08-23T21:00:46.157Z] echo ""; echo "TESTING:"; \
[2024-08-23T21:00:46.157Z] "/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_17244458861675/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-23T21:00:46.157Z] 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_17244458861675/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-23T21:00:46.157Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-23T21:00:46.157Z] echo "Nothing to be done for teardown."; \
[2024-08-23T21:00:46.157Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17244458861675/TestTargetResult";
[2024-08-23T21:00:46.157Z]
[2024-08-23T21:00:46.157Z] TEST SETUP:
[2024-08-23T21:00:46.157Z] Nothing to be done for setup.
[2024-08-23T21:00:46.157Z]
[2024-08-23T21:00:46.157Z] TESTING:
[2024-08-23T21:00:49.103Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-23T21:00:51.010Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-23T21:00:53.958Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-23T21:00:54.887Z] Training: 60056, validation: 20285, test: 19854
[2024-08-23T21:00:54.887Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-23T21:00:54.887Z] GC before operation: completed in 74.705 ms, heap usage 121.014 MB -> 36.442 MB.
[2024-08-23T21:01:00.147Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:01:04.199Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:01:07.143Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:01:10.087Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:01:11.014Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:01:12.928Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:01:14.841Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:01:16.749Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:01:16.749Z] 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.
[2024-08-23T21:01:16.749Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:01:16.749Z] Movies recommended for you:
[2024-08-23T21:01:16.749Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:01:16.749Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:01:16.749Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22352.552 ms) ======
[2024-08-23T21:01:16.749Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-23T21:01:17.677Z] GC before operation: completed in 99.653 ms, heap usage 66.766 MB -> 48.043 MB.
[2024-08-23T21:01:21.731Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:01:23.638Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:01:26.584Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:01:29.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:01:30.458Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:01:32.264Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:01:34.173Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:01:35.101Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:01:36.034Z] 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.
[2024-08-23T21:01:36.034Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:01:36.034Z] Movies recommended for you:
[2024-08-23T21:01:36.034Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:01:36.034Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:01:36.034Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18598.658 ms) ======
[2024-08-23T21:01:36.034Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-23T21:01:36.034Z] GC before operation: completed in 91.829 ms, heap usage 154.976 MB -> 49.067 MB.
[2024-08-23T21:01:39.007Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:01:40.987Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:01:42.904Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:01:45.856Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:01:46.786Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:01:48.697Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:01:50.608Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:01:51.537Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:01:51.537Z] 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.
[2024-08-23T21:01:51.537Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:01:52.541Z] Movies recommended for you:
[2024-08-23T21:01:52.541Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:01:52.541Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:01:52.541Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16039.922 ms) ======
[2024-08-23T21:01:52.541Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-23T21:01:52.541Z] GC before operation: completed in 100.231 ms, heap usage 307.077 MB -> 49.463 MB.
[2024-08-23T21:01:54.556Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:01:56.639Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:01:59.588Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:01.495Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:03.400Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:04.328Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:06.235Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:07.840Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:07.840Z] 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.
[2024-08-23T21:02:07.840Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:07.840Z] Movies recommended for you:
[2024-08-23T21:02:07.840Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:07.840Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:07.840Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15602.319 ms) ======
[2024-08-23T21:02:07.840Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-23T21:02:07.840Z] GC before operation: completed in 94.126 ms, heap usage 91.916 MB -> 49.626 MB.
[2024-08-23T21:02:09.745Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:12.690Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:14.600Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:17.546Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:18.475Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:20.387Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:22.297Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:23.230Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:23.230Z] 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.
[2024-08-23T21:02:23.230Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:24.158Z] Movies recommended for you:
[2024-08-23T21:02:24.158Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:24.158Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:24.158Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16018.765 ms) ======
[2024-08-23T21:02:24.159Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-23T21:02:24.159Z] GC before operation: completed in 92.878 ms, heap usage 80.603 MB -> 49.715 MB.
[2024-08-23T21:02:26.067Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:27.980Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:30.923Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:32.860Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:33.789Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:35.722Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:36.652Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:38.634Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:38.634Z] 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.
[2024-08-23T21:02:38.634Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:38.634Z] Movies recommended for you:
[2024-08-23T21:02:38.634Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:38.634Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:38.634Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14859.434 ms) ======
[2024-08-23T21:02:38.634Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-23T21:02:38.634Z] GC before operation: completed in 95.167 ms, heap usage 255.787 MB -> 49.902 MB.
[2024-08-23T21:02:41.578Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:43.484Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:45.389Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:47.296Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:49.202Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:50.139Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:52.043Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:52.974Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:53.902Z] 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.
[2024-08-23T21:02:53.902Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:53.902Z] Movies recommended for you:
[2024-08-23T21:02:53.902Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:53.902Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:53.902Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14849.744 ms) ======
[2024-08-23T21:02:53.902Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-23T21:02:53.902Z] GC before operation: completed in 100.545 ms, heap usage 153.003 MB -> 50.239 MB.
[2024-08-23T21:02:55.841Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:57.747Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:00.691Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:02.603Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:03.530Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:05.439Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:07.346Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:09.290Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:09.290Z] 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.
[2024-08-23T21:03:09.290Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:09.290Z] Movies recommended for you:
[2024-08-23T21:03:09.290Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:09.290Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:09.290Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14939.996 ms) ======
[2024-08-23T21:03:09.290Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-23T21:03:09.290Z] GC before operation: completed in 94.217 ms, heap usage 69.932 MB -> 50.504 MB.
[2024-08-23T21:03:11.363Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:13.274Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:16.236Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:18.145Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:19.074Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:20.979Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:21.907Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:23.818Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:23.818Z] 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.
[2024-08-23T21:03:23.818Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:23.818Z] Movies recommended for you:
[2024-08-23T21:03:23.818Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:23.818Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:23.818Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15122.441 ms) ======
[2024-08-23T21:03:23.818Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-23T21:03:23.818Z] GC before operation: completed in 93.335 ms, heap usage 76.210 MB -> 50.303 MB.
[2024-08-23T21:03:26.775Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:28.682Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:30.588Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:32.502Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:34.410Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:35.338Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:37.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:38.174Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:39.266Z] 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.
[2024-08-23T21:03:39.266Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:39.267Z] Movies recommended for you:
[2024-08-23T21:03:39.267Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:39.267Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:39.267Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14827.817 ms) ======
[2024-08-23T21:03:39.267Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-23T21:03:39.267Z] GC before operation: completed in 96.388 ms, heap usage 126.944 MB -> 50.518 MB.
[2024-08-23T21:03:41.176Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:44.121Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:46.055Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:47.961Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:49.868Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:50.834Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:52.740Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:53.669Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:54.645Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-23T21:03:54.645Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:54.645Z] Movies recommended for you:
[2024-08-23T21:03:54.645Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:54.645Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:54.645Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15344.225 ms) ======
[2024-08-23T21:03:54.645Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-23T21:03:54.645Z] GC before operation: completed in 94.074 ms, heap usage 323.669 MB -> 50.422 MB.
[2024-08-23T21:03:56.551Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:59.504Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:02.626Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:03.553Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:05.462Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:06.390Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:08.297Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:09.225Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:09.225Z] 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.
[2024-08-23T21:04:10.152Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:10.152Z] Movies recommended for you:
[2024-08-23T21:04:10.152Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:10.152Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:10.152Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15384.139 ms) ======
[2024-08-23T21:04:10.152Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-23T21:04:10.152Z] GC before operation: completed in 96.934 ms, heap usage 125.014 MB -> 50.449 MB.
[2024-08-23T21:04:12.057Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:13.962Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:16.906Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:18.811Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:20.722Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:21.650Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:23.557Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:24.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:25.415Z] 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.
[2024-08-23T21:04:25.415Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:25.415Z] Movies recommended for you:
[2024-08-23T21:04:25.415Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:25.415Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:25.415Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15342.430 ms) ======
[2024-08-23T21:04:25.415Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-23T21:04:25.415Z] GC before operation: completed in 92.057 ms, heap usage 249.302 MB -> 50.720 MB.
[2024-08-23T21:04:27.331Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:30.277Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:32.187Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:34.109Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:36.018Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:36.947Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:38.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:39.787Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:39.787Z] 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.
[2024-08-23T21:04:39.787Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:40.714Z] Movies recommended for you:
[2024-08-23T21:04:40.714Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:40.714Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:40.714Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14936.699 ms) ======
[2024-08-23T21:04:40.714Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-23T21:04:40.714Z] GC before operation: completed in 95.136 ms, heap usage 217.268 MB -> 50.449 MB.
[2024-08-23T21:04:42.618Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:45.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:47.487Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:49.442Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:50.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:52.444Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:53.375Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:55.284Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:55.284Z] 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.
[2024-08-23T21:04:55.284Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:55.284Z] Movies recommended for you:
[2024-08-23T21:04:55.284Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:55.284Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:55.284Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15269.587 ms) ======
[2024-08-23T21:04:55.284Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-23T21:04:56.212Z] GC before operation: completed in 94.194 ms, heap usage 155.968 MB -> 50.553 MB.
[2024-08-23T21:04:58.069Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:05:00.065Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:05:01.970Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:05:04.913Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:05:05.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:05:07.747Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:05:08.674Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:05:10.591Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:05:10.591Z] 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.
[2024-08-23T21:05:10.591Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:05:10.591Z] Movies recommended for you:
[2024-08-23T21:05:10.591Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:05:10.591Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:05:10.591Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14908.026 ms) ======
[2024-08-23T21:05:10.591Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-23T21:05:10.591Z] GC before operation: completed in 104.371 ms, heap usage 190.680 MB -> 50.628 MB.
[2024-08-23T21:05:12.496Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:05:15.438Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:05:17.369Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:05:19.278Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:05:21.185Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:05:22.113Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:05:24.018Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:05:24.950Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:05:24.950Z] 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.
[2024-08-23T21:05:25.879Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:05:25.879Z] Movies recommended for you:
[2024-08-23T21:05:25.879Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:05:25.879Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:05:25.879Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14793.405 ms) ======
[2024-08-23T21:05:25.879Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-23T21:05:25.879Z] GC before operation: completed in 103.964 ms, heap usage 165.030 MB -> 50.476 MB.
[2024-08-23T21:05:27.790Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:05:29.697Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:05:32.644Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:05:34.561Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:05:35.489Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:05:37.399Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:05:38.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:05:40.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:05:40.253Z] 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.
[2024-08-23T21:05:40.253Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:05:40.253Z] Movies recommended for you:
[2024-08-23T21:05:40.253Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:05:40.253Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:05:40.253Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14698.625 ms) ======
[2024-08-23T21:05:40.253Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-23T21:05:40.253Z] GC before operation: completed in 97.371 ms, heap usage 155.279 MB -> 50.580 MB.
[2024-08-23T21:05:43.206Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:05:45.112Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:05:47.019Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:05:48.925Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:05:50.834Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:05:52.522Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:05:53.452Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:05:55.372Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:05:55.372Z] 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.
[2024-08-23T21:05:55.372Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:05:55.372Z] Movies recommended for you:
[2024-08-23T21:05:55.372Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:05:55.372Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:05:55.372Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14861.146 ms) ======
[2024-08-23T21:05:55.372Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-23T21:05:55.372Z] GC before operation: completed in 94.159 ms, heap usage 213.754 MB -> 50.749 MB.
[2024-08-23T21:05:57.283Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:06:00.234Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:06:02.144Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:06:04.052Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:06:05.964Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:06:06.893Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:06:07.821Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:06:09.760Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:06:09.760Z] 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.
[2024-08-23T21:06:09.760Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:06:09.760Z] Movies recommended for you:
[2024-08-23T21:06:09.760Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:06:09.760Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:06:09.760Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14627.138 ms) ======
[2024-08-23T21:06:10.688Z] -----------------------------------
[2024-08-23T21:06:10.688Z] renaissance-movie-lens_0_PASSED
[2024-08-23T21:06:10.688Z] -----------------------------------
[2024-08-23T21:06:10.688Z]
[2024-08-23T21:06:10.688Z] TEST TEARDOWN:
[2024-08-23T21:06:10.688Z] Nothing to be done for teardown.
[2024-08-23T21:06:10.688Z] renaissance-movie-lens_0 Finish Time: Fri Aug 23 21:06:10 2024 Epoch Time (ms): 1724447170046