renaissance-movie-lens_0
[2024-08-10T14:40:50.886Z] Running test renaissance-movie-lens_0 ...
[2024-08-10T14:40:50.886Z] ===============================================
[2024-08-10T14:40:50.886Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 14:40:49 2024 Epoch Time (ms): 1723300849912
[2024-08-10T14:40:50.886Z] variation: NoOptions
[2024-08-10T14:40:50.886Z] JVM_OPTIONS:
[2024-08-10T14:40:50.886Z] { \
[2024-08-10T14:40:50.886Z] echo ""; echo "TEST SETUP:"; \
[2024-08-10T14:40:50.886Z] echo "Nothing to be done for setup."; \
[2024-08-10T14:40:50.886Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232999331475/renaissance-movie-lens_0"; \
[2024-08-10T14:40:50.886Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232999331475/renaissance-movie-lens_0"; \
[2024-08-10T14:40:50.886Z] echo ""; echo "TESTING:"; \
[2024-08-10T14:40:50.886Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-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_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232999331475/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-10T14:40:50.886Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232999331475/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-10T14:40:50.886Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-10T14:40:50.886Z] echo "Nothing to be done for teardown."; \
[2024-08-10T14:40:50.886Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232999331475/TestTargetResult";
[2024-08-10T14:40:50.886Z]
[2024-08-10T14:40:50.886Z] TEST SETUP:
[2024-08-10T14:40:50.886Z] Nothing to be done for setup.
[2024-08-10T14:40:50.886Z]
[2024-08-10T14:40:50.886Z] TESTING:
[2024-08-10T14:40:53.619Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-10T14:40:56.342Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-10T14:41:00.104Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-10T14:41:00.963Z] Training: 60056, validation: 20285, test: 19854
[2024-08-10T14:41:00.963Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-10T14:41:00.963Z] GC before operation: completed in 65.015 ms, heap usage 102.769 MB -> 36.449 MB.
[2024-08-10T14:41:09.947Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:41:14.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:41:19.714Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:41:23.477Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:41:25.235Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:41:28.121Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:41:29.810Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:41:32.425Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:41:32.425Z] 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.
[2024-08-10T14:41:32.425Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:41:32.425Z] Movies recommended for you:
[2024-08-10T14:41:32.425Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:41:32.425Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:41:32.425Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (31935.126 ms) ======
[2024-08-10T14:41:32.425Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-10T14:41:32.425Z] GC before operation: completed in 153.917 ms, heap usage 238.744 MB -> 49.984 MB.
[2024-08-10T14:41:36.060Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:41:39.684Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:41:43.388Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:41:46.015Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:41:47.710Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:41:50.329Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:41:52.019Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:41:53.705Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:41:53.705Z] 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.
[2024-08-10T14:41:53.705Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:41:53.705Z] Movies recommended for you:
[2024-08-10T14:41:53.705Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:41:53.705Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:41:53.705Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21295.823 ms) ======
[2024-08-10T14:41:53.705Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-10T14:41:54.526Z] GC before operation: completed in 107.116 ms, heap usage 203.441 MB -> 49.101 MB.
[2024-08-10T14:41:57.145Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:42:00.766Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:42:03.381Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:42:07.001Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:42:08.690Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:42:10.390Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:42:12.078Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:42:13.766Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:42:14.583Z] 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.
[2024-08-10T14:42:14.583Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:42:14.583Z] Movies recommended for you:
[2024-08-10T14:42:14.583Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:42:14.583Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:42:14.583Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20374.142 ms) ======
[2024-08-10T14:42:14.583Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-10T14:42:14.583Z] GC before operation: completed in 118.360 ms, heap usage 175.973 MB -> 49.388 MB.
[2024-08-10T14:42:17.548Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:42:20.169Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:42:23.793Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:42:26.348Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:42:28.851Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:42:30.460Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:42:32.070Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:42:33.677Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:42:34.457Z] 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.
[2024-08-10T14:42:34.457Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:42:34.457Z] Movies recommended for you:
[2024-08-10T14:42:34.457Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:42:34.457Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:42:34.457Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19797.486 ms) ======
[2024-08-10T14:42:34.457Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-10T14:42:34.457Z] GC before operation: completed in 112.578 ms, heap usage 216.631 MB -> 49.721 MB.
[2024-08-10T14:42:37.915Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:42:40.418Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:42:44.048Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:42:46.549Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:42:48.153Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:42:50.648Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:42:52.256Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:42:53.865Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:42:53.865Z] 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.
[2024-08-10T14:42:53.865Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:42:53.865Z] Movies recommended for you:
[2024-08-10T14:42:53.865Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:42:53.865Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:42:53.865Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19685.421 ms) ======
[2024-08-10T14:42:53.865Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-10T14:42:54.642Z] GC before operation: completed in 109.157 ms, heap usage 230.745 MB -> 49.903 MB.
[2024-08-10T14:42:57.139Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:43:00.594Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:43:03.609Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:43:06.104Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:43:07.719Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:43:09.326Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:43:11.822Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:43:13.427Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:43:13.427Z] 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.
[2024-08-10T14:43:13.427Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:43:13.427Z] Movies recommended for you:
[2024-08-10T14:43:13.427Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:43:13.427Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:43:13.427Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19215.112 ms) ======
[2024-08-10T14:43:13.427Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-10T14:43:13.427Z] GC before operation: completed in 117.636 ms, heap usage 213.583 MB -> 49.835 MB.
[2024-08-10T14:43:16.884Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:43:19.377Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:43:22.834Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:43:25.329Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:43:26.936Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:43:28.546Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:43:30.154Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:43:32.655Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:43:32.655Z] 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.
[2024-08-10T14:43:32.655Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:43:32.655Z] Movies recommended for you:
[2024-08-10T14:43:32.655Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:43:32.655Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:43:32.655Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18950.250 ms) ======
[2024-08-10T14:43:32.655Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-10T14:43:32.655Z] GC before operation: completed in 96.683 ms, heap usage 229.928 MB -> 50.010 MB.
[2024-08-10T14:43:35.158Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:43:38.616Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:43:41.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:43:43.614Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:43:45.222Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:43:46.828Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:43:48.982Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:43:50.591Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:43:50.591Z] 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.
[2024-08-10T14:43:50.591Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:43:51.368Z] Movies recommended for you:
[2024-08-10T14:43:51.368Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:43:51.368Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:43:51.369Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18346.503 ms) ======
[2024-08-10T14:43:51.369Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-10T14:43:51.369Z] GC before operation: completed in 115.953 ms, heap usage 205.671 MB -> 50.259 MB.
[2024-08-10T14:43:53.869Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:43:56.384Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:43:59.844Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:44:02.337Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:44:03.952Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:44:05.565Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:44:07.169Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:44:08.785Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:44:09.566Z] 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.
[2024-08-10T14:44:09.566Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:44:09.566Z] Movies recommended for you:
[2024-08-10T14:44:09.566Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:44:09.566Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:44:09.566Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18160.073 ms) ======
[2024-08-10T14:44:09.566Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-10T14:44:09.566Z] GC before operation: completed in 98.992 ms, heap usage 197.460 MB -> 50.082 MB.
[2024-08-10T14:44:12.062Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:44:15.527Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:44:18.028Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:44:20.526Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:44:22.138Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:44:23.751Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:44:25.359Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:44:27.857Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:44:27.857Z] 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.
[2024-08-10T14:44:27.857Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:44:27.857Z] Movies recommended for you:
[2024-08-10T14:44:27.857Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:44:27.857Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:44:27.857Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18363.556 ms) ======
[2024-08-10T14:44:27.857Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-10T14:44:27.858Z] GC before operation: completed in 99.439 ms, heap usage 175.572 MB -> 50.568 MB.
[2024-08-10T14:44:30.356Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:44:33.815Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:44:36.310Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:44:39.344Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:44:41.015Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:44:42.621Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:44:44.231Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:44:45.841Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:44:45.841Z] 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.
[2024-08-10T14:44:45.841Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:44:45.841Z] Movies recommended for you:
[2024-08-10T14:44:45.841Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:44:45.841Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:44:45.841Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18255.967 ms) ======
[2024-08-10T14:44:45.841Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-10T14:44:46.621Z] GC before operation: completed in 94.629 ms, heap usage 222.545 MB -> 49.972 MB.
[2024-08-10T14:44:49.134Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:44:51.633Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:44:55.092Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:44:57.589Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:44:59.221Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:45:00.833Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:45:02.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:45:04.045Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:45:04.045Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-10T14:45:04.045Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:45:04.045Z] Movies recommended for you:
[2024-08-10T14:45:04.045Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:45:04.045Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:45:04.045Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18113.952 ms) ======
[2024-08-10T14:45:04.045Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-10T14:45:04.822Z] GC before operation: completed in 101.443 ms, heap usage 152.745 MB -> 50.105 MB.
[2024-08-10T14:45:07.321Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:45:09.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:45:13.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:45:15.773Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:45:17.379Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:45:18.988Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:45:20.596Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:45:22.205Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:45:23.257Z] 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.
[2024-08-10T14:45:23.258Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:45:23.258Z] Movies recommended for you:
[2024-08-10T14:45:23.258Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:45:23.258Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:45:23.258Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18300.844 ms) ======
[2024-08-10T14:45:23.258Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-10T14:45:23.258Z] GC before operation: completed in 104.857 ms, heap usage 219.819 MB -> 50.293 MB.
[2024-08-10T14:45:25.752Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:45:28.250Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:45:31.708Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:45:34.204Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:45:35.810Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:45:37.550Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:45:39.158Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:45:40.765Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:45:40.765Z] 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.
[2024-08-10T14:45:40.765Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:45:41.543Z] Movies recommended for you:
[2024-08-10T14:45:41.543Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:45:41.543Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:45:41.543Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18370.802 ms) ======
[2024-08-10T14:45:41.543Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-10T14:45:41.543Z] GC before operation: completed in 103.475 ms, heap usage 191.136 MB -> 50.029 MB.
[2024-08-10T14:45:44.097Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:45:46.592Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:45:50.046Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:45:52.539Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:45:54.147Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:45:55.756Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:45:57.365Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:45:58.972Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:45:58.972Z] 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.
[2024-08-10T14:45:58.972Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:45:59.750Z] Movies recommended for you:
[2024-08-10T14:45:59.750Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:45:59.750Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:45:59.750Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18105.897 ms) ======
[2024-08-10T14:45:59.750Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-10T14:45:59.750Z] GC before operation: completed in 95.656 ms, heap usage 231.028 MB -> 50.192 MB.
[2024-08-10T14:46:02.243Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:46:04.738Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:46:08.191Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:46:11.208Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:46:12.817Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:46:14.426Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:46:16.035Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:46:17.646Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:46:17.646Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-10T14:46:17.646Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:46:17.646Z] Movies recommended for you:
[2024-08-10T14:46:17.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:46:17.646Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:46:17.646Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18406.497 ms) ======
[2024-08-10T14:46:17.646Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-10T14:46:18.425Z] GC before operation: completed in 101.889 ms, heap usage 204.822 MB -> 50.262 MB.
[2024-08-10T14:46:20.925Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:46:23.421Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:46:26.886Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:46:29.389Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:46:30.997Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:46:32.603Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:46:34.209Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:46:35.816Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:46:36.594Z] 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.
[2024-08-10T14:46:36.594Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:46:36.594Z] Movies recommended for you:
[2024-08-10T14:46:36.594Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:46:36.594Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:46:36.594Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18390.425 ms) ======
[2024-08-10T14:46:36.594Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-10T14:46:36.594Z] GC before operation: completed in 103.127 ms, heap usage 177.118 MB -> 50.159 MB.
[2024-08-10T14:46:39.094Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:46:42.547Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:46:45.176Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:46:47.632Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:46:49.214Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:46:50.792Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:46:53.248Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:46:54.014Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:46:55.287Z] 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.
[2024-08-10T14:46:55.287Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:46:55.287Z] Movies recommended for you:
[2024-08-10T14:46:55.287Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:46:55.287Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:46:55.287Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18171.403 ms) ======
[2024-08-10T14:46:55.287Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-10T14:46:55.287Z] GC before operation: completed in 101.132 ms, heap usage 199.148 MB -> 50.212 MB.
[2024-08-10T14:46:57.746Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:47:00.212Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:47:03.615Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:47:06.080Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:47:07.665Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:47:09.246Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:47:10.827Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:47:12.411Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:47:13.178Z] 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.
[2024-08-10T14:47:13.178Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:47:13.178Z] Movies recommended for you:
[2024-08-10T14:47:13.178Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:47:13.178Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:47:13.178Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18269.408 ms) ======
[2024-08-10T14:47:13.178Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-10T14:47:13.178Z] GC before operation: completed in 97.688 ms, heap usage 140.901 MB -> 50.308 MB.
[2024-08-10T14:47:15.646Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T14:47:19.052Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T14:47:21.520Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T14:47:23.981Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T14:47:25.561Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T14:47:27.141Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T14:47:29.595Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T14:47:31.175Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T14:47:31.175Z] 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.
[2024-08-10T14:47:31.175Z] The best model improves the baseline by 14.52%.
[2024-08-10T14:47:31.176Z] Movies recommended for you:
[2024-08-10T14:47:31.176Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T14:47:31.176Z] There is no way to check that no silent failure occurred.
[2024-08-10T14:47:31.176Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18167.888 ms) ======
[2024-08-10T14:47:31.939Z] -----------------------------------
[2024-08-10T14:47:31.939Z] renaissance-movie-lens_0_PASSED
[2024-08-10T14:47:31.939Z] -----------------------------------
[2024-08-10T14:47:31.939Z]
[2024-08-10T14:47:31.939Z] TEST TEARDOWN:
[2024-08-10T14:47:31.939Z] Nothing to be done for teardown.
[2024-08-10T14:47:31.939Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 14:47:31 2024 Epoch Time (ms): 1723301251305