renaissance-movie-lens_0
[2025-02-06T12:02:02.570Z] Running test renaissance-movie-lens_0 ...
[2025-02-06T12:02:02.570Z] ===============================================
[2025-02-06T12:02:02.570Z] renaissance-movie-lens_0 Start Time: Thu Feb 6 12:02:01 2025 Epoch Time (ms): 1738843321512
[2025-02-06T12:02:02.570Z] variation: NoOptions
[2025-02-06T12:02:02.570Z] JVM_OPTIONS:
[2025-02-06T12:02:02.570Z] { \
[2025-02-06T12:02:02.570Z] echo ""; echo "TEST SETUP:"; \
[2025-02-06T12:02:02.570Z] echo "Nothing to be done for setup."; \
[2025-02-06T12:02:02.570Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17388402802782/renaissance-movie-lens_0"; \
[2025-02-06T12:02:02.570Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17388402802782/renaissance-movie-lens_0"; \
[2025-02-06T12:02:02.570Z] echo ""; echo "TESTING:"; \
[2025-02-06T12:02:02.570Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17388402802782/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-06T12:02:02.570Z] 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/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17388402802782/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-06T12:02:02.570Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-06T12:02:02.570Z] echo "Nothing to be done for teardown."; \
[2025-02-06T12:02:02.570Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17388402802782/TestTargetResult";
[2025-02-06T12:02:02.570Z]
[2025-02-06T12:02:02.570Z] TEST SETUP:
[2025-02-06T12:02:02.570Z] Nothing to be done for setup.
[2025-02-06T12:02:02.570Z]
[2025-02-06T12:02:02.570Z] TESTING:
[2025-02-06T12:02:10.946Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-06T12:02:17.915Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-02-06T12:02:31.884Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-06T12:02:32.674Z] Training: 60056, validation: 20285, test: 19854
[2025-02-06T12:02:32.674Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-06T12:02:33.455Z] GC before operation: completed in 274.817 ms, heap usage 58.610 MB -> 36.465 MB.
[2025-02-06T12:03:03.921Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:03:23.230Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:03:37.238Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:03:51.308Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:03:58.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:04:06.809Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:04:15.288Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:04:22.382Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:04:23.176Z] 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.
[2025-02-06T12:04:23.176Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:04:23.987Z] Movies recommended for you:
[2025-02-06T12:04:23.987Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:04:23.987Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:04:23.987Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (111046.957 ms) ======
[2025-02-06T12:04:23.987Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-06T12:04:24.783Z] GC before operation: completed in 740.545 ms, heap usage 210.010 MB -> 49.025 MB.
[2025-02-06T12:04:38.678Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:04:56.524Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:05:10.454Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:05:18.952Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:05:25.989Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:05:30.601Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:05:35.784Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:05:41.601Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:05:42.412Z] 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.
[2025-02-06T12:05:42.412Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:05:42.412Z] Movies recommended for you:
[2025-02-06T12:05:42.412Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:05:42.412Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:05:42.412Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (77759.352 ms) ======
[2025-02-06T12:05:42.412Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-06T12:05:43.208Z] GC before operation: completed in 444.867 ms, heap usage 59.513 MB -> 48.866 MB.
[2025-02-06T12:05:53.294Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:06:03.335Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:06:13.444Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:06:23.573Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:06:29.385Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:06:37.263Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:06:44.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:06:51.364Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:06:51.364Z] 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.
[2025-02-06T12:06:51.364Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:06:52.168Z] Movies recommended for you:
[2025-02-06T12:06:52.168Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:06:52.168Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:06:52.168Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (68948.503 ms) ======
[2025-02-06T12:06:52.168Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-06T12:06:52.954Z] GC before operation: completed in 432.162 ms, heap usage 179.675 MB -> 49.299 MB.
[2025-02-06T12:07:04.968Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:07:15.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:07:27.194Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:07:35.733Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:07:41.819Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:07:47.635Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:07:54.726Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:07:59.386Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:08:00.210Z] 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.
[2025-02-06T12:08:00.210Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:08:00.210Z] Movies recommended for you:
[2025-02-06T12:08:00.210Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:08:00.210Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:08:00.210Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (67657.803 ms) ======
[2025-02-06T12:08:00.210Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-06T12:08:01.009Z] GC before operation: completed in 423.012 ms, heap usage 203.726 MB -> 49.840 MB.
[2025-02-06T12:08:08.059Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:08:18.223Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:08:28.295Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:08:35.344Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:08:41.645Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:08:47.413Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:08:54.504Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:08:59.127Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:09:00.802Z] 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.
[2025-02-06T12:09:00.802Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:09:00.802Z] Movies recommended for you:
[2025-02-06T12:09:00.802Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:09:00.802Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:09:00.802Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60118.142 ms) ======
[2025-02-06T12:09:00.802Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-06T12:09:01.593Z] GC before operation: completed in 373.547 ms, heap usage 113.720 MB -> 49.816 MB.
[2025-02-06T12:09:12.167Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:09:20.718Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:09:30.735Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:09:40.783Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:09:47.154Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:09:52.926Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:09:58.681Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:10:04.502Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:10:06.148Z] 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.
[2025-02-06T12:10:06.148Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:10:06.148Z] Movies recommended for you:
[2025-02-06T12:10:06.148Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:10:06.148Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:10:06.148Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (65151.227 ms) ======
[2025-02-06T12:10:06.148Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-06T12:10:06.957Z] GC before operation: completed in 410.795 ms, heap usage 232.533 MB -> 49.765 MB.
[2025-02-06T12:10:15.441Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:10:22.494Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:10:31.043Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:10:39.572Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:10:47.332Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:10:50.870Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:10:56.643Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:11:01.212Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:11:02.028Z] 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.
[2025-02-06T12:11:02.028Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:11:02.028Z] Movies recommended for you:
[2025-02-06T12:11:02.028Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:11:02.028Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:11:02.028Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55583.998 ms) ======
[2025-02-06T12:11:02.028Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-06T12:11:02.808Z] GC before operation: completed in 166.506 ms, heap usage 260.131 MB -> 49.989 MB.
[2025-02-06T12:11:05.341Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:11:13.857Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:11:20.903Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:11:30.653Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:11:35.403Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:11:40.040Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:11:47.140Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:11:51.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:11:53.436Z] 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.
[2025-02-06T12:11:53.436Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:11:53.436Z] Movies recommended for you:
[2025-02-06T12:11:53.436Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:11:53.436Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:11:53.436Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (51095.209 ms) ======
[2025-02-06T12:11:53.436Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-06T12:11:54.235Z] GC before operation: completed in 350.859 ms, heap usage 123.275 MB -> 50.118 MB.
[2025-02-06T12:12:04.403Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:12:12.848Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:12:21.289Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:12:27.014Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:12:32.748Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:12:37.386Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:12:47.519Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:12:53.874Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:12:55.123Z] 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.
[2025-02-06T12:12:55.123Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:12:58.609Z] Movies recommended for you:
[2025-02-06T12:12:58.609Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:12:58.609Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:12:58.609Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (64512.284 ms) ======
[2025-02-06T12:12:58.609Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-06T12:12:58.609Z] GC before operation: completed in 486.552 ms, heap usage 229.318 MB -> 50.035 MB.
[2025-02-06T12:13:08.797Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:13:18.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:13:30.934Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:13:38.029Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:13:43.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:13:50.930Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:13:57.226Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:14:04.400Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:14:06.047Z] 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.
[2025-02-06T12:14:06.047Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:14:06.047Z] Movies recommended for you:
[2025-02-06T12:14:06.047Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:14:06.047Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:14:06.047Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (67098.320 ms) ======
[2025-02-06T12:14:06.047Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-06T12:14:06.840Z] GC before operation: completed in 555.500 ms, heap usage 124.353 MB -> 50.212 MB.
[2025-02-06T12:14:17.057Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:14:29.014Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:14:37.587Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:14:46.263Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:14:50.857Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:14:55.444Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:15:00.767Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:15:05.361Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:15:05.361Z] 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.
[2025-02-06T12:15:05.361Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:15:05.361Z] Movies recommended for you:
[2025-02-06T12:15:05.361Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:15:05.361Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:15:05.361Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (59091.515 ms) ======
[2025-02-06T12:15:05.361Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-06T12:15:06.169Z] GC before operation: completed in 271.397 ms, heap usage 230.682 MB -> 49.882 MB.
[2025-02-06T12:15:20.081Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:15:30.223Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:15:42.431Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:15:51.434Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:16:00.793Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:16:07.441Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:16:12.331Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:16:17.175Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:16:18.030Z] 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.
[2025-02-06T12:16:18.030Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:16:18.030Z] Movies recommended for you:
[2025-02-06T12:16:18.030Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:16:18.030Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:16:18.030Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (72268.970 ms) ======
[2025-02-06T12:16:18.030Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-06T12:16:18.893Z] GC before operation: completed in 344.005 ms, heap usage 143.296 MB -> 50.015 MB.
[2025-02-06T12:16:26.271Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:16:35.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:16:48.274Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:16:57.229Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:17:02.069Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:17:08.125Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:17:14.847Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:17:22.407Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:17:26.119Z] 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.
[2025-02-06T12:17:26.119Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:17:26.119Z] Movies recommended for you:
[2025-02-06T12:17:26.119Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:17:26.119Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:17:26.119Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (67815.697 ms) ======
[2025-02-06T12:17:26.119Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-06T12:17:26.978Z] GC before operation: completed in 343.612 ms, heap usage 106.812 MB -> 50.123 MB.
[2025-02-06T12:17:39.499Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:17:52.090Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:18:01.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:18:11.902Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:18:19.412Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:18:24.851Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:18:32.475Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:18:40.081Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:18:41.056Z] 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.
[2025-02-06T12:18:41.056Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:18:41.924Z] Movies recommended for you:
[2025-02-06T12:18:41.924Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:18:41.924Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:18:41.924Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (74688.335 ms) ======
[2025-02-06T12:18:41.924Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-06T12:18:41.924Z] GC before operation: completed in 533.045 ms, heap usage 111.477 MB -> 49.880 MB.
[2025-02-06T12:18:54.607Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:19:10.197Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:19:25.578Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:19:34.597Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:19:42.500Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:19:50.128Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:19:57.659Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:20:03.857Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:20:04.727Z] 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.
[2025-02-06T12:20:04.727Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:20:04.727Z] Movies recommended for you:
[2025-02-06T12:20:04.727Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:20:04.727Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:20:04.727Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (83023.483 ms) ======
[2025-02-06T12:20:04.727Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-06T12:20:05.589Z] GC before operation: completed in 499.526 ms, heap usage 69.262 MB -> 49.993 MB.
[2025-02-06T12:20:20.310Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:20:31.043Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:20:41.793Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:20:51.459Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:21:00.464Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:21:07.952Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:21:15.427Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:21:21.652Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:21:23.455Z] 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.
[2025-02-06T12:21:23.455Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:21:24.326Z] Movies recommended for you:
[2025-02-06T12:21:24.326Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:21:24.326Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:21:24.326Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (78497.489 ms) ======
[2025-02-06T12:21:24.326Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-06T12:21:24.326Z] GC before operation: completed in 657.632 ms, heap usage 215.894 MB -> 50.234 MB.
[2025-02-06T12:21:42.616Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:21:53.357Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:22:06.580Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:22:17.326Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:22:25.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:22:33.225Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:22:39.433Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:22:47.068Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:22:47.917Z] 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.
[2025-02-06T12:22:47.917Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:22:48.762Z] Movies recommended for you:
[2025-02-06T12:22:48.762Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:22:48.762Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:22:48.762Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (83652.700 ms) ======
[2025-02-06T12:22:48.762Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-06T12:22:48.762Z] GC before operation: completed in 552.857 ms, heap usage 194.670 MB -> 50.252 MB.
[2025-02-06T12:23:03.531Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:23:14.890Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:23:27.478Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:23:36.532Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:23:43.978Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:23:50.072Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:23:57.536Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:24:05.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:24:05.896Z] 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.
[2025-02-06T12:24:05.896Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:24:06.770Z] Movies recommended for you:
[2025-02-06T12:24:06.770Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:24:06.770Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:24:06.770Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (77573.708 ms) ======
[2025-02-06T12:24:06.770Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-06T12:24:06.770Z] GC before operation: completed in 433.794 ms, heap usage 178.781 MB -> 50.272 MB.
[2025-02-06T12:24:24.702Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:24:37.359Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:24:49.994Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:25:04.797Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:25:06.549Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:25:10.320Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:25:17.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:25:25.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:25:27.707Z] 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.
[2025-02-06T12:25:27.707Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:25:27.707Z] Movies recommended for you:
[2025-02-06T12:25:27.707Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:25:27.707Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:25:27.707Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (80597.907 ms) ======
[2025-02-06T12:25:27.707Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-06T12:25:28.590Z] GC before operation: completed in 557.270 ms, heap usage 141.302 MB -> 50.253 MB.
[2025-02-06T12:25:39.329Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T12:25:51.643Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T12:26:02.197Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T12:26:11.049Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T12:26:17.007Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T12:26:22.968Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T12:26:28.957Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T12:26:35.309Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T12:26:36.152Z] 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.
[2025-02-06T12:26:36.152Z] The best model improves the baseline by 14.52%.
[2025-02-06T12:26:36.985Z] Movies recommended for you:
[2025-02-06T12:26:36.985Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T12:26:36.985Z] There is no way to check that no silent failure occurred.
[2025-02-06T12:26:36.985Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (68788.089 ms) ======
[2025-02-06T12:26:38.723Z] -----------------------------------
[2025-02-06T12:26:38.723Z] renaissance-movie-lens_0_PASSED
[2025-02-06T12:26:38.723Z] -----------------------------------
[2025-02-06T12:26:38.723Z]
[2025-02-06T12:26:38.723Z] TEST TEARDOWN:
[2025-02-06T12:26:38.723Z] Nothing to be done for teardown.
[2025-02-06T12:26:38.723Z] renaissance-movie-lens_0 Finish Time: Thu Feb 6 12:26:38 2025 Epoch Time (ms): 1738844798455