renaissance-movie-lens_0
[2025-01-10T19:34:31.454Z] Running test renaissance-movie-lens_0 ...
[2025-01-10T19:34:31.454Z] ===============================================
[2025-01-10T19:34:31.454Z] renaissance-movie-lens_0 Start Time: Fri Jan 10 19:34:31 2025 Epoch Time (ms): 1736537671243
[2025-01-10T19:34:31.454Z] variation: NoOptions
[2025-01-10T19:34:31.454Z] JVM_OPTIONS:
[2025-01-10T19:34:31.454Z] { \
[2025-01-10T19:34:31.454Z] echo ""; echo "TEST SETUP:"; \
[2025-01-10T19:34:31.454Z] echo "Nothing to be done for setup."; \
[2025-01-10T19:34:31.454Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17365368469914/renaissance-movie-lens_0"; \
[2025-01-10T19:34:31.454Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17365368469914/renaissance-movie-lens_0"; \
[2025-01-10T19:34:31.454Z] echo ""; echo "TESTING:"; \
[2025-01-10T19:34:31.454Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17365368469914/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-01-10T19:34:31.454Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17365368469914/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-01-10T19:34:31.454Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-01-10T19:34:31.454Z] echo "Nothing to be done for teardown."; \
[2025-01-10T19:34:31.454Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17365368469914/TestTargetResult";
[2025-01-10T19:34:31.454Z]
[2025-01-10T19:34:31.454Z] TEST SETUP:
[2025-01-10T19:34:31.454Z] Nothing to be done for setup.
[2025-01-10T19:34:31.454Z]
[2025-01-10T19:34:31.454Z] TESTING:
[2025-01-10T19:34:34.475Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-01-10T19:34:36.433Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-01-10T19:34:39.483Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-01-10T19:34:39.483Z] Training: 60056, validation: 20285, test: 19854
[2025-01-10T19:34:39.483Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-01-10T19:34:39.483Z] GC before operation: completed in 47.503 ms, heap usage 121.452 MB -> 37.296 MB.
[2025-01-10T19:34:44.853Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:34:46.806Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:34:49.823Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:34:51.786Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:34:53.740Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:34:54.693Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:34:56.888Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:34:57.838Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:34:57.838Z] 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.
[2025-01-10T19:34:57.838Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:34:58.793Z] Movies recommended for you:
[2025-01-10T19:34:58.793Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:34:58.793Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:34:58.793Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (19153.463 ms) ======
[2025-01-10T19:34:58.793Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-01-10T19:34:58.793Z] GC before operation: completed in 73.153 ms, heap usage 105.593 MB -> 51.672 MB.
[2025-01-10T19:35:00.748Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:35:02.701Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:35:05.763Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:35:07.716Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:35:08.667Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:35:09.617Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:35:11.570Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:35:12.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:35:12.520Z] 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.
[2025-01-10T19:35:12.521Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:35:12.521Z] Movies recommended for you:
[2025-01-10T19:35:12.521Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:35:12.521Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:35:12.521Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (14474.796 ms) ======
[2025-01-10T19:35:12.521Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-01-10T19:35:13.473Z] GC before operation: completed in 61.551 ms, heap usage 97.739 MB -> 49.777 MB.
[2025-01-10T19:35:15.430Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:35:17.382Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:35:19.337Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:35:21.292Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:35:22.242Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:35:23.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:35:25.152Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:35:26.105Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:35:26.105Z] 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.
[2025-01-10T19:35:26.105Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:35:26.105Z] Movies recommended for you:
[2025-01-10T19:35:26.105Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:35:26.105Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:35:26.105Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13457.749 ms) ======
[2025-01-10T19:35:26.105Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-01-10T19:35:26.105Z] GC before operation: completed in 57.770 ms, heap usage 73.516 MB -> 50.085 MB.
[2025-01-10T19:35:28.059Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:35:30.011Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:35:31.967Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:35:34.984Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:35:35.935Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:35:36.887Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:35:37.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:35:38.797Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:35:39.755Z] 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.
[2025-01-10T19:35:39.755Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:35:39.755Z] Movies recommended for you:
[2025-01-10T19:35:39.755Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:35:39.755Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:35:39.755Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13086.554 ms) ======
[2025-01-10T19:35:39.755Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-01-10T19:35:39.755Z] GC before operation: completed in 64.423 ms, heap usage 78.054 MB -> 50.343 MB.
[2025-01-10T19:35:41.706Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:35:43.657Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:35:45.610Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:35:47.353Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:35:49.480Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:35:50.432Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:35:51.387Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:35:52.338Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:35:52.338Z] 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.
[2025-01-10T19:35:53.289Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:35:53.289Z] Movies recommended for you:
[2025-01-10T19:35:53.289Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:35:53.289Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:35:53.289Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13241.480 ms) ======
[2025-01-10T19:35:53.289Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-01-10T19:35:53.289Z] GC before operation: completed in 59.281 ms, heap usage 431.685 MB -> 54.141 MB.
[2025-01-10T19:35:55.241Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:35:57.196Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:35:58.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:36:00.104Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:36:01.056Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:36:03.008Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:36:04.077Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:36:05.027Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:36:05.027Z] 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.
[2025-01-10T19:36:05.027Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:36:05.027Z] Movies recommended for you:
[2025-01-10T19:36:05.027Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:36:05.027Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:36:05.027Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12290.435 ms) ======
[2025-01-10T19:36:05.027Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-01-10T19:36:05.027Z] GC before operation: completed in 64.006 ms, heap usage 496.614 MB -> 54.082 MB.
[2025-01-10T19:36:06.986Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:36:08.938Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:36:10.890Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:36:12.840Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:36:13.792Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:36:14.742Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:36:16.695Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:36:17.646Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:36:17.646Z] 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.
[2025-01-10T19:36:17.646Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:36:17.646Z] Movies recommended for you:
[2025-01-10T19:36:17.646Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:36:17.646Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:36:17.646Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12400.183 ms) ======
[2025-01-10T19:36:17.646Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-01-10T19:36:17.646Z] GC before operation: completed in 64.270 ms, heap usage 230.316 MB -> 50.942 MB.
[2025-01-10T19:36:19.596Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:36:21.549Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:36:23.503Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:36:25.456Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:36:26.408Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:36:27.360Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:36:28.312Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:36:29.267Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:36:29.267Z] 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.
[2025-01-10T19:36:29.267Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:36:30.220Z] Movies recommended for you:
[2025-01-10T19:36:30.220Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:36:30.220Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:36:30.220Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (11995.310 ms) ======
[2025-01-10T19:36:30.220Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-01-10T19:36:30.220Z] GC before operation: completed in 73.619 ms, heap usage 418.369 MB -> 54.530 MB.
[2025-01-10T19:36:31.172Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:36:33.126Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:36:35.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:36:37.036Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:36:39.211Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:36:39.211Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:36:40.162Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:36:42.116Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:36:42.116Z] 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.
[2025-01-10T19:36:42.116Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:36:42.116Z] Movies recommended for you:
[2025-01-10T19:36:42.116Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:36:42.116Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:36:42.116Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12105.607 ms) ======
[2025-01-10T19:36:42.116Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-01-10T19:36:42.116Z] GC before operation: completed in 61.994 ms, heap usage 431.170 MB -> 54.387 MB.
[2025-01-10T19:36:44.069Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:36:46.024Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:36:47.978Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:36:48.936Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:36:49.888Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:36:51.843Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:36:52.795Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:36:53.747Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:36:53.747Z] 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.
[2025-01-10T19:36:53.747Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:36:53.747Z] Movies recommended for you:
[2025-01-10T19:36:53.747Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:36:53.747Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:36:53.747Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12098.058 ms) ======
[2025-01-10T19:36:53.747Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-01-10T19:36:53.747Z] GC before operation: completed in 68.744 ms, heap usage 203.788 MB -> 51.105 MB.
[2025-01-10T19:36:55.702Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:36:57.655Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:36:59.609Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:37:01.568Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:37:02.521Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:37:03.473Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:37:05.428Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:37:06.380Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:37:06.380Z] 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.
[2025-01-10T19:37:06.380Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:37:06.380Z] Movies recommended for you:
[2025-01-10T19:37:06.380Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:37:06.380Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:37:06.380Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12324.850 ms) ======
[2025-01-10T19:37:06.380Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-01-10T19:37:06.380Z] GC before operation: completed in 91.759 ms, heap usage 431.545 MB -> 54.210 MB.
[2025-01-10T19:37:08.362Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:37:10.322Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:37:12.278Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:37:14.359Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:37:15.310Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:37:16.261Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:37:18.211Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:37:19.235Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:37:19.235Z] 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.
[2025-01-10T19:37:19.235Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:37:19.235Z] Movies recommended for you:
[2025-01-10T19:37:19.235Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:37:19.235Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:37:19.235Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12682.599 ms) ======
[2025-01-10T19:37:19.235Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-01-10T19:37:19.235Z] GC before operation: completed in 75.174 ms, heap usage 202.951 MB -> 51.018 MB.
[2025-01-10T19:37:20.855Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:37:22.808Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:37:24.762Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:37:26.714Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:37:27.664Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:37:29.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:37:30.575Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:37:31.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:37:31.528Z] 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.
[2025-01-10T19:37:31.528Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:37:32.481Z] Movies recommended for you:
[2025-01-10T19:37:32.481Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:37:32.481Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:37:32.481Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12689.001 ms) ======
[2025-01-10T19:37:32.481Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-01-10T19:37:32.481Z] GC before operation: completed in 86.159 ms, heap usage 97.253 MB -> 51.072 MB.
[2025-01-10T19:37:33.433Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:37:35.386Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:37:38.401Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:37:39.358Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:37:41.313Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:37:42.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:37:43.218Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:37:44.170Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:37:45.121Z] 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.
[2025-01-10T19:37:45.121Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:37:45.121Z] Movies recommended for you:
[2025-01-10T19:37:45.121Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:37:45.121Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:37:45.121Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12632.779 ms) ======
[2025-01-10T19:37:45.121Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-01-10T19:37:45.121Z] GC before operation: completed in 80.294 ms, heap usage 416.513 MB -> 54.311 MB.
[2025-01-10T19:37:47.075Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:37:49.029Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:37:50.983Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:37:51.934Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:37:53.885Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:37:54.837Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:37:55.789Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:37:56.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:37:57.693Z] 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.
[2025-01-10T19:37:57.693Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:37:57.693Z] Movies recommended for you:
[2025-01-10T19:37:57.693Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:37:57.693Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:37:57.693Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12680.485 ms) ======
[2025-01-10T19:37:57.693Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-01-10T19:37:57.693Z] GC before operation: completed in 77.712 ms, heap usage 437.341 MB -> 54.474 MB.
[2025-01-10T19:37:59.647Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:38:01.604Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:38:03.557Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:38:05.511Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:38:06.465Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:38:07.417Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:38:08.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:38:09.325Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:38:10.276Z] 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.
[2025-01-10T19:38:10.276Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:38:10.276Z] Movies recommended for you:
[2025-01-10T19:38:10.276Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:38:10.276Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:38:10.276Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12435.469 ms) ======
[2025-01-10T19:38:10.276Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-01-10T19:38:10.276Z] GC before operation: completed in 88.453 ms, heap usage 82.167 MB -> 51.024 MB.
[2025-01-10T19:38:12.231Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:38:14.185Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:38:16.140Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:38:19.008Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:38:19.008Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:38:19.960Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:38:20.911Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:38:21.863Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:38:21.863Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-01-10T19:38:21.863Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:38:22.816Z] Movies recommended for you:
[2025-01-10T19:38:22.816Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:38:22.816Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:38:22.816Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12272.731 ms) ======
[2025-01-10T19:38:22.816Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-01-10T19:38:22.816Z] GC before operation: completed in 81.870 ms, heap usage 430.567 MB -> 54.410 MB.
[2025-01-10T19:38:24.768Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:38:25.725Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:38:27.679Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:38:29.635Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:38:30.587Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:38:31.539Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:38:33.505Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:38:34.456Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:38:34.456Z] 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.
[2025-01-10T19:38:34.456Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:38:34.456Z] Movies recommended for you:
[2025-01-10T19:38:34.456Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:38:34.456Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:38:34.456Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12113.500 ms) ======
[2025-01-10T19:38:34.456Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-01-10T19:38:34.456Z] GC before operation: completed in 69.809 ms, heap usage 191.502 MB -> 51.077 MB.
[2025-01-10T19:38:36.413Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:38:38.365Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:38:40.320Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:38:42.274Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:38:43.236Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:38:44.188Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:38:45.140Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:38:46.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:38:47.065Z] 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.
[2025-01-10T19:38:47.065Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:38:47.065Z] Movies recommended for you:
[2025-01-10T19:38:47.065Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:38:47.065Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:38:47.065Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12011.323 ms) ======
[2025-01-10T19:38:47.065Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-01-10T19:38:47.065Z] GC before operation: completed in 70.879 ms, heap usage 430.557 MB -> 54.733 MB.
[2025-01-10T19:38:49.019Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T19:38:49.969Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T19:38:51.924Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T19:38:53.878Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T19:38:54.828Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T19:38:56.777Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T19:38:57.727Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T19:38:58.677Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T19:38:58.677Z] 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.
[2025-01-10T19:38:58.677Z] The best model improves the baseline by 14.52%.
[2025-01-10T19:38:58.677Z] Movies recommended for you:
[2025-01-10T19:38:58.677Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T19:38:58.677Z] There is no way to check that no silent failure occurred.
[2025-01-10T19:38:58.677Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12187.677 ms) ======
[2025-01-10T19:38:59.629Z] -----------------------------------
[2025-01-10T19:38:59.629Z] renaissance-movie-lens_0_PASSED
[2025-01-10T19:38:59.629Z] -----------------------------------
[2025-01-10T19:38:59.629Z]
[2025-01-10T19:38:59.629Z] TEST TEARDOWN:
[2025-01-10T19:38:59.629Z] Nothing to be done for teardown.
[2025-01-10T19:38:59.629Z] renaissance-movie-lens_0 Finish Time: Fri Jan 10 19:38:58 2025 Epoch Time (ms): 1736537938924