renaissance-movie-lens_0
[2025-02-20T01:56:07.818Z] Running test renaissance-movie-lens_0 ...
[2025-02-20T01:56:07.818Z] ===============================================
[2025-02-20T01:56:07.818Z] renaissance-movie-lens_0 Start Time: Thu Feb 20 01:56:06 2025 Epoch Time (ms): 1740016566395
[2025-02-20T01:56:07.818Z] variation: NoOptions
[2025-02-20T01:56:07.818Z] JVM_OPTIONS:
[2025-02-20T01:56:07.818Z] { \
[2025-02-20T01:56:07.818Z] echo ""; echo "TEST SETUP:"; \
[2025-02-20T01:56:07.818Z] echo "Nothing to be done for setup."; \
[2025-02-20T01:56:07.818Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17400148699441/renaissance-movie-lens_0"; \
[2025-02-20T01:56:07.818Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17400148699441/renaissance-movie-lens_0"; \
[2025-02-20T01:56:07.818Z] echo ""; echo "TESTING:"; \
[2025-02-20T01:56:07.818Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/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_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17400148699441/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-20T01:56:07.818Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17400148699441/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-20T01:56:07.818Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-20T01:56:07.818Z] echo "Nothing to be done for teardown."; \
[2025-02-20T01:56:07.818Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17400148699441/TestTargetResult";
[2025-02-20T01:56:07.818Z]
[2025-02-20T01:56:07.818Z] TEST SETUP:
[2025-02-20T01:56:07.818Z] Nothing to be done for setup.
[2025-02-20T01:56:07.818Z]
[2025-02-20T01:56:07.818Z] TESTING:
[2025-02-20T01:56:49.214Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-20T01:56:50.802Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 16) threads.
[2025-02-20T01:56:57.672Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-20T01:56:57.672Z] Training: 60056, validation: 20285, test: 19854
[2025-02-20T01:56:57.672Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-20T01:56:57.672Z] GC before operation: completed in 68.755 ms, heap usage 327.908 MB -> 37.316 MB.
[2025-02-20T01:57:04.568Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:57:09.038Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:57:13.498Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:57:16.924Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:57:19.399Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:57:20.990Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:57:25.453Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:57:27.437Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:57:27.437Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:57:27.437Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:57:28.212Z] Movies recommended for you:
[2025-02-20T01:57:28.212Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:57:28.212Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:57:28.212Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (30004.635 ms) ======
[2025-02-20T01:57:28.212Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-20T01:57:28.212Z] GC before operation: completed in 121.067 ms, heap usage 579.782 MB -> 52.819 MB.
[2025-02-20T01:57:31.640Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:57:35.065Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:57:38.597Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:57:42.026Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:57:44.511Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:57:46.127Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:57:48.603Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:57:50.202Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:57:50.970Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:57:50.970Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:57:50.970Z] Movies recommended for you:
[2025-02-20T01:57:50.970Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:57:50.970Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:57:50.970Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23041.626 ms) ======
[2025-02-20T01:57:50.970Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-20T01:57:50.970Z] GC before operation: completed in 146.981 ms, heap usage 462.285 MB -> 51.120 MB.
[2025-02-20T01:57:54.618Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:57:58.046Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:58:01.514Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:58:04.955Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:58:06.559Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:58:09.040Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:58:12.486Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:58:14.174Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:58:14.946Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:58:14.946Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:58:14.946Z] Movies recommended for you:
[2025-02-20T01:58:14.946Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:58:14.946Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:58:14.946Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23554.222 ms) ======
[2025-02-20T01:58:14.946Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-20T01:58:14.946Z] GC before operation: completed in 111.330 ms, heap usage 422.233 MB -> 51.448 MB.
[2025-02-20T01:58:18.433Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:58:20.917Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:58:25.380Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:58:28.811Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:58:31.282Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:58:32.875Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:58:34.479Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:58:36.986Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:58:36.986Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:58:36.986Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:58:36.986Z] Movies recommended for you:
[2025-02-20T01:58:36.986Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:58:36.986Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:58:36.986Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22142.948 ms) ======
[2025-02-20T01:58:36.986Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-20T01:58:36.986Z] GC before operation: completed in 147.538 ms, heap usage 128.247 MB -> 51.593 MB.
[2025-02-20T01:58:40.411Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:58:43.840Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:58:47.701Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:58:50.175Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:58:51.770Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:58:54.248Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:58:56.727Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:58:58.363Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:58:58.364Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:58:58.364Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:58:59.134Z] Movies recommended for you:
[2025-02-20T01:58:59.134Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:58:59.134Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:58:59.134Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21583.857 ms) ======
[2025-02-20T01:58:59.134Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-20T01:58:59.134Z] GC before operation: completed in 133.789 ms, heap usage 139.537 MB -> 51.772 MB.
[2025-02-20T01:59:01.629Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:59:05.121Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:59:08.561Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:59:11.991Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:59:13.589Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:59:15.186Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:59:18.611Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:59:20.206Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:59:20.981Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:59:20.981Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:59:20.981Z] Movies recommended for you:
[2025-02-20T01:59:20.981Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:59:20.981Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:59:20.981Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (21946.611 ms) ======
[2025-02-20T01:59:20.981Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-20T01:59:20.981Z] GC before operation: completed in 121.009 ms, heap usage 209.991 MB -> 51.800 MB.
[2025-02-20T01:59:24.460Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:59:26.938Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:59:31.403Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:59:34.826Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:59:36.424Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:59:38.058Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:59:40.536Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:59:42.141Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:59:42.958Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:59:42.958Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:59:42.958Z] Movies recommended for you:
[2025-02-20T01:59:42.958Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:59:42.958Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:59:42.958Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21974.129 ms) ======
[2025-02-20T01:59:42.958Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-20T01:59:42.958Z] GC before operation: completed in 131.193 ms, heap usage 169.664 MB -> 51.911 MB.
[2025-02-20T01:59:46.408Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:59:49.423Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:59:53.908Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:59:56.384Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:59:58.867Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:00:00.455Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:00:03.881Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:00:05.488Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:00:05.488Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:00:05.488Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:00:06.257Z] Movies recommended for you:
[2025-02-20T02:00:06.257Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:00:06.257Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:00:06.257Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22823.620 ms) ======
[2025-02-20T02:00:06.257Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-20T02:00:06.257Z] GC before operation: completed in 146.813 ms, heap usage 123.694 MB -> 52.122 MB.
[2025-02-20T02:00:08.727Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:00:12.162Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:00:16.617Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:00:19.083Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:00:21.552Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:00:23.146Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:00:25.634Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:00:27.250Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:00:27.250Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:00:27.250Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:00:28.019Z] Movies recommended for you:
[2025-02-20T02:00:28.019Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:00:28.019Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:00:28.019Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21690.282 ms) ======
[2025-02-20T02:00:28.019Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-20T02:00:28.019Z] GC before operation: completed in 150.475 ms, heap usage 253.112 MB -> 52.029 MB.
[2025-02-20T02:00:31.458Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:00:33.931Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:00:39.536Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:00:42.973Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:00:44.569Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:00:46.171Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:00:48.674Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:00:50.262Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:00:50.262Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:00:50.262Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:00:51.034Z] Movies recommended for you:
[2025-02-20T02:00:51.034Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:00:51.034Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:00:51.034Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (22836.115 ms) ======
[2025-02-20T02:00:51.034Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-20T02:00:51.034Z] GC before operation: completed in 152.108 ms, heap usage 137.960 MB -> 52.090 MB.
[2025-02-20T02:00:53.535Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:00:56.962Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:01:01.437Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:01:03.917Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:01:05.523Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:01:07.482Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:01:09.953Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:01:12.434Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:01:12.434Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:01:12.434Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:01:12.434Z] Movies recommended for you:
[2025-02-20T02:01:12.434Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:01:12.434Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:01:12.434Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (21594.724 ms) ======
[2025-02-20T02:01:12.434Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-20T02:01:12.434Z] GC before operation: completed in 145.009 ms, heap usage 424.069 MB -> 51.995 MB.
[2025-02-20T02:01:15.909Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:01:18.393Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:01:28.340Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:01:30.834Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:01:34.380Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:01:34.380Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:01:37.825Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:01:40.333Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:01:40.333Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:01:40.333Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:01:40.333Z] Movies recommended for you:
[2025-02-20T02:01:40.333Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:01:40.333Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:01:40.333Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (27687.028 ms) ======
[2025-02-20T02:01:40.333Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-20T02:01:40.333Z] GC before operation: completed in 145.505 ms, heap usage 277.352 MB -> 52.055 MB.
[2025-02-20T02:01:43.760Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:01:46.231Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:01:50.701Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:01:54.127Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:01:55.723Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:01:57.311Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:02:00.770Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:02:02.363Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:02:03.138Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:02:03.138Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:02:03.138Z] Movies recommended for you:
[2025-02-20T02:02:03.138Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:02:03.138Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:02:03.138Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22671.398 ms) ======
[2025-02-20T02:02:03.138Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-20T02:02:03.138Z] GC before operation: completed in 158.697 ms, heap usage 178.934 MB -> 52.224 MB.
[2025-02-20T02:02:06.574Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:02:09.181Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:02:13.679Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:02:16.176Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:02:17.781Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:02:20.249Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:02:21.843Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:02:23.442Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:02:24.212Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:02:24.212Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:02:24.212Z] Movies recommended for you:
[2025-02-20T02:02:24.212Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:02:24.212Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:02:24.212Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20923.173 ms) ======
[2025-02-20T02:02:24.212Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-20T02:02:24.212Z] GC before operation: completed in 117.409 ms, heap usage 320.005 MB -> 51.994 MB.
[2025-02-20T02:02:27.641Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:02:31.063Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:02:39.340Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:02:41.825Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:02:43.417Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:02:45.005Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:02:47.493Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:02:49.099Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:02:49.099Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:02:49.099Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:02:49.099Z] Movies recommended for you:
[2025-02-20T02:02:49.099Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:02:49.099Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:02:49.099Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (25001.449 ms) ======
[2025-02-20T02:02:49.099Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-20T02:02:49.099Z] GC before operation: completed in 138.835 ms, heap usage 400.990 MB -> 52.281 MB.
[2025-02-20T02:02:52.562Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:02:55.220Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:03:01.893Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:03:01.893Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:03:04.369Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:03:05.968Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:03:07.556Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:03:10.036Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:03:10.036Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:03:10.036Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:03:10.036Z] Movies recommended for you:
[2025-02-20T02:03:10.036Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:03:10.036Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:03:10.036Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20795.029 ms) ======
[2025-02-20T02:03:10.036Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-20T02:03:10.036Z] GC before operation: completed in 143.791 ms, heap usage 838.666 MB -> 56.184 MB.
[2025-02-20T02:03:13.484Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:03:16.328Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:03:20.811Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:03:23.278Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:03:24.866Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:03:27.337Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:03:28.927Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:03:30.531Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:03:31.388Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:03:31.388Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:03:31.388Z] Movies recommended for you:
[2025-02-20T02:03:31.388Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:03:31.388Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:03:31.388Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20697.178 ms) ======
[2025-02-20T02:03:31.388Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-20T02:03:31.388Z] GC before operation: completed in 160.332 ms, heap usage 785.744 MB -> 55.825 MB.
[2025-02-20T02:03:33.897Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:03:37.330Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:03:45.622Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:03:47.218Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:03:49.703Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:03:51.294Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:03:53.786Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:03:55.382Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:03:56.152Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:03:56.152Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:03:56.152Z] Movies recommended for you:
[2025-02-20T02:03:56.152Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:03:56.152Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:03:56.152Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (24684.779 ms) ======
[2025-02-20T02:03:56.152Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-20T02:03:56.152Z] GC before operation: completed in 144.907 ms, heap usage 460.772 MB -> 52.257 MB.
[2025-02-20T02:03:59.578Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:04:03.001Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:04:06.440Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:04:09.864Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:04:11.489Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:04:13.115Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:04:16.558Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:04:18.177Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:04:18.177Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:04:18.177Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:04:18.177Z] Movies recommended for you:
[2025-02-20T02:04:18.177Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:04:18.177Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:04:18.177Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22215.521 ms) ======
[2025-02-20T02:04:18.177Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-20T02:04:18.177Z] GC before operation: completed in 141.853 ms, heap usage 296.628 MB -> 55.570 MB.
[2025-02-20T02:04:21.601Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T02:04:25.027Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T02:04:29.674Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T02:04:32.315Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T02:04:33.922Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T02:04:36.430Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T02:04:38.030Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T02:04:39.645Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T02:04:40.424Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T02:04:40.424Z] The best model improves the baseline by 14.43%.
[2025-02-20T02:04:40.424Z] Movies recommended for you:
[2025-02-20T02:04:40.424Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T02:04:40.424Z] There is no way to check that no silent failure occurred.
[2025-02-20T02:04:40.424Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (22018.956 ms) ======
[2025-02-20T02:04:41.193Z] -----------------------------------
[2025-02-20T02:04:41.193Z] renaissance-movie-lens_0_PASSED
[2025-02-20T02:04:41.193Z] -----------------------------------
[2025-02-20T02:04:41.193Z]
[2025-02-20T02:04:41.193Z] TEST TEARDOWN:
[2025-02-20T02:04:41.193Z] Nothing to be done for teardown.
[2025-02-20T02:04:41.193Z] renaissance-movie-lens_0 Finish Time: Thu Feb 20 02:04:40 2025 Epoch Time (ms): 1740017080579