renaissance-movie-lens_0
[2024-08-28T21:44:11.638Z] Running test renaissance-movie-lens_0 ...
[2024-08-28T21:44:11.638Z] ===============================================
[2024-08-28T21:44:11.638Z] renaissance-movie-lens_0 Start Time: Wed Aug 28 21:44:10 2024 Epoch Time (ms): 1724881450577
[2024-08-28T21:44:11.638Z] variation: NoOptions
[2024-08-28T21:44:11.638Z] JVM_OPTIONS:
[2024-08-28T21:44:11.638Z] { \
[2024-08-28T21:44:11.638Z] echo ""; echo "TEST SETUP:"; \
[2024-08-28T21:44:11.638Z] echo "Nothing to be done for setup."; \
[2024-08-28T21:44:11.638Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17248807774153/renaissance-movie-lens_0"; \
[2024-08-28T21:44:11.638Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17248807774153/renaissance-movie-lens_0"; \
[2024-08-28T21:44:11.638Z] echo ""; echo "TESTING:"; \
[2024-08-28T21:44:11.638Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_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_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17248807774153/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-28T21:44:11.638Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17248807774153/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-28T21:44:11.638Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-28T21:44:11.638Z] echo "Nothing to be done for teardown."; \
[2024-08-28T21:44:11.638Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17248807774153/TestTargetResult";
[2024-08-28T21:44:11.638Z]
[2024-08-28T21:44:11.638Z] TEST SETUP:
[2024-08-28T21:44:11.638Z] Nothing to be done for setup.
[2024-08-28T21:44:11.638Z]
[2024-08-28T21:44:11.638Z] TESTING:
[2024-08-28T21:44:13.555Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-28T21:44:15.472Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-28T21:44:18.436Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-28T21:44:18.436Z] Training: 60056, validation: 20285, test: 19854
[2024-08-28T21:44:18.436Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-28T21:44:18.436Z] GC before operation: completed in 61.493 ms, heap usage 233.028 MB -> 37.209 MB.
[2024-08-28T21:44:23.850Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:44:26.813Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:44:29.778Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:44:31.824Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:44:32.758Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:44:34.677Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:44:35.613Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:44:37.531Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:44:37.531Z] 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.
[2024-08-28T21:44:37.531Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:44:37.531Z] Movies recommended for you:
[2024-08-28T21:44:37.531Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:44:37.531Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:44:37.531Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (18647.919 ms) ======
[2024-08-28T21:44:37.531Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-28T21:44:37.531Z] GC before operation: completed in 122.004 ms, heap usage 256.196 MB -> 50.584 MB.
[2024-08-28T21:44:39.451Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:44:41.373Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:44:44.337Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:44:46.258Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:44:47.192Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:44:48.128Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:44:49.510Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:44:50.453Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:44:51.387Z] 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.
[2024-08-28T21:44:51.387Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:44:51.387Z] Movies recommended for you:
[2024-08-28T21:44:51.387Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:44:51.387Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:44:51.387Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (13461.389 ms) ======
[2024-08-28T21:44:51.387Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-28T21:44:51.387Z] GC before operation: completed in 114.130 ms, heap usage 407.661 MB -> 51.094 MB.
[2024-08-28T21:44:53.306Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:44:55.230Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:44:57.151Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:44:59.069Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:45:00.005Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:45:00.942Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:45:02.863Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:45:03.797Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:45:03.797Z] 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.
[2024-08-28T21:45:03.798Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:45:03.798Z] Movies recommended for you:
[2024-08-28T21:45:03.798Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:45:03.798Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:45:03.798Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (12703.850 ms) ======
[2024-08-28T21:45:03.798Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-28T21:45:03.798Z] GC before operation: completed in 110.657 ms, heap usage 249.488 MB -> 51.394 MB.
[2024-08-28T21:45:05.716Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:45:07.637Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:45:09.556Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:45:11.546Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:45:12.480Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:45:13.415Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:45:14.354Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:45:15.289Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:45:15.289Z] 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.
[2024-08-28T21:45:15.289Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:45:15.289Z] Movies recommended for you:
[2024-08-28T21:45:15.289Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:45:15.289Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:45:15.289Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (11756.243 ms) ======
[2024-08-28T21:45:15.289Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-28T21:45:16.223Z] GC before operation: completed in 107.489 ms, heap usage 334.539 MB -> 51.822 MB.
[2024-08-28T21:45:18.141Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:45:19.076Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:45:21.108Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:45:23.026Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:45:23.960Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:45:24.894Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:45:25.835Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:45:26.768Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:45:27.703Z] 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.
[2024-08-28T21:45:27.703Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:45:27.703Z] Movies recommended for you:
[2024-08-28T21:45:27.703Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:45:27.703Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:45:27.703Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (11579.029 ms) ======
[2024-08-28T21:45:27.703Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-28T21:45:27.703Z] GC before operation: completed in 116.387 ms, heap usage 256.873 MB -> 51.947 MB.
[2024-08-28T21:45:29.624Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:45:31.643Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:45:33.562Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:45:34.496Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:45:35.431Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:45:37.357Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:45:38.292Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:45:39.226Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:45:39.226Z] 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.
[2024-08-28T21:45:39.226Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:45:39.226Z] Movies recommended for you:
[2024-08-28T21:45:39.226Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:45:39.226Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:45:39.226Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (11861.704 ms) ======
[2024-08-28T21:45:39.226Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-28T21:45:39.226Z] GC before operation: completed in 109.340 ms, heap usage 274.749 MB -> 51.799 MB.
[2024-08-28T21:45:41.145Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:45:43.066Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:45:44.986Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:45:46.904Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:45:47.839Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:45:48.776Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:45:49.715Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:45:50.651Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:45:50.651Z] 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.
[2024-08-28T21:45:50.651Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:45:50.651Z] Movies recommended for you:
[2024-08-28T21:45:50.651Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:45:50.651Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:45:50.651Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (11529.827 ms) ======
[2024-08-28T21:45:50.651Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-28T21:45:51.585Z] GC before operation: completed in 111.585 ms, heap usage 187.359 MB -> 51.930 MB.
[2024-08-28T21:45:52.534Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:45:54.451Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:45:56.369Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:45:58.285Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:45:59.218Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:46:00.152Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:46:01.090Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:46:02.024Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:46:02.024Z] 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.
[2024-08-28T21:46:02.024Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:46:02.958Z] Movies recommended for you:
[2024-08-28T21:46:02.958Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:46:02.958Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:46:02.958Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (11377.090 ms) ======
[2024-08-28T21:46:02.958Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-28T21:46:02.958Z] GC before operation: completed in 110.950 ms, heap usage 233.780 MB -> 52.261 MB.
[2024-08-28T21:46:04.875Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:46:05.810Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:46:07.728Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:46:09.646Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:46:10.580Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:46:11.515Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:46:12.449Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:46:13.381Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:46:14.315Z] 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.
[2024-08-28T21:46:14.315Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:46:14.315Z] Movies recommended for you:
[2024-08-28T21:46:14.315Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:46:14.315Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:46:14.315Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11346.643 ms) ======
[2024-08-28T21:46:14.315Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-28T21:46:14.315Z] GC before operation: completed in 110.940 ms, heap usage 254.734 MB -> 52.084 MB.
[2024-08-28T21:46:16.232Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:46:18.149Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:46:19.083Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:46:20.999Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:46:21.932Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:46:22.865Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:46:24.664Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:46:25.598Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:46:25.598Z] 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.
[2024-08-28T21:46:25.598Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:46:25.598Z] Movies recommended for you:
[2024-08-28T21:46:25.598Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:46:25.598Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:46:25.598Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11386.436 ms) ======
[2024-08-28T21:46:25.598Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-28T21:46:25.598Z] GC before operation: completed in 120.759 ms, heap usage 331.388 MB -> 52.287 MB.
[2024-08-28T21:46:27.516Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:46:29.437Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:46:30.370Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:46:32.289Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:46:33.318Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:46:34.259Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:46:36.179Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:46:37.114Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:46:37.114Z] 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.
[2024-08-28T21:46:37.114Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:46:37.114Z] Movies recommended for you:
[2024-08-28T21:46:37.114Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:46:37.114Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:46:37.114Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11395.235 ms) ======
[2024-08-28T21:46:37.114Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-28T21:46:37.114Z] GC before operation: completed in 130.767 ms, heap usage 547.159 MB -> 55.396 MB.
[2024-08-28T21:46:39.035Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:46:40.954Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:46:41.888Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:46:43.809Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:46:44.748Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:46:45.682Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:46:47.602Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:46:48.535Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:46:48.535Z] 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.
[2024-08-28T21:46:48.535Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:46:48.535Z] Movies recommended for you:
[2024-08-28T21:46:48.535Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:46:48.535Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:46:48.535Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11251.917 ms) ======
[2024-08-28T21:46:48.535Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-28T21:46:48.535Z] GC before operation: completed in 116.321 ms, heap usage 204.137 MB -> 52.165 MB.
[2024-08-28T21:46:50.458Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:46:52.375Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:46:54.293Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:46:55.226Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:46:56.161Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:46:58.080Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:46:59.013Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:46:59.946Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:46:59.946Z] 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.
[2024-08-28T21:46:59.946Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:46:59.946Z] Movies recommended for you:
[2024-08-28T21:46:59.946Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:46:59.946Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:46:59.946Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11546.373 ms) ======
[2024-08-28T21:46:59.946Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-28T21:46:59.946Z] GC before operation: completed in 117.219 ms, heap usage 76.988 MB -> 54.796 MB.
[2024-08-28T21:47:01.863Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:47:03.780Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:47:05.698Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:47:06.632Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:47:08.550Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:47:09.484Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:47:10.419Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:47:11.357Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:47:11.357Z] 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.
[2024-08-28T21:47:11.357Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:47:11.357Z] Movies recommended for you:
[2024-08-28T21:47:11.357Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:47:11.357Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:47:11.357Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11487.695 ms) ======
[2024-08-28T21:47:11.357Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-28T21:47:11.357Z] GC before operation: completed in 115.379 ms, heap usage 206.186 MB -> 52.004 MB.
[2024-08-28T21:47:13.288Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:47:15.206Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:47:17.129Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:47:19.046Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:47:19.983Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:47:20.917Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:47:21.850Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:47:22.812Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:47:22.812Z] 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.
[2024-08-28T21:47:22.812Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:47:22.812Z] Movies recommended for you:
[2024-08-28T21:47:22.812Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:47:22.812Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:47:22.812Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11329.958 ms) ======
[2024-08-28T21:47:22.812Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-28T21:47:22.812Z] GC before operation: completed in 129.528 ms, heap usage 210.250 MB -> 52.215 MB.
[2024-08-28T21:47:24.733Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:47:26.652Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:47:28.572Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:47:30.657Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:47:31.589Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:47:32.523Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:47:33.457Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:47:34.392Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:47:34.392Z] 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.
[2024-08-28T21:47:34.392Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:47:34.392Z] Movies recommended for you:
[2024-08-28T21:47:34.392Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:47:34.392Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:47:34.392Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11446.797 ms) ======
[2024-08-28T21:47:34.392Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-28T21:47:34.392Z] GC before operation: completed in 129.019 ms, heap usage 167.085 MB -> 52.228 MB.
[2024-08-28T21:47:36.308Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:47:38.226Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:47:40.148Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:47:42.072Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:47:43.008Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:47:43.943Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:47:44.876Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:47:45.810Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:47:45.810Z] 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.
[2024-08-28T21:47:45.810Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:47:45.810Z] Movies recommended for you:
[2024-08-28T21:47:45.810Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:47:45.810Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:47:45.810Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (11225.012 ms) ======
[2024-08-28T21:47:45.810Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-28T21:47:45.810Z] GC before operation: completed in 121.944 ms, heap usage 166.671 MB -> 55.296 MB.
[2024-08-28T21:47:47.727Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:47:49.648Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:47:51.573Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:47:54.549Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:47:56.476Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:47:58.280Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:47:59.219Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:48:01.318Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:48:01.318Z] 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.
[2024-08-28T21:48:01.318Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:48:01.318Z] Movies recommended for you:
[2024-08-28T21:48:01.318Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:48:01.318Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:48:01.318Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15526.783 ms) ======
[2024-08-28T21:48:01.318Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-28T21:48:02.252Z] GC before operation: completed in 136.095 ms, heap usage 222.125 MB -> 52.096 MB.
[2024-08-28T21:48:04.179Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:48:07.156Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:48:09.085Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:48:12.062Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:48:12.997Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:48:14.955Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:48:16.898Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:48:18.888Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:48:18.888Z] 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.
[2024-08-28T21:48:18.888Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:48:18.888Z] Movies recommended for you:
[2024-08-28T21:48:18.888Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:48:18.888Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:48:18.888Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17497.400 ms) ======
[2024-08-28T21:48:18.888Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-28T21:48:19.825Z] GC before operation: completed in 128.953 ms, heap usage 352.044 MB -> 52.338 MB.
[2024-08-28T21:48:21.751Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:48:24.722Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:48:26.646Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:48:29.623Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:48:30.631Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:48:32.555Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:48:34.476Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:48:36.395Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:48:36.395Z] 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.
[2024-08-28T21:48:36.395Z] The best model improves the baseline by 14.43%.
[2024-08-28T21:48:36.395Z] Movies recommended for you:
[2024-08-28T21:48:36.395Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:48:36.395Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:48:36.395Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17067.108 ms) ======
[2024-08-28T21:48:38.319Z] -----------------------------------
[2024-08-28T21:48:38.319Z] renaissance-movie-lens_0_PASSED
[2024-08-28T21:48:38.319Z] -----------------------------------
[2024-08-28T21:48:38.319Z]
[2024-08-28T21:48:38.319Z] TEST TEARDOWN:
[2024-08-28T21:48:38.319Z] Nothing to be done for teardown.
[2024-08-28T21:48:38.319Z] renaissance-movie-lens_0 Finish Time: Wed Aug 28 21:48:37 2024 Epoch Time (ms): 1724881717533