renaissance-movie-lens_0
[2024-08-09T21:08:37.011Z] Running test renaissance-movie-lens_0 ...
[2024-08-09T21:08:37.011Z] ===============================================
[2024-08-09T21:08:37.011Z] renaissance-movie-lens_0 Start Time: Fri Aug 9 21:08:36 2024 Epoch Time (ms): 1723237716341
[2024-08-09T21:08:37.011Z] variation: NoOptions
[2024-08-09T21:08:37.011Z] JVM_OPTIONS:
[2024-08-09T21:08:37.011Z] { \
[2024-08-09T21:08:37.011Z] echo ""; echo "TEST SETUP:"; \
[2024-08-09T21:08:37.011Z] echo "Nothing to be done for setup."; \
[2024-08-09T21:08:37.011Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232366558997/renaissance-movie-lens_0"; \
[2024-08-09T21:08:37.011Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232366558997/renaissance-movie-lens_0"; \
[2024-08-09T21:08:37.012Z] echo ""; echo "TESTING:"; \
[2024-08-09T21:08:37.012Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232366558997/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-09T21:08:37.012Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232366558997/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-09T21:08:37.012Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-09T21:08:37.012Z] echo "Nothing to be done for teardown."; \
[2024-08-09T21:08:37.012Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232366558997/TestTargetResult";
[2024-08-09T21:08:37.012Z]
[2024-08-09T21:08:37.012Z] TEST SETUP:
[2024-08-09T21:08:37.012Z] Nothing to be done for setup.
[2024-08-09T21:08:37.012Z]
[2024-08-09T21:08:37.012Z] TESTING:
[2024-08-09T21:08:41.161Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-09T21:08:45.298Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-09T21:08:50.734Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-09T21:08:51.683Z] Training: 60056, validation: 20285, test: 19854
[2024-08-09T21:08:51.683Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-09T21:08:51.683Z] GC before operation: completed in 88.269 ms, heap usage 160.480 MB -> 39.535 MB.
[2024-08-09T21:09:03.160Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:09:08.510Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:09:13.866Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:09:18.006Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:09:21.014Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:09:24.020Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:09:25.970Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:09:29.712Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:09:29.712Z] 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.
[2024-08-09T21:09:29.712Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:09:29.712Z] Movies recommended for you:
[2024-08-09T21:09:29.712Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:09:29.712Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:09:29.712Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (37854.261 ms) ======
[2024-08-09T21:09:29.712Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-09T21:09:29.712Z] GC before operation: completed in 142.452 ms, heap usage 464.739 MB -> 56.027 MB.
[2024-08-09T21:09:33.858Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:09:37.994Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:09:40.996Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:09:43.999Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:09:45.944Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:09:48.945Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:09:50.892Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:09:52.836Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:09:53.787Z] 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.
[2024-08-09T21:09:53.787Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:09:53.787Z] Movies recommended for you:
[2024-08-09T21:09:53.787Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:09:53.787Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:09:53.787Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24073.954 ms) ======
[2024-08-09T21:09:53.787Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-09T21:09:53.787Z] GC before operation: completed in 117.644 ms, heap usage 638.586 MB -> 57.991 MB.
[2024-08-09T21:09:57.920Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:10:00.926Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:10:06.279Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:10:09.283Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:10:11.229Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:10:13.174Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:10:15.125Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:10:17.075Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:10:17.075Z] 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.
[2024-08-09T21:10:17.075Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:10:17.075Z] Movies recommended for you:
[2024-08-09T21:10:17.075Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:10:17.075Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:10:17.075Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23550.530 ms) ======
[2024-08-09T21:10:17.075Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-09T21:10:17.075Z] GC before operation: completed in 194.900 ms, heap usage 1.818 GB -> 59.779 MB.
[2024-08-09T21:10:21.215Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:10:24.231Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:10:28.375Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:10:31.377Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:10:35.116Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:10:36.066Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:10:38.014Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:10:39.960Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:10:40.908Z] 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.
[2024-08-09T21:10:40.908Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:10:40.908Z] Movies recommended for you:
[2024-08-09T21:10:40.908Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:10:40.908Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:10:40.908Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23570.256 ms) ======
[2024-08-09T21:10:40.908Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-09T21:10:40.908Z] GC before operation: completed in 126.956 ms, heap usage 140.777 MB -> 57.453 MB.
[2024-08-09T21:10:43.925Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:10:48.063Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:10:51.067Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:10:55.202Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:10:57.151Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:10:59.098Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:11:01.221Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:11:03.172Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:11:03.172Z] 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.
[2024-08-09T21:11:03.172Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:11:04.122Z] Movies recommended for you:
[2024-08-09T21:11:04.122Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:11:04.122Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:11:04.122Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22537.667 ms) ======
[2024-08-09T21:11:04.122Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-09T21:11:04.122Z] GC before operation: completed in 132.717 ms, heap usage 1.046 GB -> 61.694 MB.
[2024-08-09T21:11:07.129Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:11:11.273Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:11:14.285Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:11:17.300Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:11:19.261Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:11:21.212Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:11:23.159Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:11:26.166Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:11:27.113Z] 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.
[2024-08-09T21:11:27.113Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:11:28.060Z] Movies recommended for you:
[2024-08-09T21:11:28.060Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:11:28.060Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:11:28.060Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (23825.052 ms) ======
[2024-08-09T21:11:28.060Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-09T21:11:28.060Z] GC before operation: completed in 202.700 ms, heap usage 977.396 MB -> 63.010 MB.
[2024-08-09T21:11:31.064Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:11:35.220Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:11:38.227Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:11:41.646Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:11:43.600Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:11:44.550Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:11:46.524Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:11:48.529Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:11:48.529Z] 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.
[2024-08-09T21:11:49.488Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:11:49.488Z] Movies recommended for you:
[2024-08-09T21:11:49.488Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:11:49.488Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:11:49.489Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21300.170 ms) ======
[2024-08-09T21:11:49.489Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-09T21:11:49.489Z] GC before operation: completed in 121.635 ms, heap usage 111.452 MB -> 56.606 MB.
[2024-08-09T21:11:52.496Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:11:55.517Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:11:58.662Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:12:01.669Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:12:03.615Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:12:05.572Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:12:07.518Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:12:10.522Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:12:10.522Z] 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.
[2024-08-09T21:12:10.522Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:12:10.522Z] Movies recommended for you:
[2024-08-09T21:12:10.522Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:12:10.522Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:12:10.522Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21440.186 ms) ======
[2024-08-09T21:12:10.522Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-09T21:12:10.522Z] GC before operation: completed in 126.792 ms, heap usage 514.710 MB -> 58.991 MB.
[2024-08-09T21:12:14.662Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:12:17.671Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:12:21.807Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:12:25.962Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:12:27.908Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:12:29.856Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:12:31.803Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:12:33.748Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:12:33.748Z] 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.
[2024-08-09T21:12:33.748Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:12:34.695Z] Movies recommended for you:
[2024-08-09T21:12:34.695Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:12:34.695Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:12:34.695Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (23396.236 ms) ======
[2024-08-09T21:12:34.695Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-09T21:12:34.695Z] GC before operation: completed in 140.169 ms, heap usage 823.567 MB -> 63.849 MB.
[2024-08-09T21:12:37.765Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:12:40.767Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:12:43.767Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:12:47.509Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:12:49.460Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:12:51.405Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:12:52.353Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:12:54.307Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:12:55.256Z] 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.
[2024-08-09T21:12:55.256Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:12:55.256Z] Movies recommended for you:
[2024-08-09T21:12:55.256Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:12:55.256Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:12:55.256Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20835.765 ms) ======
[2024-08-09T21:12:55.256Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-09T21:12:55.256Z] GC before operation: completed in 136.622 ms, heap usage 971.914 MB -> 61.358 MB.
[2024-08-09T21:12:59.399Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:13:02.404Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:13:05.413Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:13:08.421Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:13:10.377Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:13:12.323Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:13:14.275Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:13:16.227Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:13:17.179Z] 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.
[2024-08-09T21:13:17.179Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:13:17.179Z] Movies recommended for you:
[2024-08-09T21:13:17.179Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:13:17.179Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:13:17.179Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (21608.474 ms) ======
[2024-08-09T21:13:17.179Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-09T21:13:17.179Z] GC before operation: completed in 139.076 ms, heap usage 1.846 GB -> 64.884 MB.
[2024-08-09T21:13:20.184Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:13:24.325Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:13:27.334Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:13:30.354Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:13:32.327Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:13:34.275Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:13:35.226Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:13:37.177Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:13:38.131Z] 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.
[2024-08-09T21:13:38.131Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:13:38.131Z] Movies recommended for you:
[2024-08-09T21:13:38.131Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:13:38.131Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:13:38.131Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20910.355 ms) ======
[2024-08-09T21:13:38.131Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-09T21:13:38.131Z] GC before operation: completed in 155.774 ms, heap usage 1.772 GB -> 64.468 MB.
[2024-08-09T21:13:41.156Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:13:45.295Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:13:48.995Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:13:50.947Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:13:53.958Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:13:55.908Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:13:57.860Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:13:59.819Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:13:59.819Z] 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.
[2024-08-09T21:13:59.819Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:13:59.819Z] Movies recommended for you:
[2024-08-09T21:13:59.819Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:13:59.819Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:13:59.819Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22062.183 ms) ======
[2024-08-09T21:13:59.819Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-09T21:14:00.773Z] GC before operation: completed in 138.882 ms, heap usage 1.780 GB -> 63.681 MB.
[2024-08-09T21:14:03.782Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:14:05.732Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:14:08.743Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:14:11.751Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:14:13.713Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:14:15.657Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:14:17.603Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:14:19.547Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:14:19.547Z] 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.
[2024-08-09T21:14:19.547Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:14:19.547Z] Movies recommended for you:
[2024-08-09T21:14:19.547Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:14:19.547Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:14:19.547Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19364.485 ms) ======
[2024-08-09T21:14:19.547Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-09T21:14:19.547Z] GC before operation: completed in 135.149 ms, heap usage 153.719 MB -> 56.508 MB.
[2024-08-09T21:14:23.722Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:14:27.862Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:14:30.878Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:14:33.924Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:14:35.937Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:14:37.883Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:14:39.827Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:14:40.775Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:14:41.723Z] 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.
[2024-08-09T21:14:41.723Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:14:41.723Z] Movies recommended for you:
[2024-08-09T21:14:41.723Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:14:41.723Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:14:41.723Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (22023.589 ms) ======
[2024-08-09T21:14:41.723Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-09T21:14:41.723Z] GC before operation: completed in 142.014 ms, heap usage 510.603 MB -> 57.601 MB.
[2024-08-09T21:14:45.861Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:14:47.810Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:14:50.909Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:14:54.354Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:14:55.302Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:14:57.253Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:14:59.197Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:15:01.145Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:15:01.145Z] 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.
[2024-08-09T21:15:01.145Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:15:02.093Z] Movies recommended for you:
[2024-08-09T21:15:02.093Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:15:02.093Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:15:02.093Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19659.434 ms) ======
[2024-08-09T21:15:02.093Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-09T21:15:02.093Z] GC before operation: completed in 138.720 ms, heap usage 262.836 MB -> 55.620 MB.
[2024-08-09T21:15:06.233Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:15:09.247Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:15:12.248Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:15:15.250Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:15:17.200Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:15:19.149Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:15:21.095Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:15:22.041Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:15:22.990Z] 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.
[2024-08-09T21:15:22.990Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:15:22.990Z] Movies recommended for you:
[2024-08-09T21:15:22.990Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:15:22.990Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:15:22.990Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (21128.300 ms) ======
[2024-08-09T21:15:22.990Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-09T21:15:22.990Z] GC before operation: completed in 136.784 ms, heap usage 472.507 MB -> 58.068 MB.
[2024-08-09T21:15:25.991Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:15:30.119Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:15:33.122Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:15:36.124Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:15:37.073Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:15:39.019Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:15:40.967Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:15:42.912Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:15:42.912Z] 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.
[2024-08-09T21:15:42.912Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:15:42.912Z] Movies recommended for you:
[2024-08-09T21:15:42.912Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:15:42.912Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:15:42.912Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19808.035 ms) ======
[2024-08-09T21:15:42.912Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-09T21:15:42.912Z] GC before operation: completed in 137.261 ms, heap usage 1.009 GB -> 63.121 MB.
[2024-08-09T21:15:45.921Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:15:48.927Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:15:51.936Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:15:55.031Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:15:57.509Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:15:58.673Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:16:00.799Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:16:02.749Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:16:02.749Z] 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.
[2024-08-09T21:16:02.749Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:16:02.749Z] Movies recommended for you:
[2024-08-09T21:16:02.749Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:16:02.749Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:16:02.749Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19826.008 ms) ======
[2024-08-09T21:16:02.749Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-09T21:16:02.749Z] GC before operation: completed in 152.767 ms, heap usage 1.831 GB -> 62.494 MB.
[2024-08-09T21:16:05.767Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T21:16:08.771Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T21:16:11.776Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T21:16:14.798Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T21:16:16.747Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T21:16:17.696Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T21:16:19.647Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T21:16:21.598Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T21:16:21.598Z] 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.
[2024-08-09T21:16:21.598Z] The best model improves the baseline by 14.43%.
[2024-08-09T21:16:22.549Z] Movies recommended for you:
[2024-08-09T21:16:22.549Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T21:16:22.549Z] There is no way to check that no silent failure occurred.
[2024-08-09T21:16:22.549Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19134.214 ms) ======
[2024-08-09T21:16:24.496Z] -----------------------------------
[2024-08-09T21:16:24.496Z] renaissance-movie-lens_0_PASSED
[2024-08-09T21:16:24.496Z] -----------------------------------
[2024-08-09T21:16:24.496Z]
[2024-08-09T21:16:24.496Z] TEST TEARDOWN:
[2024-08-09T21:16:24.496Z] Nothing to be done for teardown.
[2024-08-09T21:16:24.496Z] renaissance-movie-lens_0 Finish Time: Fri Aug 9 21:16:23 2024 Epoch Time (ms): 1723238183976