renaissance-movie-lens_0
[2025-02-20T03:57:00.642Z] Running test renaissance-movie-lens_0 ...
[2025-02-20T03:57:00.642Z] ===============================================
[2025-02-20T03:57:00.642Z] renaissance-movie-lens_0 Start Time: Wed Feb 19 21:57:00 2025 Epoch Time (ms): 1740023820544
[2025-02-20T03:57:00.642Z] variation: NoOptions
[2025-02-20T03:57:00.642Z] JVM_OPTIONS:
[2025-02-20T03:57:00.642Z] { \
[2025-02-20T03:57:00.642Z] echo ""; echo "TEST SETUP:"; \
[2025-02-20T03:57:00.642Z] echo "Nothing to be done for setup."; \
[2025-02-20T03:57:00.642Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400229474543/renaissance-movie-lens_0"; \
[2025-02-20T03:57:00.642Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400229474543/renaissance-movie-lens_0"; \
[2025-02-20T03:57:00.642Z] echo ""; echo "TESTING:"; \
[2025-02-20T03:57:00.642Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400229474543/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-20T03:57:00.642Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400229474543/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-20T03:57:00.642Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-20T03:57:00.642Z] echo "Nothing to be done for teardown."; \
[2025-02-20T03:57:00.642Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400229474543/TestTargetResult";
[2025-02-20T03:57:00.642Z]
[2025-02-20T03:57:00.642Z] TEST SETUP:
[2025-02-20T03:57:00.642Z] Nothing to be done for setup.
[2025-02-20T03:57:00.642Z]
[2025-02-20T03:57:00.642Z] TESTING:
[2025-02-20T03:57:03.725Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-20T03:57:05.967Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-02-20T03:57:09.086Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-20T03:57:09.086Z] Training: 60056, validation: 20285, test: 19854
[2025-02-20T03:57:09.086Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-20T03:57:09.086Z] GC before operation: completed in 104.013 ms, heap usage 141.067 MB -> 37.204 MB.
[2025-02-20T03:57:16.864Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:57:20.965Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:57:24.076Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:57:27.199Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:57:29.552Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:57:30.979Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:57:32.407Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:57:34.639Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:57:34.639Z] 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.
[2025-02-20T03:57:34.639Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:57:35.329Z] Movies recommended for you:
[2025-02-20T03:57:35.329Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:57:35.329Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:57:35.329Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25940.988 ms) ======
[2025-02-20T03:57:35.329Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-20T03:57:35.329Z] GC before operation: completed in 127.271 ms, heap usage 157.814 MB -> 48.148 MB.
[2025-02-20T03:57:38.439Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:57:41.539Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:57:44.676Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:57:46.940Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:57:49.156Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:57:50.578Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:57:52.839Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:57:54.264Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:57:54.264Z] 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.
[2025-02-20T03:57:54.264Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:57:54.264Z] Movies recommended for you:
[2025-02-20T03:57:54.264Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:57:54.264Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:57:54.264Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19378.632 ms) ======
[2025-02-20T03:57:54.264Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-20T03:57:54.958Z] GC before operation: completed in 106.559 ms, heap usage 454.653 MB -> 51.102 MB.
[2025-02-20T03:57:57.191Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:58:01.264Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:58:03.537Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:58:06.681Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:58:08.108Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:58:09.551Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:58:10.977Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:58:13.672Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:58:13.672Z] 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.
[2025-02-20T03:58:13.672Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:58:13.672Z] Movies recommended for you:
[2025-02-20T03:58:13.672Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:58:13.672Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:58:13.672Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18550.294 ms) ======
[2025-02-20T03:58:13.672Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-20T03:58:13.672Z] GC before operation: completed in 107.457 ms, heap usage 387.015 MB -> 51.463 MB.
[2025-02-20T03:58:15.909Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:58:18.997Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:58:21.226Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:58:23.470Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:58:25.687Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:58:27.129Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:58:28.595Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:58:30.827Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:58:30.828Z] 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.
[2025-02-20T03:58:30.828Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:58:30.828Z] Movies recommended for you:
[2025-02-20T03:58:30.828Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:58:30.828Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:58:30.828Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17561.448 ms) ======
[2025-02-20T03:58:30.828Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-20T03:58:30.828Z] GC before operation: completed in 97.829 ms, heap usage 204.004 MB -> 51.737 MB.
[2025-02-20T03:58:33.928Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:58:36.160Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:58:38.406Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:58:40.623Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:58:42.870Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:58:44.334Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:58:45.769Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:58:47.215Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:58:47.215Z] 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.
[2025-02-20T03:58:47.902Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:58:47.902Z] Movies recommended for you:
[2025-02-20T03:58:47.902Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:58:47.902Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:58:47.902Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16699.524 ms) ======
[2025-02-20T03:58:47.902Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-20T03:58:47.902Z] GC before operation: completed in 111.590 ms, heap usage 188.675 MB -> 51.843 MB.
[2025-02-20T03:58:50.143Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:58:53.256Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:58:55.470Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:58:57.716Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:58:59.136Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:59:00.562Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:59:02.793Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:59:03.482Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:59:04.198Z] 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.
[2025-02-20T03:59:04.198Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:59:04.198Z] Movies recommended for you:
[2025-02-20T03:59:04.198Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:59:04.198Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:59:04.198Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16346.257 ms) ======
[2025-02-20T03:59:04.198Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-20T03:59:04.198Z] GC before operation: completed in 108.426 ms, heap usage 460.031 MB -> 51.931 MB.
[2025-02-20T03:59:06.895Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:59:09.130Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:59:12.245Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:59:14.472Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:59:15.910Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:59:17.355Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:59:18.789Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:59:20.228Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:59:20.914Z] 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.
[2025-02-20T03:59:20.914Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:59:20.914Z] Movies recommended for you:
[2025-02-20T03:59:20.914Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:59:20.914Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:59:20.914Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16558.269 ms) ======
[2025-02-20T03:59:20.914Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-20T03:59:20.914Z] GC before operation: completed in 103.267 ms, heap usage 200.247 MB -> 51.987 MB.
[2025-02-20T03:59:24.007Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:59:26.270Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:59:28.538Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:59:30.782Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:59:32.244Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:59:34.469Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:59:35.906Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:59:37.331Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:59:37.331Z] 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.
[2025-02-20T03:59:37.331Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:59:37.331Z] Movies recommended for you:
[2025-02-20T03:59:37.331Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:59:37.331Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:59:37.331Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16724.133 ms) ======
[2025-02-20T03:59:37.331Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-20T03:59:38.019Z] GC before operation: completed in 104.754 ms, heap usage 391.166 MB -> 52.369 MB.
[2025-02-20T03:59:40.265Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:59:42.501Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T03:59:45.608Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T03:59:47.851Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T03:59:49.277Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T03:59:50.701Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T03:59:52.155Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T03:59:53.588Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T03:59:53.588Z] 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.
[2025-02-20T03:59:53.588Z] The best model improves the baseline by 14.43%.
[2025-02-20T03:59:54.293Z] Movies recommended for you:
[2025-02-20T03:59:54.293Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T03:59:54.293Z] There is no way to check that no silent failure occurred.
[2025-02-20T03:59:54.293Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16269.766 ms) ======
[2025-02-20T03:59:54.293Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-20T03:59:54.293Z] GC before operation: completed in 107.264 ms, heap usage 66.669 MB -> 54.587 MB.
[2025-02-20T03:59:56.574Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T03:59:59.733Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:00:01.633Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:00:03.865Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:00:06.108Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:00:07.534Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:00:08.962Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:00:10.397Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:00:10.397Z] 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.
[2025-02-20T04:00:10.397Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:00:10.397Z] Movies recommended for you:
[2025-02-20T04:00:10.397Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:00:10.397Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:00:10.397Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16613.097 ms) ======
[2025-02-20T04:00:10.397Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-20T04:00:11.081Z] GC before operation: completed in 121.303 ms, heap usage 430.675 MB -> 52.334 MB.
[2025-02-20T04:00:13.303Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:00:16.402Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:00:18.644Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:00:20.875Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:00:22.296Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:00:23.715Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:00:25.176Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:00:26.615Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:00:26.615Z] 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.
[2025-02-20T04:00:26.615Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:00:26.615Z] Movies recommended for you:
[2025-02-20T04:00:26.615Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:00:26.615Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:00:26.615Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15942.456 ms) ======
[2025-02-20T04:00:26.615Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-20T04:00:26.615Z] GC before operation: completed in 108.112 ms, heap usage 369.479 MB -> 51.949 MB.
[2025-02-20T04:00:29.725Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:00:31.955Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:00:34.765Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:00:36.196Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:00:38.439Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:00:39.864Z] RMSE (validation) = 1.117495376637101 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:00:41.305Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:00:42.742Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:00:42.742Z] 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.
[2025-02-20T04:00:42.742Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:00:42.742Z] Movies recommended for you:
[2025-02-20T04:00:42.742Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:00:42.742Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:00:42.742Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16174.738 ms) ======
[2025-02-20T04:00:42.742Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-20T04:00:43.428Z] GC before operation: completed in 99.248 ms, heap usage 75.361 MB -> 54.387 MB.
[2025-02-20T04:00:45.673Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:00:48.764Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:00:51.080Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:00:53.298Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:00:54.728Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:00:56.388Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:00:57.809Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:00:59.247Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:00:59.945Z] 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.
[2025-02-20T04:00:59.945Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:00:59.945Z] Movies recommended for you:
[2025-02-20T04:00:59.945Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:00:59.945Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:00:59.945Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16606.284 ms) ======
[2025-02-20T04:00:59.945Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-20T04:00:59.945Z] GC before operation: completed in 95.566 ms, heap usage 222.790 MB -> 52.297 MB.
[2025-02-20T04:01:02.357Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:01:05.459Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:01:07.693Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:01:09.926Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:01:11.360Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:01:12.892Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:01:14.336Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:01:15.761Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:01:16.465Z] 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.
[2025-02-20T04:01:16.465Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:01:16.465Z] Movies recommended for you:
[2025-02-20T04:01:16.465Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:01:16.465Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:01:16.465Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16596.735 ms) ======
[2025-02-20T04:01:16.465Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-20T04:01:16.465Z] GC before operation: completed in 108.278 ms, heap usage 428.076 MB -> 52.119 MB.
[2025-02-20T04:01:19.561Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:01:21.786Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:01:24.028Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:01:26.299Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:01:27.734Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:01:29.178Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:01:30.629Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:01:32.074Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:01:32.768Z] 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.
[2025-02-20T04:01:32.768Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:01:32.768Z] Movies recommended for you:
[2025-02-20T04:01:32.768Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:01:32.768Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:01:32.768Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16093.786 ms) ======
[2025-02-20T04:01:32.768Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-20T04:01:32.768Z] GC before operation: completed in 134.151 ms, heap usage 348.751 MB -> 52.221 MB.
[2025-02-20T04:01:34.993Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:01:38.096Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:01:40.342Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:01:42.624Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:01:44.064Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:01:45.570Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:01:47.800Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:01:49.676Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:01:49.676Z] 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.
[2025-02-20T04:01:49.676Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:01:49.676Z] Movies recommended for you:
[2025-02-20T04:01:49.676Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:01:49.676Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:01:49.676Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16510.034 ms) ======
[2025-02-20T04:01:49.676Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-20T04:01:49.676Z] GC before operation: completed in 107.808 ms, heap usage 179.748 MB -> 52.243 MB.
[2025-02-20T04:01:51.906Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:01:55.048Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:01:57.335Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:01:59.585Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:02:01.030Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:02:02.461Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:02:04.690Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:02:06.196Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:02:06.196Z] 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.
[2025-02-20T04:02:06.196Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:02:06.196Z] Movies recommended for you:
[2025-02-20T04:02:06.196Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:02:06.196Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:02:06.196Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16829.120 ms) ======
[2025-02-20T04:02:06.196Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-20T04:02:06.196Z] GC before operation: completed in 133.554 ms, heap usage 139.239 MB -> 52.006 MB.
[2025-02-20T04:02:09.459Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:02:11.711Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:02:13.938Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:02:16.234Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:02:17.677Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:02:19.131Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:02:21.374Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:02:22.071Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:02:22.769Z] 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.
[2025-02-20T04:02:22.769Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:02:22.769Z] Movies recommended for you:
[2025-02-20T04:02:22.769Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:02:22.769Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:02:22.769Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16388.535 ms) ======
[2025-02-20T04:02:22.769Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-20T04:02:22.769Z] GC before operation: completed in 120.227 ms, heap usage 253.189 MB -> 52.119 MB.
[2025-02-20T04:02:25.079Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:02:27.328Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:02:30.545Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:02:32.776Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:02:34.230Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:02:36.108Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:02:37.593Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:02:39.019Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:02:39.019Z] 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.
[2025-02-20T04:02:39.019Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:02:39.019Z] Movies recommended for you:
[2025-02-20T04:02:39.019Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:02:39.019Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:02:39.019Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16368.130 ms) ======
[2025-02-20T04:02:39.019Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-20T04:02:39.715Z] GC before operation: completed in 101.701 ms, heap usage 234.048 MB -> 52.364 MB.
[2025-02-20T04:02:42.052Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T04:02:44.277Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T04:02:46.524Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T04:02:48.789Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T04:02:50.228Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T04:02:51.682Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T04:02:53.113Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T04:02:54.560Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T04:02:54.560Z] 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.
[2025-02-20T04:02:54.560Z] The best model improves the baseline by 14.43%.
[2025-02-20T04:02:55.246Z] Movies recommended for you:
[2025-02-20T04:02:55.246Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T04:02:55.246Z] There is no way to check that no silent failure occurred.
[2025-02-20T04:02:55.246Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15582.211 ms) ======
[2025-02-20T04:02:55.977Z] -----------------------------------
[2025-02-20T04:02:55.977Z] renaissance-movie-lens_0_PASSED
[2025-02-20T04:02:55.977Z] -----------------------------------
[2025-02-20T04:02:55.977Z]
[2025-02-20T04:02:55.977Z] TEST TEARDOWN:
[2025-02-20T04:02:55.977Z] Nothing to be done for teardown.
[2025-02-20T04:02:55.977Z] renaissance-movie-lens_0 Finish Time: Wed Feb 19 22:02:55 2025 Epoch Time (ms): 1740024175881