renaissance-movie-lens_0
[2025-02-20T01:25:45.955Z] Running test renaissance-movie-lens_0 ...
[2025-02-20T01:25:45.955Z] ===============================================
[2025-02-20T01:25:45.955Z] renaissance-movie-lens_0 Start Time: Wed Feb 19 19:25:46 2025 Epoch Time (ms): 1740014746115
[2025-02-20T01:25:45.955Z] variation: NoOptions
[2025-02-20T01:25:45.955Z] JVM_OPTIONS:
[2025-02-20T01:25:45.955Z] { \
[2025-02-20T01:25:45.955Z] echo ""; echo "TEST SETUP:"; \
[2025-02-20T01:25:45.955Z] echo "Nothing to be done for setup."; \
[2025-02-20T01:25:45.955Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400141304440/renaissance-movie-lens_0"; \
[2025-02-20T01:25:45.955Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400141304440/renaissance-movie-lens_0"; \
[2025-02-20T01:25:45.955Z] echo ""; echo "TESTING:"; \
[2025-02-20T01:25:45.955Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400141304440/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-20T01:25:45.955Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400141304440/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-20T01:25:45.955Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-20T01:25:45.955Z] echo "Nothing to be done for teardown."; \
[2025-02-20T01:25:45.955Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17400141304440/TestTargetResult";
[2025-02-20T01:25:45.955Z]
[2025-02-20T01:25:45.955Z] TEST SETUP:
[2025-02-20T01:25:45.955Z] Nothing to be done for setup.
[2025-02-20T01:25:45.955Z]
[2025-02-20T01:25:45.955Z] TESTING:
[2025-02-20T01:25:49.072Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-20T01:25:50.497Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-02-20T01:25:53.604Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-20T01:25:53.604Z] Training: 60056, validation: 20285, test: 19854
[2025-02-20T01:25:53.604Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-20T01:25:53.604Z] GC before operation: completed in 50.685 ms, heap usage 96.707 MB -> 37.641 MB.
[2025-02-20T01:25:59.985Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:26:04.073Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:26:07.228Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:26:09.451Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:26:10.896Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:26:12.329Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:26:14.556Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:26:15.997Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:26:16.714Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:26:16.714Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:26:16.714Z] Movies recommended for you:
[2025-02-20T01:26:16.714Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:26:16.714Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:26:16.714Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23111.044 ms) ======
[2025-02-20T01:26:16.714Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-20T01:26:16.714Z] GC before operation: completed in 117.099 ms, heap usage 470.726 MB -> 56.695 MB.
[2025-02-20T01:26:19.813Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:26:22.959Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:26:25.201Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:26:27.438Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:26:28.885Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:26:30.325Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:26:31.756Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:26:33.993Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:26:33.993Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:26:33.993Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:26:33.993Z] Movies recommended for you:
[2025-02-20T01:26:33.993Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:26:33.993Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:26:33.993Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17294.305 ms) ======
[2025-02-20T01:26:33.993Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-20T01:26:33.993Z] GC before operation: completed in 51.868 ms, heap usage 390.059 MB -> 51.588 MB.
[2025-02-20T01:26:37.123Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:26:39.358Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:26:41.598Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:26:43.834Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:26:45.341Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:26:48.374Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:26:49.073Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:26:50.514Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:26:50.514Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:26:50.514Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:26:50.514Z] Movies recommended for you:
[2025-02-20T01:26:50.514Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:26:50.514Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:26:50.514Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16498.615 ms) ======
[2025-02-20T01:26:50.514Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-20T01:26:50.514Z] GC before operation: completed in 51.067 ms, heap usage 411.839 MB -> 52.030 MB.
[2025-02-20T01:26:52.736Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:26:56.387Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:26:57.817Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:27:00.051Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:27:00.743Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:27:02.176Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:27:03.610Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:27:05.051Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:27:05.051Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:27:05.051Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:27:05.736Z] Movies recommended for you:
[2025-02-20T01:27:05.736Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:27:05.736Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:27:05.736Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14824.001 ms) ======
[2025-02-20T01:27:05.736Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-20T01:27:05.736Z] GC before operation: completed in 51.480 ms, heap usage 460.896 MB -> 55.799 MB.
[2025-02-20T01:27:07.970Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:27:10.196Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:27:12.462Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:27:13.906Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:27:15.342Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:27:16.812Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:27:18.254Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:27:18.950Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:27:19.637Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:27:19.637Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:27:19.637Z] Movies recommended for you:
[2025-02-20T01:27:19.637Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:27:19.637Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:27:19.637Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14060.955 ms) ======
[2025-02-20T01:27:19.637Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-20T01:27:19.637Z] GC before operation: completed in 53.547 ms, heap usage 261.997 MB -> 52.441 MB.
[2025-02-20T01:27:21.875Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:27:24.104Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:27:26.355Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:27:28.586Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:27:30.036Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:27:30.732Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:27:32.174Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:27:33.601Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:27:33.601Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:27:33.601Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:27:33.601Z] Movies recommended for you:
[2025-02-20T01:27:33.601Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:27:33.601Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:27:33.601Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14131.517 ms) ======
[2025-02-20T01:27:33.601Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-20T01:27:33.601Z] GC before operation: completed in 72.801 ms, heap usage 504.776 MB -> 55.897 MB.
[2025-02-20T01:27:36.703Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:27:38.221Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:27:40.455Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:27:42.675Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:27:43.381Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:27:44.817Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:27:46.259Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:27:46.960Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:27:47.648Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:27:47.648Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:27:47.648Z] Movies recommended for you:
[2025-02-20T01:27:47.648Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:27:47.648Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:27:47.648Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13663.309 ms) ======
[2025-02-20T01:27:47.648Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-20T01:27:47.648Z] GC before operation: completed in 68.675 ms, heap usage 529.497 MB -> 55.959 MB.
[2025-02-20T01:27:49.878Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:27:52.124Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:27:54.416Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:27:55.838Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:27:57.260Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:27:57.949Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:27:59.406Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:28:01.075Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:28:01.075Z] 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.
[2025-02-20T01:28:01.075Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:28:01.075Z] Movies recommended for you:
[2025-02-20T01:28:01.075Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:28:01.075Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:28:01.075Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13488.431 ms) ======
[2025-02-20T01:28:01.075Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-20T01:28:01.075Z] GC before operation: completed in 53.178 ms, heap usage 197.272 MB -> 54.627 MB.
[2025-02-20T01:28:03.336Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:28:05.587Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:28:07.814Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:28:10.118Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:28:10.825Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:28:12.261Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:28:13.683Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:28:15.119Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:28:15.119Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:28:15.119Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:28:15.119Z] Movies recommended for you:
[2025-02-20T01:28:15.119Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:28:15.119Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:28:15.119Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14140.688 ms) ======
[2025-02-20T01:28:15.119Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-20T01:28:15.119Z] GC before operation: completed in 54.799 ms, heap usage 223.661 MB -> 52.655 MB.
[2025-02-20T01:28:17.355Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:28:19.613Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:28:21.829Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:28:24.054Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:28:24.759Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:28:26.186Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:28:27.617Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:28:29.106Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:28:29.106Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:28:29.106Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:28:29.106Z] Movies recommended for you:
[2025-02-20T01:28:29.106Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:28:29.106Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:28:29.106Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13929.436 ms) ======
[2025-02-20T01:28:29.106Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-20T01:28:29.106Z] GC before operation: completed in 61.871 ms, heap usage 333.768 MB -> 52.782 MB.
[2025-02-20T01:28:31.338Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:28:33.573Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:28:35.808Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:28:38.042Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:28:38.734Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:28:40.172Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:28:41.606Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:28:43.051Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:28:43.051Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:28:43.051Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:28:43.051Z] Movies recommended for you:
[2025-02-20T01:28:43.051Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:28:43.051Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:28:43.051Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13717.364 ms) ======
[2025-02-20T01:28:43.051Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-20T01:28:43.051Z] GC before operation: completed in 60.692 ms, heap usage 427.786 MB -> 52.706 MB.
[2025-02-20T01:28:45.408Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:28:47.663Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:28:49.889Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:28:52.138Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:28:52.826Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:28:54.252Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:28:55.671Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:28:57.126Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:28:57.126Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:28:57.126Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:28:57.126Z] Movies recommended for you:
[2025-02-20T01:28:57.126Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:28:57.126Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:28:57.126Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14234.346 ms) ======
[2025-02-20T01:28:57.126Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-20T01:28:57.126Z] GC before operation: completed in 57.411 ms, heap usage 855.718 MB -> 56.683 MB.
[2025-02-20T01:29:00.235Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:29:01.691Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:29:03.925Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:29:06.590Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:29:07.293Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:29:08.745Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:29:10.167Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:29:11.605Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:29:11.605Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:29:11.605Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:29:11.605Z] Movies recommended for you:
[2025-02-20T01:29:11.605Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:29:11.605Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:29:11.605Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14340.507 ms) ======
[2025-02-20T01:29:11.605Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-20T01:29:11.605Z] GC before operation: completed in 84.317 ms, heap usage 157.674 MB -> 52.778 MB.
[2025-02-20T01:29:13.865Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:29:16.094Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:29:18.321Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:29:20.559Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:29:22.006Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:29:22.712Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:29:24.160Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:29:25.601Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:29:25.601Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:29:25.601Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:29:25.601Z] Movies recommended for you:
[2025-02-20T01:29:25.601Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:29:25.601Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:29:25.601Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14103.562 ms) ======
[2025-02-20T01:29:25.601Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-20T01:29:26.284Z] GC before operation: completed in 108.841 ms, heap usage 325.708 MB -> 52.711 MB.
[2025-02-20T01:29:28.523Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:29:29.969Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:29:32.213Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:29:34.438Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:29:35.955Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:29:36.651Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:29:38.126Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:29:39.559Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:29:39.559Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:29:39.559Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:29:40.248Z] Movies recommended for you:
[2025-02-20T01:29:40.248Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:29:40.248Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:29:40.248Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13933.333 ms) ======
[2025-02-20T01:29:40.248Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-20T01:29:40.248Z] GC before operation: completed in 49.390 ms, heap usage 214.584 MB -> 52.787 MB.
[2025-02-20T01:29:42.483Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:29:43.919Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:29:46.224Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:29:48.469Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:29:49.906Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:29:50.591Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:29:52.833Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:29:53.529Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:29:53.529Z] 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.
[2025-02-20T01:29:54.214Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:29:54.214Z] Movies recommended for you:
[2025-02-20T01:29:54.214Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:29:54.214Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:29:54.214Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13969.230 ms) ======
[2025-02-20T01:29:54.214Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-20T01:29:54.214Z] GC before operation: completed in 74.047 ms, heap usage 253.205 MB -> 52.877 MB.
[2025-02-20T01:29:56.444Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:29:58.670Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:30:00.936Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:30:02.367Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:30:03.798Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:30:05.673Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:30:06.374Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:30:07.813Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:30:07.813Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:30:07.813Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:30:07.813Z] Movies recommended for you:
[2025-02-20T01:30:07.813Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:30:07.813Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:30:07.813Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13835.853 ms) ======
[2025-02-20T01:30:07.813Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-20T01:30:07.813Z] GC before operation: completed in 49.642 ms, heap usage 474.805 MB -> 56.142 MB.
[2025-02-20T01:30:10.044Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:30:12.289Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:30:14.515Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:30:16.740Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:30:17.426Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:30:18.858Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:30:20.289Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:30:21.731Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:30:21.731Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:30:21.731Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:30:22.414Z] Movies recommended for you:
[2025-02-20T01:30:22.414Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:30:22.414Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:30:22.414Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14166.363 ms) ======
[2025-02-20T01:30:22.414Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-20T01:30:22.414Z] GC before operation: completed in 58.400 ms, heap usage 745.963 MB -> 56.426 MB.
[2025-02-20T01:30:24.632Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:30:26.880Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:30:28.314Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:30:30.551Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:30:32.085Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:30:32.782Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:30:34.224Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:30:35.669Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:30:35.669Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T01:30:35.669Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:30:36.362Z] Movies recommended for you:
[2025-02-20T01:30:36.362Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:30:36.362Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:30:36.362Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13845.078 ms) ======
[2025-02-20T01:30:36.362Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-20T01:30:36.362Z] GC before operation: completed in 54.044 ms, heap usage 299.710 MB -> 53.094 MB.
[2025-02-20T01:30:38.605Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T01:30:40.042Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T01:30:42.280Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T01:30:44.555Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T01:30:45.985Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T01:30:46.678Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T01:30:48.107Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T01:30:49.535Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T01:30:49.535Z] 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.
[2025-02-20T01:30:49.535Z] The best model improves the baseline by 14.43%.
[2025-02-20T01:30:50.237Z] Movies recommended for you:
[2025-02-20T01:30:50.237Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T01:30:50.237Z] There is no way to check that no silent failure occurred.
[2025-02-20T01:30:50.237Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13814.733 ms) ======
[2025-02-20T01:30:50.921Z] -----------------------------------
[2025-02-20T01:30:50.921Z] renaissance-movie-lens_0_PASSED
[2025-02-20T01:30:50.921Z] -----------------------------------
[2025-02-20T01:30:50.921Z]
[2025-02-20T01:30:50.921Z] TEST TEARDOWN:
[2025-02-20T01:30:50.921Z] Nothing to be done for teardown.
[2025-02-20T01:30:50.921Z] renaissance-movie-lens_0 Finish Time: Wed Feb 19 19:30:50 2025 Epoch Time (ms): 1740015050769