renaissance-movie-lens_0
[2025-02-12T21:54:20.655Z] Running test renaissance-movie-lens_0 ...
[2025-02-12T21:54:20.655Z] ===============================================
[2025-02-12T21:54:20.655Z] renaissance-movie-lens_0 Start Time: Wed Feb 12 15:54:20 2025 Epoch Time (ms): 1739397260377
[2025-02-12T21:54:20.655Z] variation: NoOptions
[2025-02-12T21:54:20.655Z] JVM_OPTIONS:
[2025-02-12T21:54:20.655Z] { \
[2025-02-12T21:54:20.655Z] echo ""; echo "TEST SETUP:"; \
[2025-02-12T21:54:20.655Z] echo "Nothing to be done for setup."; \
[2025-02-12T21:54:20.655Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17393966366363/renaissance-movie-lens_0"; \
[2025-02-12T21:54:20.655Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17393966366363/renaissance-movie-lens_0"; \
[2025-02-12T21:54:20.655Z] echo ""; echo "TESTING:"; \
[2025-02-12T21:54:20.655Z] "/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_17393966366363/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-12T21:54:20.655Z] 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_17393966366363/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-12T21:54:20.655Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-12T21:54:20.655Z] echo "Nothing to be done for teardown."; \
[2025-02-12T21:54:20.655Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17393966366363/TestTargetResult";
[2025-02-12T21:54:20.655Z]
[2025-02-12T21:54:20.655Z] TEST SETUP:
[2025-02-12T21:54:20.655Z] Nothing to be done for setup.
[2025-02-12T21:54:20.655Z]
[2025-02-12T21:54:20.655Z] TESTING:
[2025-02-12T21:54:23.087Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-12T21:54:24.663Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-02-12T21:54:28.064Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-12T21:54:28.064Z] Training: 60056, validation: 20285, test: 19854
[2025-02-12T21:54:28.064Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-12T21:54:28.064Z] GC before operation: completed in 54.597 ms, heap usage 76.290 MB -> 37.713 MB.
[2025-02-12T21:54:34.879Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:54:38.314Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:54:41.748Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:54:44.261Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:54:45.870Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:54:47.488Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:54:49.099Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:54:50.746Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:54:50.746Z] 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.
[2025-02-12T21:54:50.746Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:54:50.746Z] Movies recommended for you:
[2025-02-12T21:54:50.746Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:54:50.746Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:54:50.746Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23168.907 ms) ======
[2025-02-12T21:54:50.746Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-12T21:54:51.502Z] GC before operation: completed in 108.074 ms, heap usage 806.975 MB -> 57.070 MB.
[2025-02-12T21:54:53.978Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:54:57.368Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:54:59.810Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:02.295Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:03.072Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:04.648Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:07.052Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:07.830Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:07.830Z] 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.
[2025-02-12T21:55:07.830Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:55:08.738Z] Movies recommended for you:
[2025-02-12T21:55:08.738Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:08.738Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:08.738Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17009.080 ms) ======
[2025-02-12T21:55:08.738Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-12T21:55:08.738Z] GC before operation: completed in 54.499 ms, heap usage 248.835 MB -> 51.421 MB.
[2025-02-12T21:55:11.199Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:13.776Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:16.277Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:18.733Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:20.331Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:21.917Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:22.689Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:24.257Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:24.257Z] 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.
[2025-02-12T21:55:24.257Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:55:25.013Z] Movies recommended for you:
[2025-02-12T21:55:25.013Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:25.013Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:25.013Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16401.256 ms) ======
[2025-02-12T21:55:25.013Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-12T21:55:25.013Z] GC before operation: completed in 78.494 ms, heap usage 382.011 MB -> 51.954 MB.
[2025-02-12T21:55:27.448Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:29.019Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:31.477Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:33.050Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:34.623Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:36.191Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:37.774Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:38.538Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:39.296Z] 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.
[2025-02-12T21:55:39.296Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:55:39.296Z] Movies recommended for you:
[2025-02-12T21:55:39.296Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:39.296Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:39.296Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14342.585 ms) ======
[2025-02-12T21:55:39.296Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-12T21:55:39.296Z] GC before operation: completed in 55.592 ms, heap usage 448.313 MB -> 52.357 MB.
[2025-02-12T21:55:41.758Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:43.331Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:45.801Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:47.383Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:48.966Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:50.551Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:51.310Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:52.891Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:52.891Z] 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.
[2025-02-12T21:55:52.891Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:55:52.891Z] Movies recommended for you:
[2025-02-12T21:55:52.891Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:52.891Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:52.891Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14084.440 ms) ======
[2025-02-12T21:55:52.891Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-12T21:55:53.649Z] GC before operation: completed in 73.156 ms, heap usage 296.327 MB -> 52.511 MB.
[2025-02-12T21:55:56.091Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:58.534Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:00.115Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:02.677Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:03.438Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:05.032Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:05.812Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:07.504Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:07.504Z] 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.
[2025-02-12T21:56:07.504Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:56:07.504Z] Movies recommended for you:
[2025-02-12T21:56:07.504Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:07.504Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:07.504Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14383.653 ms) ======
[2025-02-12T21:56:07.504Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-12T21:56:07.504Z] GC before operation: completed in 53.880 ms, heap usage 419.797 MB -> 52.552 MB.
[2025-02-12T21:56:09.960Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:12.413Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:13.989Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:16.450Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:17.205Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:18.776Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:20.343Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:21.921Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:21.921Z] 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.
[2025-02-12T21:56:21.921Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:56:21.921Z] Movies recommended for you:
[2025-02-12T21:56:21.921Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:21.921Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:21.921Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14191.966 ms) ======
[2025-02-12T21:56:21.921Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-12T21:56:21.921Z] GC before operation: completed in 56.806 ms, heap usage 264.705 MB -> 55.661 MB.
[2025-02-12T21:56:24.371Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:25.939Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:28.397Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:30.028Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:31.617Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:33.184Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:34.766Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:35.552Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:35.552Z] 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.
[2025-02-12T21:56:35.552Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:56:36.315Z] Movies recommended for you:
[2025-02-12T21:56:36.315Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:36.315Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:36.315Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13946.764 ms) ======
[2025-02-12T21:56:36.315Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-12T21:56:36.315Z] GC before operation: completed in 56.539 ms, heap usage 341.059 MB -> 52.723 MB.
[2025-02-12T21:56:37.889Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:40.320Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:42.774Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:44.354Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:45.923Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:46.686Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:48.278Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:49.040Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:49.798Z] 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.
[2025-02-12T21:56:49.798Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:56:49.798Z] Movies recommended for you:
[2025-02-12T21:56:49.798Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:49.798Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:49.798Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13710.156 ms) ======
[2025-02-12T21:56:49.798Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-12T21:56:49.798Z] GC before operation: completed in 51.602 ms, heap usage 843.930 MB -> 56.518 MB.
[2025-02-12T21:56:52.246Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:53.820Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:56.297Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:57.880Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:59.443Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:01.055Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:01.818Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:03.393Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:03.393Z] 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.
[2025-02-12T21:57:03.393Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:57:03.393Z] Movies recommended for you:
[2025-02-12T21:57:03.393Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:03.393Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:03.393Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13726.235 ms) ======
[2025-02-12T21:57:03.393Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-12T21:57:03.393Z] GC before operation: completed in 50.292 ms, heap usage 300.067 MB -> 52.807 MB.
[2025-02-12T21:57:05.929Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:07.521Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:09.982Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:11.568Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:13.146Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:14.718Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:15.496Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:17.070Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:17.070Z] 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.
[2025-02-12T21:57:17.070Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:57:17.826Z] Movies recommended for you:
[2025-02-12T21:57:17.826Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:17.826Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:17.826Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13966.316 ms) ======
[2025-02-12T21:57:17.826Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-12T21:57:17.826Z] GC before operation: completed in 60.614 ms, heap usage 458.412 MB -> 52.585 MB.
[2025-02-12T21:57:20.273Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:21.849Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:24.287Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:25.874Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:27.450Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:29.018Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:29.774Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:31.347Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:31.347Z] 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.
[2025-02-12T21:57:31.347Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:57:31.347Z] Movies recommended for you:
[2025-02-12T21:57:31.347Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:31.347Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:31.347Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14085.315 ms) ======
[2025-02-12T21:57:31.347Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-12T21:57:32.103Z] GC before operation: completed in 83.105 ms, heap usage 764.022 MB -> 56.472 MB.
[2025-02-12T21:57:34.557Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:36.130Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:38.582Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:40.174Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:41.755Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:43.327Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:44.920Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:45.683Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:45.683Z] 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.
[2025-02-12T21:57:45.683Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:57:45.683Z] Movies recommended for you:
[2025-02-12T21:57:45.683Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:45.683Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:45.683Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14292.488 ms) ======
[2025-02-12T21:57:45.683Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-12T21:57:46.457Z] GC before operation: completed in 50.274 ms, heap usage 282.722 MB -> 52.955 MB.
[2025-02-12T21:57:48.046Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:50.540Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:52.992Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:54.565Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:56.172Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:56.939Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:58.508Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:00.087Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:00.087Z] 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.
[2025-02-12T21:58:00.087Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:00.087Z] Movies recommended for you:
[2025-02-12T21:58:00.087Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:00.087Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:00.087Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13996.437 ms) ======
[2025-02-12T21:58:00.087Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-12T21:58:00.087Z] GC before operation: completed in 55.889 ms, heap usage 482.268 MB -> 56.023 MB.
[2025-02-12T21:58:02.534Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:04.109Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:06.549Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:08.996Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:09.760Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:11.339Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:12.930Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:13.693Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:14.463Z] 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.
[2025-02-12T21:58:14.463Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:14.463Z] Movies recommended for you:
[2025-02-12T21:58:14.463Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:14.463Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:14.463Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14093.040 ms) ======
[2025-02-12T21:58:14.463Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-12T21:58:14.463Z] GC before operation: completed in 68.592 ms, heap usage 440.126 MB -> 54.729 MB.
[2025-02-12T21:58:16.919Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:18.485Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:20.929Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:23.397Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:24.167Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:25.760Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:27.347Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:28.119Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:28.119Z] 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.
[2025-02-12T21:58:28.119Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:28.888Z] Movies recommended for you:
[2025-02-12T21:58:28.888Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:28.888Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:28.888Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14210.962 ms) ======
[2025-02-12T21:58:28.888Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-12T21:58:28.888Z] GC before operation: completed in 97.334 ms, heap usage 292.399 MB -> 52.847 MB.
[2025-02-12T21:58:31.353Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:32.932Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:35.422Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:37.007Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:38.589Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:39.349Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:40.931Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:41.696Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:42.466Z] 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.
[2025-02-12T21:58:42.466Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:42.466Z] Movies recommended for you:
[2025-02-12T21:58:42.466Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:42.466Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:42.466Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13767.553 ms) ======
[2025-02-12T21:58:42.466Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-12T21:58:42.466Z] GC before operation: completed in 49.070 ms, heap usage 73.669 MB -> 56.540 MB.
[2025-02-12T21:58:44.918Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:46.529Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:48.978Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:50.542Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:52.128Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:52.904Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:54.483Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:56.048Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:56.048Z] 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.
[2025-02-12T21:58:56.048Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:56.048Z] Movies recommended for you:
[2025-02-12T21:58:56.048Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:56.048Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:56.048Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13745.202 ms) ======
[2025-02-12T21:58:56.048Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-12T21:58:56.048Z] GC before operation: completed in 58.371 ms, heap usage 364.612 MB -> 52.787 MB.
[2025-02-12T21:58:58.611Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:59:00.211Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:59:02.661Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:59:05.113Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:59:05.879Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:59:07.460Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:59:08.228Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:59:09.804Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:59:09.804Z] 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.
[2025-02-12T21:59:09.804Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:59:09.804Z] Movies recommended for you:
[2025-02-12T21:59:09.804Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:59:09.804Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:59:09.804Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13909.451 ms) ======
[2025-02-12T21:59:09.804Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-12T21:59:10.562Z] GC before operation: completed in 72.451 ms, heap usage 317.813 MB -> 52.996 MB.
[2025-02-12T21:59:12.129Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:59:14.562Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:59:17.003Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:59:18.583Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:59:20.153Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:59:20.918Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:59:22.539Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:59:24.123Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:59:24.123Z] 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.
[2025-02-12T21:59:24.123Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:59:24.123Z] Movies recommended for you:
[2025-02-12T21:59:24.123Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:59:24.123Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:59:24.123Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13986.266 ms) ======
[2025-02-12T21:59:24.883Z] -----------------------------------
[2025-02-12T21:59:24.883Z] renaissance-movie-lens_0_PASSED
[2025-02-12T21:59:24.883Z] -----------------------------------
[2025-02-12T21:59:24.883Z]
[2025-02-12T21:59:24.883Z] TEST TEARDOWN:
[2025-02-12T21:59:24.883Z] Nothing to be done for teardown.
[2025-02-12T21:59:25.640Z] renaissance-movie-lens_0 Finish Time: Wed Feb 12 15:59:25 2025 Epoch Time (ms): 1739397565088