renaissance-movie-lens_0
[2025-02-12T22:20:47.904Z] Running test renaissance-movie-lens_0 ...
[2025-02-12T22:20:47.904Z] ===============================================
[2025-02-12T22:20:47.904Z] renaissance-movie-lens_0 Start Time: Wed Feb 12 22:20:47 2025 Epoch Time (ms): 1739398847157
[2025-02-12T22:20:47.904Z] variation: NoOptions
[2025-02-12T22:20:47.904Z] JVM_OPTIONS:
[2025-02-12T22:20:47.904Z] { \
[2025-02-12T22:20:47.905Z] echo ""; echo "TEST SETUP:"; \
[2025-02-12T22:20:47.905Z] echo "Nothing to be done for setup."; \
[2025-02-12T22:20:47.905Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17393971974003/renaissance-movie-lens_0"; \
[2025-02-12T22:20:47.905Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17393971974003/renaissance-movie-lens_0"; \
[2025-02-12T22:20:47.905Z] echo ""; echo "TESTING:"; \
[2025-02-12T22:20:47.905Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/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_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17393971974003/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-12T22:20:47.905Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17393971974003/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-12T22:20:47.905Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-12T22:20:47.905Z] echo "Nothing to be done for teardown."; \
[2025-02-12T22:20:47.905Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17393971974003/TestTargetResult";
[2025-02-12T22:20:47.905Z]
[2025-02-12T22:20:47.905Z] TEST SETUP:
[2025-02-12T22:20:47.905Z] Nothing to be done for setup.
[2025-02-12T22:20:47.905Z]
[2025-02-12T22:20:47.905Z] TESTING:
[2025-02-12T22:21:18.014Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-12T22:21:24.902Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 16) threads.
[2025-02-12T22:21:29.360Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-12T22:21:30.140Z] Training: 60056, validation: 20285, test: 19854
[2025-02-12T22:21:30.140Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-12T22:21:30.140Z] GC before operation: completed in 54.220 ms, heap usage 47.362 MB -> 37.395 MB.
[2025-02-12T22:21:37.079Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:21:40.525Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:21:46.142Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:21:49.573Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:21:51.164Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:21:52.769Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:21:55.268Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:21:57.216Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:21:57.216Z] 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.
[2025-02-12T22:21:57.216Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:21:57.216Z] Movies recommended for you:
[2025-02-12T22:21:57.216Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:21:57.216Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:21:57.216Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27196.241 ms) ======
[2025-02-12T22:21:57.216Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-12T22:21:57.216Z] GC before operation: completed in 82.110 ms, heap usage 815.782 MB -> 54.343 MB.
[2025-02-12T22:22:00.810Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:22:03.279Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:22:07.747Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:22:10.216Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:22:11.814Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:22:14.294Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:22:15.889Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:22:17.499Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:22:18.269Z] 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.
[2025-02-12T22:22:18.269Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:22:18.269Z] Movies recommended for you:
[2025-02-12T22:22:18.269Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:22:18.269Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:22:18.269Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20846.393 ms) ======
[2025-02-12T22:22:18.269Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-12T22:22:18.269Z] GC before operation: completed in 88.183 ms, heap usage 2.652 GB -> 56.178 MB.
[2025-02-12T22:22:20.748Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:22:24.194Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:22:27.620Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:22:31.043Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:22:32.638Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:22:34.241Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:22:38.707Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:22:41.183Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:22:41.183Z] 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.
[2025-02-12T22:22:41.183Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:22:41.183Z] Movies recommended for you:
[2025-02-12T22:22:41.183Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:22:41.183Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:22:41.183Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23148.981 ms) ======
[2025-02-12T22:22:41.183Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-12T22:22:41.183Z] GC before operation: completed in 79.417 ms, heap usage 510.641 MB -> 55.017 MB.
[2025-02-12T22:22:44.630Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:22:47.105Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:22:51.585Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:22:55.025Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:22:56.623Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:22:58.217Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:22:59.814Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:23:02.300Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:23:02.300Z] 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.
[2025-02-12T22:23:02.300Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:23:02.300Z] Movies recommended for you:
[2025-02-12T22:23:02.300Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:23:02.300Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:23:02.300Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20898.747 ms) ======
[2025-02-12T22:23:02.300Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-12T22:23:02.300Z] GC before operation: completed in 84.539 ms, heap usage 2.084 GB -> 56.832 MB.
[2025-02-12T22:23:04.997Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:23:07.492Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:23:11.970Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:23:15.397Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:23:16.999Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:23:18.597Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:23:21.247Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:23:22.840Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:23:22.840Z] 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.
[2025-02-12T22:23:23.611Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:23:23.611Z] Movies recommended for you:
[2025-02-12T22:23:23.611Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:23:23.611Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:23:23.611Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21000.050 ms) ======
[2025-02-12T22:23:23.611Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-12T22:23:23.611Z] GC before operation: completed in 103.878 ms, heap usage 1.998 GB -> 57.010 MB.
[2025-02-12T22:23:26.094Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:23:28.577Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:23:33.050Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:23:35.542Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:23:37.136Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:23:38.726Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:23:41.209Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:23:43.701Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:23:43.701Z] 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.
[2025-02-12T22:23:43.701Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:23:43.701Z] Movies recommended for you:
[2025-02-12T22:23:43.701Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:23:43.701Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:23:43.701Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20171.764 ms) ======
[2025-02-12T22:23:43.701Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-12T22:23:43.701Z] GC before operation: completed in 82.334 ms, heap usage 242.856 MB -> 52.084 MB.
[2025-02-12T22:23:46.215Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:23:49.639Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:23:56.558Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:23:59.063Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:24:00.659Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:24:02.254Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:24:04.736Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:24:06.337Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:24:06.337Z] 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.
[2025-02-12T22:24:06.337Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:24:07.112Z] Movies recommended for you:
[2025-02-12T22:24:07.112Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:24:07.112Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:24:07.112Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23039.341 ms) ======
[2025-02-12T22:24:07.112Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-12T22:24:07.112Z] GC before operation: completed in 78.806 ms, heap usage 568.944 MB -> 55.694 MB.
[2025-02-12T22:24:09.582Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:24:12.068Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:24:16.052Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:24:19.484Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:24:21.074Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:24:22.673Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:24:25.144Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:24:26.754Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:24:27.524Z] 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.
[2025-02-12T22:24:27.524Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:24:27.524Z] Movies recommended for you:
[2025-02-12T22:24:27.524Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:24:27.524Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:24:27.524Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20545.887 ms) ======
[2025-02-12T22:24:27.524Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-12T22:24:27.524Z] GC before operation: completed in 90.909 ms, heap usage 513.584 MB -> 52.687 MB.
[2025-02-12T22:24:30.007Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:24:32.498Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:24:36.964Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:24:39.465Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:24:41.962Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:24:43.569Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:24:46.050Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:24:47.640Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:24:48.412Z] 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.
[2025-02-12T22:24:48.412Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:24:48.412Z] Movies recommended for you:
[2025-02-12T22:24:48.412Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:24:48.412Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:24:48.412Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20734.832 ms) ======
[2025-02-12T22:24:48.412Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-12T22:24:48.412Z] GC before operation: completed in 83.537 ms, heap usage 435.721 MB -> 52.466 MB.
[2025-02-12T22:24:50.884Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:24:54.421Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:25:03.084Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:25:05.571Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:25:07.176Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:25:08.774Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:25:11.257Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:25:12.880Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:25:12.880Z] 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.
[2025-02-12T22:25:12.880Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:25:12.880Z] Movies recommended for you:
[2025-02-12T22:25:12.880Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:25:12.880Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:25:12.880Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (24753.538 ms) ======
[2025-02-12T22:25:12.880Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-12T22:25:12.880Z] GC before operation: completed in 85.530 ms, heap usage 378.391 MB -> 52.506 MB.
[2025-02-12T22:25:15.357Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:25:18.782Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:25:23.271Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:25:25.761Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:25:27.359Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:25:28.953Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:25:31.424Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:25:33.024Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:25:33.794Z] 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.
[2025-02-12T22:25:33.794Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:25:33.794Z] Movies recommended for you:
[2025-02-12T22:25:33.794Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:25:33.794Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:25:33.794Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20633.418 ms) ======
[2025-02-12T22:25:33.794Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-12T22:25:33.794Z] GC before operation: completed in 79.671 ms, heap usage 278.631 MB -> 52.158 MB.
[2025-02-12T22:25:36.285Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:25:38.764Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:25:44.385Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:25:45.977Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:25:47.591Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:25:49.184Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:25:51.741Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:25:53.934Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:25:53.934Z] 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.
[2025-02-12T22:25:53.934Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:25:53.934Z] Movies recommended for you:
[2025-02-12T22:25:53.934Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:25:53.934Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:25:53.934Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20088.866 ms) ======
[2025-02-12T22:25:53.934Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-12T22:25:53.934Z] GC before operation: completed in 85.624 ms, heap usage 628.631 MB -> 55.807 MB.
[2025-02-12T22:25:57.365Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:25:59.844Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:26:13.583Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:26:16.082Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:26:19.525Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:26:22.014Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:26:28.884Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:26:30.493Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:26:30.493Z] 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.
[2025-02-12T22:26:30.493Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:26:30.493Z] Movies recommended for you:
[2025-02-12T22:26:30.493Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:26:30.493Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:26:30.493Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36461.940 ms) ======
[2025-02-12T22:26:30.493Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-12T22:26:30.493Z] GC before operation: completed in 86.777 ms, heap usage 227.739 MB -> 52.491 MB.
[2025-02-12T22:26:32.969Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:26:36.388Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:26:44.678Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:26:48.111Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:26:49.718Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:26:51.355Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:26:55.816Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:26:57.410Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:26:58.182Z] 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.
[2025-02-12T22:26:58.182Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:26:58.182Z] Movies recommended for you:
[2025-02-12T22:26:58.182Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:26:58.182Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:26:58.182Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (27530.415 ms) ======
[2025-02-12T22:26:58.182Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-12T22:26:58.182Z] GC before operation: completed in 87.758 ms, heap usage 1.539 GB -> 57.021 MB.
[2025-02-12T22:27:00.659Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:27:04.086Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:27:08.571Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:27:11.740Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:27:14.214Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:27:16.685Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:27:20.125Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:27:21.759Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:27:21.759Z] 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.
[2025-02-12T22:27:21.759Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:27:22.531Z] Movies recommended for you:
[2025-02-12T22:27:22.531Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:27:22.531Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:27:22.531Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (23949.837 ms) ======
[2025-02-12T22:27:22.531Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-12T22:27:22.531Z] GC before operation: completed in 76.897 ms, heap usage 298.647 MB -> 52.452 MB.
[2025-02-12T22:27:25.015Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:27:28.451Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:27:32.944Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:27:35.414Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:27:37.908Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:27:39.505Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:27:42.947Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:27:44.540Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:27:44.540Z] 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.
[2025-02-12T22:27:44.540Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:27:45.310Z] Movies recommended for you:
[2025-02-12T22:27:45.310Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:27:45.310Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:27:45.310Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (22771.308 ms) ======
[2025-02-12T22:27:45.310Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-12T22:27:45.310Z] GC before operation: completed in 93.887 ms, heap usage 2.945 GB -> 57.525 MB.
[2025-02-12T22:27:47.811Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:27:50.281Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:27:55.901Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:27:58.393Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:27:59.986Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:28:01.589Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:28:05.022Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:28:06.614Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:28:06.614Z] 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.
[2025-02-12T22:28:06.614Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:28:06.614Z] Movies recommended for you:
[2025-02-12T22:28:06.614Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:28:06.614Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:28:06.614Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (21785.844 ms) ======
[2025-02-12T22:28:06.614Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-12T22:28:06.614Z] GC before operation: completed in 77.402 ms, heap usage 311.559 MB -> 52.384 MB.
[2025-02-12T22:28:10.070Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:28:13.497Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:28:22.520Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:28:24.990Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:28:27.460Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:28:29.049Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:28:31.536Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:28:33.140Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:28:33.910Z] 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.
[2025-02-12T22:28:33.910Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:28:33.910Z] Movies recommended for you:
[2025-02-12T22:28:33.910Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:28:33.910Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:28:33.910Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26771.118 ms) ======
[2025-02-12T22:28:33.910Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-12T22:28:33.910Z] GC before operation: completed in 97.032 ms, heap usage 2.292 GB -> 57.345 MB.
[2025-02-12T22:28:36.377Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:28:39.807Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:28:45.422Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:28:47.913Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:28:50.388Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:28:51.988Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:28:56.448Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:28:58.058Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:28:58.058Z] 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.
[2025-02-12T22:28:58.058Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:28:58.058Z] Movies recommended for you:
[2025-02-12T22:28:58.058Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:28:58.058Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:28:58.058Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (24327.685 ms) ======
[2025-02-12T22:28:58.058Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-12T22:28:58.058Z] GC before operation: completed in 83.822 ms, heap usage 999.108 MB -> 56.700 MB.
[2025-02-12T22:29:01.493Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T22:29:04.944Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T22:29:10.556Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T22:29:13.042Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T22:29:14.637Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T22:29:16.242Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T22:29:20.017Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T22:29:20.808Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T22:29:21.575Z] 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.
[2025-02-12T22:29:21.575Z] The best model improves the baseline by 14.43%.
[2025-02-12T22:29:21.575Z] Movies recommended for you:
[2025-02-12T22:29:21.575Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T22:29:21.575Z] There is no way to check that no silent failure occurred.
[2025-02-12T22:29:21.575Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (23183.149 ms) ======
[2025-02-12T22:29:22.348Z] -----------------------------------
[2025-02-12T22:29:22.348Z] renaissance-movie-lens_0_PASSED
[2025-02-12T22:29:22.348Z] -----------------------------------
[2025-02-12T22:29:22.348Z]
[2025-02-12T22:29:22.348Z] TEST TEARDOWN:
[2025-02-12T22:29:22.348Z] Nothing to be done for teardown.
[2025-02-12T22:29:22.348Z] renaissance-movie-lens_0 Finish Time: Wed Feb 12 22:29:21 2025 Epoch Time (ms): 1739399361872