renaissance-movie-lens_0
[2025-01-10T21:17:04.598Z] Running test renaissance-movie-lens_0 ...
[2025-01-10T21:17:04.598Z] ===============================================
[2025-01-10T21:17:04.598Z] renaissance-movie-lens_0 Start Time: Fri Jan 10 21:17:03 2025 Epoch Time (ms): 1736543823575
[2025-01-10T21:17:04.598Z] variation: NoOptions
[2025-01-10T21:17:04.598Z] JVM_OPTIONS:
[2025-01-10T21:17:04.598Z] { \
[2025-01-10T21:17:04.598Z] echo ""; echo "TEST SETUP:"; \
[2025-01-10T21:17:04.598Z] echo "Nothing to be done for setup."; \
[2025-01-10T21:17:04.598Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365429563040/renaissance-movie-lens_0"; \
[2025-01-10T21:17:04.598Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365429563040/renaissance-movie-lens_0"; \
[2025-01-10T21:17:04.598Z] echo ""; echo "TESTING:"; \
[2025-01-10T21:17:04.598Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_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_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365429563040/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-01-10T21:17:04.598Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365429563040/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-01-10T21:17:04.598Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-01-10T21:17:04.598Z] echo "Nothing to be done for teardown."; \
[2025-01-10T21:17:04.598Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365429563040/TestTargetResult";
[2025-01-10T21:17:04.598Z]
[2025-01-10T21:17:04.598Z] TEST SETUP:
[2025-01-10T21:17:04.598Z] Nothing to be done for setup.
[2025-01-10T21:17:04.598Z]
[2025-01-10T21:17:04.598Z] TESTING:
[2025-01-10T21:17:07.614Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-01-10T21:17:10.626Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-01-10T21:17:14.772Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-01-10T21:17:14.772Z] Training: 60056, validation: 20285, test: 19854
[2025-01-10T21:17:14.772Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-01-10T21:17:14.772Z] GC before operation: completed in 63.360 ms, heap usage 107.797 MB -> 39.241 MB.
[2025-01-10T21:17:22.175Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:17:27.567Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:17:30.584Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:17:33.606Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:17:35.563Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:17:37.515Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:17:38.645Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:17:40.599Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:17:41.550Z] 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.
[2025-01-10T21:17:41.550Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:17:41.550Z] Movies recommended for you:
[2025-01-10T21:17:41.550Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:17:41.550Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:17:41.550Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26820.433 ms) ======
[2025-01-10T21:17:41.550Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-01-10T21:17:41.550Z] GC before operation: completed in 145.964 ms, heap usage 327.531 MB -> 52.214 MB.
[2025-01-10T21:17:45.704Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:17:48.726Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:17:52.889Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:17:55.918Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:17:56.871Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:17:58.828Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:18:00.783Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:18:02.743Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:18:02.743Z] 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.
[2025-01-10T21:18:02.743Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:18:02.743Z] Movies recommended for you:
[2025-01-10T21:18:02.743Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:18:02.743Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:18:02.743Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21373.642 ms) ======
[2025-01-10T21:18:02.743Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-01-10T21:18:02.743Z] GC before operation: completed in 161.050 ms, heap usage 1.038 GB -> 57.234 MB.
[2025-01-10T21:18:05.761Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:18:08.788Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:18:11.805Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:18:14.830Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:18:15.782Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:18:17.739Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:18:20.397Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:18:21.372Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:18:21.372Z] 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.
[2025-01-10T21:18:21.372Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:18:21.372Z] Movies recommended for you:
[2025-01-10T21:18:21.372Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:18:21.372Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:18:21.372Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18462.763 ms) ======
[2025-01-10T21:18:21.372Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-01-10T21:18:21.372Z] GC before operation: completed in 98.082 ms, heap usage 396.339 MB -> 53.341 MB.
[2025-01-10T21:18:24.422Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:18:27.441Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:18:30.460Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:18:32.418Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:18:34.382Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:18:35.337Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:18:37.295Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:18:38.250Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:18:39.204Z] 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.
[2025-01-10T21:18:39.204Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:18:39.204Z] Movies recommended for you:
[2025-01-10T21:18:39.204Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:18:39.204Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:18:39.204Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17237.275 ms) ======
[2025-01-10T21:18:39.204Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-01-10T21:18:39.204Z] GC before operation: completed in 92.527 ms, heap usage 456.464 MB -> 53.779 MB.
[2025-01-10T21:18:41.160Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:18:44.201Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:18:46.161Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:18:49.181Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:18:50.135Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:18:52.088Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:18:53.041Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:18:54.998Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:18:54.998Z] 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.
[2025-01-10T21:18:54.998Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:18:54.998Z] Movies recommended for you:
[2025-01-10T21:18:54.998Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:18:54.998Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:18:54.998Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15928.202 ms) ======
[2025-01-10T21:18:54.998Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-01-10T21:18:54.998Z] GC before operation: completed in 89.454 ms, heap usage 380.042 MB -> 53.884 MB.
[2025-01-10T21:18:58.016Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:18:59.973Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:19:01.933Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:19:04.954Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:19:05.909Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:19:06.912Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:19:08.870Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:19:09.822Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:19:10.774Z] 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.
[2025-01-10T21:19:10.774Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:19:10.774Z] Movies recommended for you:
[2025-01-10T21:19:10.774Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:19:10.774Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:19:10.774Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15398.191 ms) ======
[2025-01-10T21:19:10.774Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-01-10T21:19:10.774Z] GC before operation: completed in 90.533 ms, heap usage 384.050 MB -> 53.789 MB.
[2025-01-10T21:19:12.745Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:19:15.760Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:19:17.718Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:19:20.374Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:19:21.329Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:19:22.283Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:19:24.240Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:19:25.193Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:19:25.194Z] 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.
[2025-01-10T21:19:25.194Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:19:25.194Z] Movies recommended for you:
[2025-01-10T21:19:25.194Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:19:25.194Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:19:25.194Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15111.767 ms) ======
[2025-01-10T21:19:25.194Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-01-10T21:19:26.145Z] GC before operation: completed in 89.513 ms, heap usage 378.742 MB -> 54.061 MB.
[2025-01-10T21:19:28.127Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:19:30.081Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:19:32.150Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:19:35.166Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:19:36.118Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:19:37.070Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:19:39.024Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:19:39.974Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:19:39.974Z] 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.
[2025-01-10T21:19:39.974Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:19:39.974Z] Movies recommended for you:
[2025-01-10T21:19:39.974Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:19:39.974Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:19:39.974Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14571.614 ms) ======
[2025-01-10T21:19:39.974Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-01-10T21:19:39.974Z] GC before operation: completed in 87.801 ms, heap usage 1020.450 MB -> 58.332 MB.
[2025-01-10T21:19:42.987Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:19:44.939Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:19:47.962Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:19:49.929Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:19:51.892Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:19:52.844Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:19:54.795Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:19:55.748Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:19:55.748Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-01-10T21:19:55.748Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:19:55.748Z] Movies recommended for you:
[2025-01-10T21:19:55.749Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:19:55.749Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:19:55.749Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15801.588 ms) ======
[2025-01-10T21:19:55.749Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-01-10T21:19:56.702Z] GC before operation: completed in 115.267 ms, heap usage 358.299 MB -> 54.174 MB.
[2025-01-10T21:19:58.661Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:20:00.617Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:20:03.641Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:20:05.595Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:20:06.546Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:20:08.501Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:20:09.451Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:20:10.403Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:20:11.353Z] 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.
[2025-01-10T21:20:11.353Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:20:11.353Z] Movies recommended for you:
[2025-01-10T21:20:11.353Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:20:11.353Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:20:11.353Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14788.286 ms) ======
[2025-01-10T21:20:11.353Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-01-10T21:20:11.353Z] GC before operation: completed in 91.299 ms, heap usage 994.484 MB -> 58.290 MB.
[2025-01-10T21:20:13.303Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:20:16.315Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:20:18.265Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:20:20.761Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:20:21.714Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:20:23.666Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:20:24.618Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:20:25.570Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:20:26.521Z] 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.
[2025-01-10T21:20:26.521Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:20:26.521Z] Movies recommended for you:
[2025-01-10T21:20:26.521Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:20:26.521Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:20:26.521Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15164.617 ms) ======
[2025-01-10T21:20:26.521Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-01-10T21:20:26.521Z] GC before operation: completed in 89.450 ms, heap usage 382.225 MB -> 54.012 MB.
[2025-01-10T21:20:28.474Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:20:31.499Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:20:33.450Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:20:35.454Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:20:37.404Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:20:38.354Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:20:40.432Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:20:41.399Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:20:41.399Z] 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.
[2025-01-10T21:20:41.399Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:20:41.399Z] Movies recommended for you:
[2025-01-10T21:20:41.399Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:20:41.399Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:20:41.399Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15130.479 ms) ======
[2025-01-10T21:20:41.399Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-01-10T21:20:41.399Z] GC before operation: completed in 91.134 ms, heap usage 712.245 MB -> 57.768 MB.
[2025-01-10T21:20:44.412Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:20:46.366Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:20:49.378Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:20:51.333Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:20:52.283Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:20:54.235Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:20:55.186Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:20:57.138Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:20:57.138Z] 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.
[2025-01-10T21:20:57.138Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:20:57.138Z] Movies recommended for you:
[2025-01-10T21:20:57.138Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:20:57.138Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:20:57.138Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15607.858 ms) ======
[2025-01-10T21:20:57.138Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-01-10T21:20:57.138Z] GC before operation: completed in 94.373 ms, heap usage 357.883 MB -> 54.478 MB.
[2025-01-10T21:21:00.152Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:21:02.108Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:21:04.072Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:21:07.085Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:21:08.041Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:21:09.993Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:21:10.944Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:21:11.896Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:21:12.848Z] 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.
[2025-01-10T21:21:12.848Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:21:12.848Z] Movies recommended for you:
[2025-01-10T21:21:12.848Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:21:12.848Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:21:12.848Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15339.578 ms) ======
[2025-01-10T21:21:12.848Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-01-10T21:21:12.848Z] GC before operation: completed in 104.106 ms, heap usage 836.415 MB -> 57.763 MB.
[2025-01-10T21:21:14.799Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:21:17.818Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:21:19.655Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:21:21.608Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:21:23.565Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:21:24.526Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:21:25.478Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:21:27.431Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:21:27.431Z] 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.
[2025-01-10T21:21:27.431Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:21:27.431Z] Movies recommended for you:
[2025-01-10T21:21:27.431Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:21:27.431Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:21:27.431Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14517.989 ms) ======
[2025-01-10T21:21:27.431Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-01-10T21:21:27.431Z] GC before operation: completed in 94.939 ms, heap usage 384.105 MB -> 54.326 MB.
[2025-01-10T21:21:29.384Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:21:32.425Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:21:34.417Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:21:36.371Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:21:37.324Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:21:39.278Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:21:40.231Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:21:41.181Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:21:42.133Z] 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.
[2025-01-10T21:21:42.133Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:21:42.133Z] Movies recommended for you:
[2025-01-10T21:21:42.133Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:21:42.133Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:21:42.133Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14401.601 ms) ======
[2025-01-10T21:21:42.133Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-01-10T21:21:42.133Z] GC before operation: completed in 90.157 ms, heap usage 380.216 MB -> 54.397 MB.
[2025-01-10T21:21:44.090Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:21:46.044Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:21:47.997Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:21:51.017Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:21:51.969Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:21:52.922Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:21:53.873Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:21:55.827Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:21:55.827Z] 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.
[2025-01-10T21:21:55.827Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:21:55.827Z] Movies recommended for you:
[2025-01-10T21:21:55.827Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:21:55.827Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:21:55.827Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13979.895 ms) ======
[2025-01-10T21:21:55.827Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-01-10T21:21:55.827Z] GC before operation: completed in 93.890 ms, heap usage 377.680 MB -> 54.137 MB.
[2025-01-10T21:21:58.842Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:22:00.808Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:22:02.762Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:22:04.718Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:22:05.669Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:22:07.622Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:22:08.572Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:22:09.522Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:22:10.473Z] 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.
[2025-01-10T21:22:10.473Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:22:10.473Z] Movies recommended for you:
[2025-01-10T21:22:10.473Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:22:10.473Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:22:10.473Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14240.456 ms) ======
[2025-01-10T21:22:10.473Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-01-10T21:22:10.473Z] GC before operation: completed in 89.155 ms, heap usage 783.898 MB -> 57.673 MB.
[2025-01-10T21:22:13.487Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:22:15.446Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:22:17.405Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:22:19.821Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:22:20.807Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:22:21.758Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:22:23.712Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:22:24.663Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:22:24.663Z] 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.
[2025-01-10T21:22:24.663Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:22:24.663Z] Movies recommended for you:
[2025-01-10T21:22:24.663Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:22:24.663Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:22:24.663Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14747.821 ms) ======
[2025-01-10T21:22:24.663Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-01-10T21:22:25.614Z] GC before operation: completed in 90.009 ms, heap usage 283.438 MB -> 54.490 MB.
[2025-01-10T21:22:27.571Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:22:29.571Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:22:31.526Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:22:34.537Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:22:35.519Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:22:36.471Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:22:37.423Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:22:39.552Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:22:39.552Z] 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.
[2025-01-10T21:22:39.552Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:22:39.552Z] Movies recommended for you:
[2025-01-10T21:22:39.552Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:22:39.552Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:22:39.552Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14357.148 ms) ======
[2025-01-10T21:22:41.504Z] -----------------------------------
[2025-01-10T21:22:41.504Z] renaissance-movie-lens_0_PASSED
[2025-01-10T21:22:41.504Z] -----------------------------------
[2025-01-10T21:22:41.504Z]
[2025-01-10T21:22:41.504Z] TEST TEARDOWN:
[2025-01-10T21:22:41.504Z] Nothing to be done for teardown.
[2025-01-10T21:22:41.504Z] renaissance-movie-lens_0 Finish Time: Fri Jan 10 21:22:40 2025 Epoch Time (ms): 1736544160747