renaissance-movie-lens_0
[2025-02-19T21:58:45.803Z] Running test renaissance-movie-lens_0 ...
[2025-02-19T21:58:45.803Z] ===============================================
[2025-02-19T21:58:45.803Z] renaissance-movie-lens_0 Start Time: Wed Feb 19 21:58:45 2025 Epoch Time (ms): 1740002325322
[2025-02-19T21:58:45.803Z] variation: NoOptions
[2025-02-19T21:58:45.803Z] JVM_OPTIONS:
[2025-02-19T21:58:45.803Z] { \
[2025-02-19T21:58:45.803Z] echo ""; echo "TEST SETUP:"; \
[2025-02-19T21:58:45.803Z] echo "Nothing to be done for setup."; \
[2025-02-19T21:58:45.803Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400015116116/renaissance-movie-lens_0"; \
[2025-02-19T21:58:45.803Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400015116116/renaissance-movie-lens_0"; \
[2025-02-19T21:58:45.803Z] echo ""; echo "TESTING:"; \
[2025-02-19T21:58:45.803Z] "/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_17400015116116/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-19T21:58:45.803Z] 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_17400015116116/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-19T21:58:45.803Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-19T21:58:45.803Z] echo "Nothing to be done for teardown."; \
[2025-02-19T21:58:45.803Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400015116116/TestTargetResult";
[2025-02-19T21:58:45.803Z]
[2025-02-19T21:58:45.803Z] TEST SETUP:
[2025-02-19T21:58:45.803Z] Nothing to be done for setup.
[2025-02-19T21:58:45.803Z]
[2025-02-19T21:58:45.803Z] TESTING:
[2025-02-19T21:58:48.851Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-19T21:58:51.874Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-02-19T21:58:56.127Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-19T21:58:56.127Z] Training: 60056, validation: 20285, test: 19854
[2025-02-19T21:58:56.127Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-19T21:58:56.127Z] GC before operation: completed in 66.367 ms, heap usage 160.944 MB -> 39.481 MB.
[2025-02-19T21:59:04.345Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T21:59:07.378Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T21:59:11.535Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T21:59:14.582Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T21:59:16.561Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T21:59:18.518Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T21:59:20.488Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T21:59:22.453Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T21:59:22.453Z] 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.
[2025-02-19T21:59:22.453Z] The best model improves the baseline by 14.43%.
[2025-02-19T21:59:22.453Z] Movies recommended for you:
[2025-02-19T21:59:22.453Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T21:59:22.453Z] There is no way to check that no silent failure occurred.
[2025-02-19T21:59:22.453Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26452.502 ms) ======
[2025-02-19T21:59:22.453Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-19T21:59:22.453Z] GC before operation: completed in 117.203 ms, heap usage 315.615 MB -> 54.692 MB.
[2025-02-19T21:59:25.472Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T21:59:28.489Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T21:59:31.508Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T21:59:34.533Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T21:59:35.486Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T21:59:37.441Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T21:59:39.393Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T21:59:40.347Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T21:59:40.347Z] 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.
[2025-02-19T21:59:41.307Z] The best model improves the baseline by 14.43%.
[2025-02-19T21:59:41.307Z] Movies recommended for you:
[2025-02-19T21:59:41.307Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T21:59:41.307Z] There is no way to check that no silent failure occurred.
[2025-02-19T21:59:41.307Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18166.946 ms) ======
[2025-02-19T21:59:41.307Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-19T21:59:41.307Z] GC before operation: completed in 92.992 ms, heap usage 669.916 MB -> 56.695 MB.
[2025-02-19T21:59:44.322Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T21:59:46.289Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T21:59:48.837Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T21:59:51.854Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T21:59:52.806Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T21:59:54.759Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T21:59:55.712Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T21:59:57.676Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T21:59:57.676Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-19T21:59:57.676Z] The best model improves the baseline by 14.43%.
[2025-02-19T21:59:57.676Z] Movies recommended for you:
[2025-02-19T21:59:57.676Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T21:59:57.676Z] There is no way to check that no silent failure occurred.
[2025-02-19T21:59:57.676Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16724.190 ms) ======
[2025-02-19T21:59:57.676Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-19T21:59:57.676Z] GC before operation: completed in 99.725 ms, heap usage 898.508 MB -> 57.424 MB.
[2025-02-19T22:00:00.719Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:00:03.815Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:00:05.767Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:00:07.900Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:00:09.858Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:00:10.812Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:00:12.788Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:00:14.765Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:00:14.765Z] 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.
[2025-02-19T22:00:14.765Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:00:14.765Z] Movies recommended for you:
[2025-02-19T22:00:14.765Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:00:14.765Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:00:14.765Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16925.482 ms) ======
[2025-02-19T22:00:14.765Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-19T22:00:14.765Z] GC before operation: completed in 95.579 ms, heap usage 358.888 MB -> 54.080 MB.
[2025-02-19T22:00:17.799Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:00:19.754Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:00:22.775Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:00:24.732Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:00:26.737Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:00:27.689Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:00:29.645Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:00:30.598Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:00:30.598Z] 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.
[2025-02-19T22:00:30.598Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:00:30.598Z] Movies recommended for you:
[2025-02-19T22:00:30.598Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:00:30.598Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:00:30.598Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16162.129 ms) ======
[2025-02-19T22:00:30.598Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-19T22:00:31.551Z] GC before operation: completed in 104.446 ms, heap usage 837.038 MB -> 57.956 MB.
[2025-02-19T22:00:34.593Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:00:36.551Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:00:38.507Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:00:40.469Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:00:42.424Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:00:43.377Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:00:45.350Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:00:46.304Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:00:47.255Z] 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.
[2025-02-19T22:00:47.255Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:00:47.255Z] Movies recommended for you:
[2025-02-19T22:00:47.255Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:00:47.256Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:00:47.256Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15974.776 ms) ======
[2025-02-19T22:00:47.256Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-19T22:00:47.256Z] GC before operation: completed in 99.192 ms, heap usage 383.512 MB -> 54.121 MB.
[2025-02-19T22:00:50.289Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:00:52.244Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:00:54.205Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:00:57.226Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:00:58.728Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:00:59.683Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:01:01.637Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:01:02.616Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:01:03.572Z] 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.
[2025-02-19T22:01:03.572Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:01:03.572Z] Movies recommended for you:
[2025-02-19T22:01:03.572Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:01:03.572Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:01:03.572Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16095.782 ms) ======
[2025-02-19T22:01:03.572Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-19T22:01:03.572Z] GC before operation: completed in 95.959 ms, heap usage 357.491 MB -> 54.393 MB.
[2025-02-19T22:01:06.662Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:01:08.678Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:01:10.653Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:01:13.696Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:01:14.657Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:01:16.626Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:01:17.587Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:01:18.549Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:01:19.509Z] 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.
[2025-02-19T22:01:19.509Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:01:19.509Z] Movies recommended for you:
[2025-02-19T22:01:19.509Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:01:19.509Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:01:19.509Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15864.707 ms) ======
[2025-02-19T22:01:19.509Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-19T22:01:19.509Z] GC before operation: completed in 93.883 ms, heap usage 834.997 MB -> 58.363 MB.
[2025-02-19T22:01:22.529Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:01:24.518Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:01:26.485Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:01:29.523Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:01:30.477Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:01:31.432Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:01:33.422Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:01:34.375Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:01:35.330Z] 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.
[2025-02-19T22:01:35.330Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:01:35.331Z] Movies recommended for you:
[2025-02-19T22:01:35.331Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:01:35.331Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:01:35.331Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15874.918 ms) ======
[2025-02-19T22:01:35.331Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-19T22:01:35.331Z] GC before operation: completed in 106.843 ms, heap usage 351.340 MB -> 54.559 MB.
[2025-02-19T22:01:38.416Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:01:40.375Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:01:43.405Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:01:45.361Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:01:47.313Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:01:49.291Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:01:50.257Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:01:54.451Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:01:54.451Z] 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.
[2025-02-19T22:01:54.451Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:01:54.451Z] Movies recommended for you:
[2025-02-19T22:01:54.451Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:01:54.451Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:01:54.451Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17448.584 ms) ======
[2025-02-19T22:01:54.451Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-19T22:01:54.451Z] GC before operation: completed in 101.748 ms, heap usage 455.265 MB -> 54.667 MB.
[2025-02-19T22:01:55.404Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:01:58.416Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:02:00.391Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:02:03.418Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:02:04.380Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:02:06.344Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:02:07.294Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:02:09.254Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:02:09.254Z] 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.
[2025-02-19T22:02:09.254Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:02:09.254Z] Movies recommended for you:
[2025-02-19T22:02:09.254Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:02:09.254Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:02:09.254Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16490.618 ms) ======
[2025-02-19T22:02:09.254Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-19T22:02:09.254Z] GC before operation: completed in 90.800 ms, heap usage 471.435 MB -> 54.381 MB.
[2025-02-19T22:02:12.261Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:02:14.679Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:02:15.628Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:02:17.582Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:02:18.535Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:02:19.485Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:02:21.437Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:02:22.386Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:02:22.386Z] 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.
[2025-02-19T22:02:22.386Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:02:22.386Z] Movies recommended for you:
[2025-02-19T22:02:22.386Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:02:22.386Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:02:22.386Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12994.148 ms) ======
[2025-02-19T22:02:22.386Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-19T22:02:22.386Z] GC before operation: completed in 91.165 ms, heap usage 518.372 MB -> 57.965 MB.
[2025-02-19T22:02:24.423Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:02:26.833Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:02:27.784Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:02:29.739Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:02:30.691Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:02:32.636Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:02:33.610Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:02:34.568Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:02:34.568Z] 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.
[2025-02-19T22:02:34.568Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:02:34.568Z] Movies recommended for you:
[2025-02-19T22:02:34.568Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:02:34.568Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:02:34.568Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12115.675 ms) ======
[2025-02-19T22:02:34.568Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-19T22:02:34.568Z] GC before operation: completed in 92.035 ms, heap usage 314.552 MB -> 54.744 MB.
[2025-02-19T22:02:36.525Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:02:38.479Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:02:40.438Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:02:42.398Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:02:43.347Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:02:44.299Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:02:45.248Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:02:46.205Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:02:47.165Z] 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.
[2025-02-19T22:02:47.165Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:02:47.166Z] Movies recommended for you:
[2025-02-19T22:02:47.166Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:02:47.166Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:02:47.166Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12147.486 ms) ======
[2025-02-19T22:02:47.166Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-19T22:02:47.166Z] GC before operation: completed in 94.082 ms, heap usage 458.921 MB -> 54.520 MB.
[2025-02-19T22:02:49.121Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:02:51.090Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:02:53.051Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:02:55.037Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:02:55.991Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:02:57.955Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:02:58.908Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:02:59.860Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:03:00.813Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-19T22:03:00.814Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:03:00.814Z] Movies recommended for you:
[2025-02-19T22:03:00.814Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:03:00.814Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:03:00.814Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13571.874 ms) ======
[2025-02-19T22:03:00.814Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-19T22:03:00.814Z] GC before operation: completed in 89.768 ms, heap usage 164.326 MB -> 56.834 MB.
[2025-02-19T22:03:02.769Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:03:05.774Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:03:07.733Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:03:09.681Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:03:10.640Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:03:11.588Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:03:13.536Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:03:14.493Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:03:14.493Z] 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.
[2025-02-19T22:03:14.493Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:03:14.493Z] Movies recommended for you:
[2025-02-19T22:03:14.493Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:03:14.493Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:03:14.493Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14096.145 ms) ======
[2025-02-19T22:03:14.493Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-19T22:03:15.444Z] GC before operation: completed in 184.243 ms, heap usage 1.345 GB -> 61.160 MB.
[2025-02-19T22:03:17.394Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:03:20.466Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:03:22.424Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:03:24.484Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:03:25.441Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:03:26.398Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:03:28.373Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:03:29.323Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:03:29.323Z] 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.
[2025-02-19T22:03:29.323Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:03:29.323Z] Movies recommended for you:
[2025-02-19T22:03:29.323Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:03:29.323Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:03:29.323Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14682.307 ms) ======
[2025-02-19T22:03:29.323Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-19T22:03:29.323Z] GC before operation: completed in 109.399 ms, heap usage 1.098 GB -> 60.735 MB.
[2025-02-19T22:03:32.345Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:03:34.295Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:03:37.329Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:03:39.394Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:03:40.342Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:03:42.293Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:03:43.241Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:03:44.196Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:03:45.203Z] 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.
[2025-02-19T22:03:45.203Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:03:45.203Z] Movies recommended for you:
[2025-02-19T22:03:45.203Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:03:45.203Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:03:45.203Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15692.498 ms) ======
[2025-02-19T22:03:45.203Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-19T22:03:45.203Z] GC before operation: completed in 122.565 ms, heap usage 1.858 GB -> 64.290 MB.
[2025-02-19T22:03:48.228Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:03:51.243Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:03:53.204Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:03:56.213Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:03:57.163Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:03:59.112Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:04:00.083Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:04:02.034Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:04:02.034Z] 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.
[2025-02-19T22:04:02.034Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:04:02.034Z] Movies recommended for you:
[2025-02-19T22:04:02.034Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:04:02.034Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:04:02.034Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16435.977 ms) ======
[2025-02-19T22:04:02.034Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-19T22:04:02.034Z] GC before operation: completed in 102.700 ms, heap usage 1.163 GB -> 61.603 MB.
[2025-02-19T22:04:05.081Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:04:07.035Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:04:10.046Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:04:12.410Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:04:13.374Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:04:14.353Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:04:16.304Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:04:17.254Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:04:18.206Z] 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.
[2025-02-19T22:04:18.206Z] The best model improves the baseline by 14.43%.
[2025-02-19T22:04:18.206Z] Movies recommended for you:
[2025-02-19T22:04:18.206Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:04:18.206Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:04:18.206Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15789.654 ms) ======
[2025-02-19T22:04:20.158Z] -----------------------------------
[2025-02-19T22:04:20.158Z] renaissance-movie-lens_0_PASSED
[2025-02-19T22:04:20.158Z] -----------------------------------
[2025-02-19T22:04:20.158Z]
[2025-02-19T22:04:20.158Z] TEST TEARDOWN:
[2025-02-19T22:04:20.158Z] Nothing to be done for teardown.
[2025-02-19T22:04:20.158Z] renaissance-movie-lens_0 Finish Time: Wed Feb 19 22:04:19 2025 Epoch Time (ms): 1740002659286