renaissance-movie-lens_0
[2024-08-08T08:47:25.155Z] Running test renaissance-movie-lens_0 ...
[2024-08-08T08:47:25.155Z] ===============================================
[2024-08-08T08:47:25.155Z] renaissance-movie-lens_0 Start Time: Thu Aug 8 08:47:24 2024 Epoch Time (ms): 1723106844026
[2024-08-08T08:47:25.155Z] variation: NoOptions
[2024-08-08T08:47:25.155Z] JVM_OPTIONS:
[2024-08-08T08:47:25.155Z] { \
[2024-08-08T08:47:25.155Z] echo ""; echo "TEST SETUP:"; \
[2024-08-08T08:47:25.155Z] echo "Nothing to be done for setup."; \
[2024-08-08T08:47:25.155Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17231058336042/renaissance-movie-lens_0"; \
[2024-08-08T08:47:25.155Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17231058336042/renaissance-movie-lens_0"; \
[2024-08-08T08:47:25.155Z] echo ""; echo "TESTING:"; \
[2024-08-08T08:47:25.155Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/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_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17231058336042/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-08T08:47:25.155Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17231058336042/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-08T08:47:25.155Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-08T08:47:25.155Z] echo "Nothing to be done for teardown."; \
[2024-08-08T08:47:25.155Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17231058336042/TestTargetResult";
[2024-08-08T08:47:25.155Z]
[2024-08-08T08:47:25.155Z] TEST SETUP:
[2024-08-08T08:47:25.155Z] Nothing to be done for setup.
[2024-08-08T08:47:25.155Z]
[2024-08-08T08:47:25.155Z] TESTING:
[2024-08-08T08:47:29.554Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-08T08:47:31.993Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-08-08T08:47:36.393Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-08T08:47:36.393Z] Training: 60056, validation: 20285, test: 19854
[2024-08-08T08:47:36.393Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-08T08:47:36.393Z] GC before operation: completed in 61.148 ms, heap usage 55.724 MB -> 38.080 MB.
[2024-08-08T08:47:43.174Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:47:47.572Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:47:50.940Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:47:55.333Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:47:56.897Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:47:59.333Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:48:01.289Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:48:03.698Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:48:03.698Z] 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.
[2024-08-08T08:48:03.698Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:48:03.698Z] Movies recommended for you:
[2024-08-08T08:48:03.698Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:48:03.698Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:48:03.698Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26888.795 ms) ======
[2024-08-08T08:48:03.698Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-08T08:48:03.698Z] GC before operation: completed in 112.119 ms, heap usage 126.999 MB -> 50.310 MB.
[2024-08-08T08:48:07.491Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:48:10.034Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:48:13.419Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:48:16.791Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:48:19.231Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:48:20.798Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:48:23.239Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:48:24.803Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:48:25.558Z] 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.
[2024-08-08T08:48:25.558Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:48:25.558Z] Movies recommended for you:
[2024-08-08T08:48:25.558Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:48:25.558Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:48:25.558Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21892.124 ms) ======
[2024-08-08T08:48:25.558Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-08T08:48:25.558Z] GC before operation: completed in 116.808 ms, heap usage 335.256 MB -> 51.857 MB.
[2024-08-08T08:48:29.011Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:48:32.372Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:48:35.741Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:48:38.173Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:48:40.606Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:48:42.165Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:48:44.620Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:48:46.188Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:48:46.188Z] 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.
[2024-08-08T08:48:46.188Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:48:46.943Z] Movies recommended for you:
[2024-08-08T08:48:46.943Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:48:46.943Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:48:46.943Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20865.387 ms) ======
[2024-08-08T08:48:46.943Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-08T08:48:46.943Z] GC before operation: completed in 109.723 ms, heap usage 279.335 MB -> 55.435 MB.
[2024-08-08T08:48:50.320Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:48:52.749Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:48:56.116Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:48:59.489Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:49:01.059Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:49:02.627Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:49:05.058Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:49:06.641Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:49:07.397Z] 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.
[2024-08-08T08:49:07.397Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:49:07.397Z] Movies recommended for you:
[2024-08-08T08:49:07.397Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:49:07.397Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:49:07.397Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20602.838 ms) ======
[2024-08-08T08:49:07.397Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-08T08:49:07.397Z] GC before operation: completed in 117.993 ms, heap usage 281.335 MB -> 52.428 MB.
[2024-08-08T08:49:10.825Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:49:13.256Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:49:16.628Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:49:20.008Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:49:21.575Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:49:23.146Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:49:25.580Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:49:27.150Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:49:27.907Z] 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.
[2024-08-08T08:49:27.907Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:49:27.907Z] Movies recommended for you:
[2024-08-08T08:49:27.907Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:49:27.907Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:49:27.907Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20410.333 ms) ======
[2024-08-08T08:49:27.907Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-08T08:49:27.907Z] GC before operation: completed in 127.592 ms, heap usage 282.990 MB -> 52.593 MB.
[2024-08-08T08:49:31.289Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:49:34.667Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:49:37.106Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:49:40.478Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:49:42.047Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:49:44.483Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:49:46.050Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:49:48.504Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:49:48.504Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-08T08:49:48.504Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:49:48.504Z] Movies recommended for you:
[2024-08-08T08:49:48.504Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:49:48.504Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:49:48.504Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20549.529 ms) ======
[2024-08-08T08:49:48.504Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-08T08:49:48.504Z] GC before operation: completed in 124.458 ms, heap usage 310.847 MB -> 52.652 MB.
[2024-08-08T08:49:51.869Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:49:55.244Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:49:58.628Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:50:01.063Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:50:02.628Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:50:05.058Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:50:06.622Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:50:09.191Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:50:09.191Z] 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.
[2024-08-08T08:50:09.191Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:50:09.191Z] Movies recommended for you:
[2024-08-08T08:50:09.191Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:50:09.191Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:50:09.191Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20429.555 ms) ======
[2024-08-08T08:50:09.191Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-08T08:50:09.191Z] GC before operation: completed in 119.523 ms, heap usage 508.961 MB -> 56.194 MB.
[2024-08-08T08:50:12.566Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:50:14.995Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:50:18.365Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:50:21.747Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:50:23.311Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:50:24.886Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:50:27.327Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:50:28.890Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:50:29.646Z] 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.
[2024-08-08T08:50:29.646Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:50:29.646Z] Movies recommended for you:
[2024-08-08T08:50:29.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:50:29.646Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:50:29.646Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20343.377 ms) ======
[2024-08-08T08:50:29.646Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-08T08:50:29.646Z] GC before operation: completed in 119.318 ms, heap usage 221.966 MB -> 53.037 MB.
[2024-08-08T08:50:33.023Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:50:35.451Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:50:38.996Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:50:42.376Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:50:43.948Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:50:45.515Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:50:47.954Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:50:49.534Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:50:49.534Z] 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.
[2024-08-08T08:50:49.534Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:50:50.290Z] Movies recommended for you:
[2024-08-08T08:50:50.290Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:50:50.290Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:50:50.290Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20297.672 ms) ======
[2024-08-08T08:50:50.290Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-08T08:50:50.290Z] GC before operation: completed in 134.067 ms, heap usage 301.465 MB -> 52.904 MB.
[2024-08-08T08:50:53.667Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:50:56.099Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:50:59.475Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:51:02.841Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:51:04.403Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:51:06.105Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:51:08.546Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:51:10.209Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:51:10.209Z] 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.
[2024-08-08T08:51:10.209Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:51:10.209Z] Movies recommended for you:
[2024-08-08T08:51:10.209Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:51:10.209Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:51:10.209Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20389.044 ms) ======
[2024-08-08T08:51:10.209Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-08T08:51:10.968Z] GC before operation: completed in 121.139 ms, heap usage 378.935 MB -> 53.032 MB.
[2024-08-08T08:51:13.410Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:51:16.802Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:51:20.168Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:51:22.608Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:51:25.036Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:51:26.606Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:51:28.169Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:51:30.602Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:51:30.602Z] 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.
[2024-08-08T08:51:30.602Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:51:30.602Z] Movies recommended for you:
[2024-08-08T08:51:30.602Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:51:30.602Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:51:30.602Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20230.749 ms) ======
[2024-08-08T08:51:30.602Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-08T08:51:31.359Z] GC before operation: completed in 141.707 ms, heap usage 523.681 MB -> 56.125 MB.
[2024-08-08T08:51:33.790Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:51:37.159Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:51:40.545Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:51:42.985Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:51:45.422Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:51:46.996Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:51:48.560Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:51:51.001Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:51:51.001Z] 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.
[2024-08-08T08:51:51.001Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:51:51.001Z] Movies recommended for you:
[2024-08-08T08:51:51.001Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:51:51.001Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:51:51.001Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20267.421 ms) ======
[2024-08-08T08:51:51.001Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-08T08:51:51.759Z] GC before operation: completed in 141.753 ms, heap usage 212.922 MB -> 52.885 MB.
[2024-08-08T08:51:54.194Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:51:57.565Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:52:00.944Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:52:04.314Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:52:05.906Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:52:07.475Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:52:09.063Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:52:11.511Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:52:11.511Z] 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.
[2024-08-08T08:52:11.511Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:52:11.511Z] Movies recommended for you:
[2024-08-08T08:52:11.511Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:52:11.511Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:52:11.511Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20353.065 ms) ======
[2024-08-08T08:52:11.511Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-08T08:52:11.511Z] GC before operation: completed in 116.507 ms, heap usage 278.703 MB -> 53.075 MB.
[2024-08-08T08:52:14.890Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:52:18.260Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:52:21.651Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:52:24.115Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:52:26.580Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:52:28.163Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:52:29.730Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:52:31.302Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:52:32.058Z] 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.
[2024-08-08T08:52:32.058Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:52:32.058Z] Movies recommended for you:
[2024-08-08T08:52:32.058Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:52:32.058Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:52:32.058Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20248.092 ms) ======
[2024-08-08T08:52:32.058Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-08T08:52:32.058Z] GC before operation: completed in 120.320 ms, heap usage 302.901 MB -> 52.864 MB.
[2024-08-08T08:52:35.494Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:52:38.861Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:52:41.306Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:52:44.675Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:52:46.249Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:52:47.832Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:52:50.261Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:52:51.832Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:52:52.590Z] 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.
[2024-08-08T08:52:52.590Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:52:52.590Z] Movies recommended for you:
[2024-08-08T08:52:52.590Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:52:52.590Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:52:52.590Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20248.723 ms) ======
[2024-08-08T08:52:52.590Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-08T08:52:52.590Z] GC before operation: completed in 120.614 ms, heap usage 301.350 MB -> 53.060 MB.
[2024-08-08T08:52:55.969Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:52:58.410Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:53:01.781Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:53:05.145Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:53:06.715Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:53:08.279Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:53:10.751Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:53:12.319Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:53:13.081Z] 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.
[2024-08-08T08:53:13.081Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:53:13.081Z] Movies recommended for you:
[2024-08-08T08:53:13.081Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:53:13.081Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:53:13.081Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20354.966 ms) ======
[2024-08-08T08:53:13.081Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-08T08:53:13.081Z] GC before operation: completed in 124.264 ms, heap usage 233.878 MB -> 53.074 MB.
[2024-08-08T08:53:16.461Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:53:18.911Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:53:22.288Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:53:25.661Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:53:27.230Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:53:28.794Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:53:31.239Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:53:32.807Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:53:32.807Z] 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.
[2024-08-08T08:53:32.807Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:53:32.807Z] Movies recommended for you:
[2024-08-08T08:53:32.807Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:53:32.807Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:53:33.565Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20091.408 ms) ======
[2024-08-08T08:53:33.565Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-08T08:53:33.565Z] GC before operation: completed in 112.128 ms, heap usage 328.191 MB -> 52.977 MB.
[2024-08-08T08:53:36.010Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:53:39.380Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:53:42.759Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:53:46.130Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:53:47.698Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:53:49.269Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:53:51.700Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:53:53.269Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:53:53.269Z] 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.
[2024-08-08T08:53:53.269Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:53:53.269Z] Movies recommended for you:
[2024-08-08T08:53:53.269Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:53:53.269Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:53:53.269Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20319.586 ms) ======
[2024-08-08T08:53:53.269Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-08T08:53:54.025Z] GC before operation: completed in 124.500 ms, heap usage 216.522 MB -> 52.971 MB.
[2024-08-08T08:53:56.466Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:53:59.837Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:54:03.213Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:54:05.658Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:54:08.101Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:54:09.666Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:54:11.250Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:54:13.678Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:54:13.678Z] 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.
[2024-08-08T08:54:13.678Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:54:13.678Z] Movies recommended for you:
[2024-08-08T08:54:13.678Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:54:13.678Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:54:13.678Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20094.263 ms) ======
[2024-08-08T08:54:13.678Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-08T08:54:13.678Z] GC before operation: completed in 124.168 ms, heap usage 572.082 MB -> 56.614 MB.
[2024-08-08T08:54:17.059Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T08:54:20.439Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T08:54:23.811Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T08:54:26.243Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T08:54:28.759Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T08:54:31.029Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T08:54:31.973Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T08:54:33.573Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T08:54:34.330Z] 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.
[2024-08-08T08:54:34.330Z] The best model improves the baseline by 14.43%.
[2024-08-08T08:54:34.330Z] Movies recommended for you:
[2024-08-08T08:54:34.330Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T08:54:34.330Z] There is no way to check that no silent failure occurred.
[2024-08-08T08:54:34.330Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (20365.342 ms) ======
[2024-08-08T08:54:35.085Z] -----------------------------------
[2024-08-08T08:54:35.085Z] renaissance-movie-lens_0_PASSED
[2024-08-08T08:54:35.085Z] -----------------------------------
[2024-08-08T08:54:35.085Z]
[2024-08-08T08:54:35.085Z] TEST TEARDOWN:
[2024-08-08T08:54:35.085Z] Nothing to be done for teardown.
[2024-08-08T08:54:35.085Z] renaissance-movie-lens_0 Finish Time: Thu Aug 8 08:54:34 2024 Epoch Time (ms): 1723107274514