renaissance-movie-lens_0
[2024-08-01T05:22:09.920Z] Running test renaissance-movie-lens_0 ...
[2024-08-01T05:22:09.920Z] ===============================================
[2024-08-01T05:22:09.920Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 00:22:09 2024 Epoch Time (ms): 1722489729082
[2024-08-01T05:22:09.920Z] variation: NoOptions
[2024-08-01T05:22:09.920Z] JVM_OPTIONS:
[2024-08-01T05:22:09.920Z] { \
[2024-08-01T05:22:09.920Z] echo ""; echo "TEST SETUP:"; \
[2024-08-01T05:22:09.920Z] echo "Nothing to be done for setup."; \
[2024-08-01T05:22:09.920Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224888286789/renaissance-movie-lens_0"; \
[2024-08-01T05:22:09.920Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224888286789/renaissance-movie-lens_0"; \
[2024-08-01T05:22:09.920Z] echo ""; echo "TESTING:"; \
[2024-08-01T05:22:09.920Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-11.0.25+1/bin/..//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_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224888286789/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-01T05:22:09.920Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224888286789/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-01T05:22:09.920Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-01T05:22:09.920Z] echo "Nothing to be done for teardown."; \
[2024-08-01T05:22:09.921Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224888286789/TestTargetResult";
[2024-08-01T05:22:09.921Z]
[2024-08-01T05:22:09.921Z] TEST SETUP:
[2024-08-01T05:22:09.921Z] Nothing to be done for setup.
[2024-08-01T05:22:09.921Z]
[2024-08-01T05:22:09.921Z] TESTING:
[2024-08-01T05:22:12.262Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-01T05:22:14.468Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-01T05:22:18.526Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-01T05:22:18.526Z] Training: 60056, validation: 20285, test: 19854
[2024-08-01T05:22:18.527Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-01T05:22:18.527Z] GC before operation: completed in 68.664 ms, heap usage 121.588 MB -> 37.184 MB.
[2024-08-01T05:22:27.754Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:22:30.858Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:22:34.909Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:22:38.040Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:22:40.254Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:22:42.474Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:22:44.709Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:22:46.944Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:22:46.944Z] 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.
[2024-08-01T05:22:46.944Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:22:46.944Z] Movies recommended for you:
[2024-08-01T05:22:46.944Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:22:46.944Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:22:46.944Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28713.299 ms) ======
[2024-08-01T05:22:46.944Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-01T05:22:46.944Z] GC before operation: completed in 168.672 ms, heap usage 479.337 MB -> 48.947 MB.
[2024-08-01T05:22:51.012Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:22:54.106Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:22:56.343Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:22:59.424Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:23:01.665Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:23:03.102Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:23:04.554Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:23:06.777Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:23:06.777Z] 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.
[2024-08-01T05:23:06.777Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:23:07.472Z] Movies recommended for you:
[2024-08-01T05:23:07.472Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:23:07.472Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:23:07.472Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19933.577 ms) ======
[2024-08-01T05:23:07.472Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-01T05:23:07.472Z] GC before operation: completed in 156.428 ms, heap usage 336.676 MB -> 51.031 MB.
[2024-08-01T05:23:10.564Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:23:13.656Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:23:16.754Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:23:18.988Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:23:21.261Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:23:22.722Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:23:24.962Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:23:26.380Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:23:26.380Z] 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.
[2024-08-01T05:23:26.380Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:23:27.069Z] Movies recommended for you:
[2024-08-01T05:23:27.069Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:23:27.069Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:23:27.069Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19363.352 ms) ======
[2024-08-01T05:23:27.069Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-01T05:23:27.069Z] GC before operation: completed in 114.283 ms, heap usage 71.907 MB -> 54.612 MB.
[2024-08-01T05:23:29.307Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:23:32.408Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:23:35.516Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:23:37.748Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:23:39.175Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:23:40.626Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:23:42.851Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:23:44.270Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:23:44.270Z] 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.
[2024-08-01T05:23:44.270Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:23:44.270Z] Movies recommended for you:
[2024-08-01T05:23:44.270Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:23:44.270Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:23:44.270Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17613.362 ms) ======
[2024-08-01T05:23:44.270Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-01T05:23:44.270Z] GC before operation: completed in 124.754 ms, heap usage 263.161 MB -> 51.704 MB.
[2024-08-01T05:23:47.353Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:23:50.958Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:23:53.222Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:23:56.314Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:23:57.739Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:23:59.159Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:24:00.598Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:24:02.827Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:24:02.827Z] 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.
[2024-08-01T05:24:02.827Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:24:02.827Z] Movies recommended for you:
[2024-08-01T05:24:02.827Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:24:02.827Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:24:02.827Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18247.091 ms) ======
[2024-08-01T05:24:02.827Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-01T05:24:02.827Z] GC before operation: completed in 126.157 ms, heap usage 412.499 MB -> 51.967 MB.
[2024-08-01T05:24:05.910Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:24:09.010Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:24:11.236Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:24:14.324Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:24:15.753Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:24:17.176Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:24:19.408Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:24:20.826Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:24:20.826Z] 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.
[2024-08-01T05:24:20.826Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:24:21.511Z] Movies recommended for you:
[2024-08-01T05:24:21.511Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:24:21.511Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:24:21.511Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18226.671 ms) ======
[2024-08-01T05:24:21.511Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-01T05:24:21.511Z] GC before operation: completed in 122.160 ms, heap usage 251.463 MB -> 51.829 MB.
[2024-08-01T05:24:23.738Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:24:26.823Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:24:29.053Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:24:32.157Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:24:33.594Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:24:35.027Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:24:36.449Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:24:38.667Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:24:38.668Z] 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.
[2024-08-01T05:24:38.668Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:24:38.668Z] Movies recommended for you:
[2024-08-01T05:24:38.668Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:24:38.668Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:24:38.668Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17330.678 ms) ======
[2024-08-01T05:24:38.668Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-01T05:24:38.668Z] GC before operation: completed in 116.133 ms, heap usage 461.975 MB -> 52.114 MB.
[2024-08-01T05:24:41.762Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:24:44.003Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:24:47.082Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:24:49.317Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:24:50.763Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:24:52.190Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:24:54.407Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:24:55.837Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:24:55.837Z] 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.
[2024-08-01T05:24:55.837Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:24:55.837Z] Movies recommended for you:
[2024-08-01T05:24:55.837Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:24:55.837Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:24:55.837Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17279.779 ms) ======
[2024-08-01T05:24:55.837Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-01T05:24:55.837Z] GC before operation: completed in 126.569 ms, heap usage 485.485 MB -> 55.678 MB.
[2024-08-01T05:24:58.966Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:25:02.054Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:25:04.287Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:25:07.380Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:25:08.797Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:25:10.241Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:25:11.676Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:25:13.107Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:25:13.807Z] 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.
[2024-08-01T05:25:13.807Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:25:13.807Z] Movies recommended for you:
[2024-08-01T05:25:13.807Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:25:13.807Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:25:13.807Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17660.712 ms) ======
[2024-08-01T05:25:13.807Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-01T05:25:13.807Z] GC before operation: completed in 132.158 ms, heap usage 221.352 MB -> 52.088 MB.
[2024-08-01T05:25:16.946Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:25:20.081Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:25:23.174Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:25:25.390Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:25:26.842Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:25:28.270Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:25:29.705Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:25:31.945Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:25:31.945Z] 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.
[2024-08-01T05:25:31.945Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:25:31.945Z] Movies recommended for you:
[2024-08-01T05:25:31.945Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:25:31.945Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:25:31.945Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18018.650 ms) ======
[2024-08-01T05:25:31.945Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-01T05:25:31.945Z] GC before operation: completed in 136.612 ms, heap usage 307.547 MB -> 52.273 MB.
[2024-08-01T05:25:35.049Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:25:37.293Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:25:40.386Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:25:42.625Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:25:44.064Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:25:46.274Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:25:47.710Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:25:49.141Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:25:49.141Z] 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.
[2024-08-01T05:25:49.141Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:25:49.141Z] Movies recommended for you:
[2024-08-01T05:25:49.141Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:25:49.141Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:25:49.141Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17263.433 ms) ======
[2024-08-01T05:25:49.141Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-01T05:25:49.893Z] GC before operation: completed in 126.966 ms, heap usage 453.581 MB -> 52.048 MB.
[2024-08-01T05:25:52.103Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:25:55.371Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:25:57.626Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:25:59.872Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:26:02.109Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:26:03.557Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:26:04.999Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:26:06.440Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:26:07.127Z] 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.
[2024-08-01T05:26:07.127Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:26:07.127Z] Movies recommended for you:
[2024-08-01T05:26:07.127Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:26:07.127Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:26:07.127Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17586.075 ms) ======
[2024-08-01T05:26:07.127Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-01T05:26:07.127Z] GC before operation: completed in 121.632 ms, heap usage 118.604 MB -> 52.020 MB.
[2024-08-01T05:26:10.212Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:26:12.464Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:26:15.564Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:26:17.925Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:26:19.350Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:26:21.578Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:26:22.991Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:26:24.437Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:26:25.125Z] 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.
[2024-08-01T05:26:25.125Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:26:25.125Z] Movies recommended for you:
[2024-08-01T05:26:25.125Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:26:25.125Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:26:25.125Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17735.980 ms) ======
[2024-08-01T05:26:25.125Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-01T05:26:25.125Z] GC before operation: completed in 114.331 ms, heap usage 319.607 MB -> 52.314 MB.
[2024-08-01T05:26:27.354Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:26:30.437Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:26:32.685Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:26:35.804Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:26:37.249Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:26:38.669Z] RMSE (validation) = 1.117495376637101 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:26:40.089Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:26:42.299Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:26:42.299Z] 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.
[2024-08-01T05:26:42.299Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:26:42.299Z] Movies recommended for you:
[2024-08-01T05:26:42.299Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:26:42.299Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:26:42.299Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17412.817 ms) ======
[2024-08-01T05:26:42.299Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-01T05:26:42.299Z] GC before operation: completed in 127.277 ms, heap usage 120.841 MB -> 51.933 MB.
[2024-08-01T05:26:45.403Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:26:48.498Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:26:50.814Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:26:53.067Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:26:54.530Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:26:55.976Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:26:58.213Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:26:59.646Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:26:59.646Z] 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.
[2024-08-01T05:26:59.646Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:26:59.646Z] Movies recommended for you:
[2024-08-01T05:26:59.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:26:59.646Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:26:59.646Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17148.348 ms) ======
[2024-08-01T05:26:59.646Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-01T05:26:59.646Z] GC before operation: completed in 125.263 ms, heap usage 128.274 MB -> 52.110 MB.
[2024-08-01T05:27:02.744Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:27:04.967Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:27:08.127Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:27:10.346Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:27:11.876Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:27:13.298Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:27:14.749Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:27:16.964Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:27:16.964Z] 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.
[2024-08-01T05:27:16.964Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:27:16.964Z] Movies recommended for you:
[2024-08-01T05:27:16.964Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:27:16.964Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:27:16.964Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17158.178 ms) ======
[2024-08-01T05:27:16.964Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-01T05:27:16.964Z] GC before operation: completed in 129.524 ms, heap usage 392.419 MB -> 52.385 MB.
[2024-08-01T05:27:20.067Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:27:23.170Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:27:25.383Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:27:27.610Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:27:29.029Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:27:31.262Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:27:32.695Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:27:34.127Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:27:34.127Z] 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.
[2024-08-01T05:27:34.127Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:27:34.812Z] Movies recommended for you:
[2024-08-01T05:27:34.812Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:27:34.812Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:27:34.812Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17332.584 ms) ======
[2024-08-01T05:27:34.812Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-01T05:27:34.812Z] GC before operation: completed in 137.609 ms, heap usage 441.082 MB -> 52.303 MB.
[2024-08-01T05:27:37.918Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:27:40.154Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:27:43.260Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:27:45.508Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:27:46.936Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:27:48.358Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:27:50.612Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:27:52.041Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:27:52.042Z] 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.
[2024-08-01T05:27:52.042Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:27:52.042Z] Movies recommended for you:
[2024-08-01T05:27:52.042Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:27:52.042Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:27:52.042Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17504.669 ms) ======
[2024-08-01T05:27:52.042Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-01T05:27:52.042Z] GC before operation: completed in 124.709 ms, heap usage 271.750 MB -> 52.191 MB.
[2024-08-01T05:27:55.133Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:27:57.805Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:28:00.059Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:28:02.278Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:28:03.696Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:28:05.126Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:28:07.339Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:28:08.769Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:28:09.459Z] 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.
[2024-08-01T05:28:09.459Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:28:09.459Z] Movies recommended for you:
[2024-08-01T05:28:09.459Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:28:09.459Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:28:09.459Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17017.091 ms) ======
[2024-08-01T05:28:09.459Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-01T05:28:09.459Z] GC before operation: completed in 128.523 ms, heap usage 215.709 MB -> 52.368 MB.
[2024-08-01T05:28:11.709Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:28:14.818Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:28:17.060Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:28:19.276Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:28:21.540Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:28:22.970Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:28:24.393Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:28:25.824Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:28:26.505Z] 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.
[2024-08-01T05:28:26.505Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:28:26.505Z] Movies recommended for you:
[2024-08-01T05:28:26.505Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:28:26.505Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:28:26.505Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17008.744 ms) ======
[2024-08-01T05:28:27.921Z] -----------------------------------
[2024-08-01T05:28:27.921Z] renaissance-movie-lens_0_PASSED
[2024-08-01T05:28:27.921Z] -----------------------------------
[2024-08-01T05:28:27.921Z]
[2024-08-01T05:28:27.921Z] TEST TEARDOWN:
[2024-08-01T05:28:27.921Z] Nothing to be done for teardown.
[2024-08-01T05:28:27.921Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 00:28:27 2024 Epoch Time (ms): 1722490107335