renaissance-movie-lens_0
[2024-08-16T18:04:26.919Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T18:04:26.919Z] ===============================================
[2024-08-16T18:04:26.919Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 18:04:26 2024 Epoch Time (ms): 1723831466353
[2024-08-16T18:04:26.919Z] variation: NoOptions
[2024-08-16T18:04:26.919Z] JVM_OPTIONS:
[2024-08-16T18:04:26.919Z] { \
[2024-08-16T18:04:26.919Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T18:04:26.919Z] echo "Nothing to be done for setup."; \
[2024-08-16T18:04:26.919Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238307847277/renaissance-movie-lens_0"; \
[2024-08-16T18:04:26.919Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238307847277/renaissance-movie-lens_0"; \
[2024-08-16T18:04:26.919Z] echo ""; echo "TESTING:"; \
[2024-08-16T18:04:26.919Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_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_aarch64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238307847277/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T18:04:26.919Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238307847277/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T18:04:26.919Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T18:04:26.919Z] echo "Nothing to be done for teardown."; \
[2024-08-16T18:04:26.919Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238307847277/TestTargetResult";
[2024-08-16T18:04:26.919Z]
[2024-08-16T18:04:26.919Z] TEST SETUP:
[2024-08-16T18:04:26.919Z] Nothing to be done for setup.
[2024-08-16T18:04:26.919Z]
[2024-08-16T18:04:26.919Z] TESTING:
[2024-08-16T18:04:29.892Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T18:04:31.817Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-16T18:04:34.832Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T18:04:34.832Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T18:04:34.832Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T18:04:34.832Z] GC before operation: completed in 64.046 ms, heap usage 174.035 MB -> 37.195 MB.
[2024-08-16T18:04:40.249Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:04:43.226Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:04:46.205Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:04:48.143Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:04:49.085Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:04:51.751Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:04:52.696Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:04:53.635Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:04:53.635Z] 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.
[2024-08-16T18:04:53.635Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:04:54.585Z] Movies recommended for you:
[2024-08-16T18:04:54.585Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:04:54.585Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:04:54.585Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (19346.758 ms) ======
[2024-08-16T18:04:54.585Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T18:04:54.585Z] GC before operation: completed in 133.535 ms, heap usage 400.135 MB -> 50.632 MB.
[2024-08-16T18:04:56.512Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:04:58.443Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:05:00.422Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:05:02.378Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:05:04.304Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:05:05.242Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:05:06.183Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:05:08.139Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:05:08.139Z] 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.
[2024-08-16T18:05:08.139Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:05:08.139Z] Movies recommended for you:
[2024-08-16T18:05:08.139Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:05:08.139Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:05:08.139Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (13787.505 ms) ======
[2024-08-16T18:05:08.139Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T18:05:08.139Z] GC before operation: completed in 136.578 ms, heap usage 234.737 MB -> 54.248 MB.
[2024-08-16T18:05:10.193Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:05:12.119Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:05:14.245Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:05:16.173Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:05:18.137Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:05:19.075Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:05:20.162Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:05:21.099Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:05:21.099Z] 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.
[2024-08-16T18:05:21.099Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:05:21.099Z] Movies recommended for you:
[2024-08-16T18:05:21.099Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:05:21.099Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:05:21.099Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13048.700 ms) ======
[2024-08-16T18:05:21.099Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T18:05:21.099Z] GC before operation: completed in 123.416 ms, heap usage 271.622 MB -> 51.346 MB.
[2024-08-16T18:05:23.140Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:05:25.072Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:05:26.999Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:05:28.924Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:05:29.862Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:05:30.801Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:05:31.755Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:05:32.695Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:05:32.695Z] 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.
[2024-08-16T18:05:32.695Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:05:32.695Z] Movies recommended for you:
[2024-08-16T18:05:32.695Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:05:32.695Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:05:32.695Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (11724.658 ms) ======
[2024-08-16T18:05:32.695Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T18:05:33.636Z] GC before operation: completed in 119.832 ms, heap usage 310.081 MB -> 51.715 MB.
[2024-08-16T18:05:35.565Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:05:36.503Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:05:38.430Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:05:40.358Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:05:41.297Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:05:42.264Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:05:43.202Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:05:45.129Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:05:45.129Z] 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.
[2024-08-16T18:05:45.129Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:05:45.129Z] Movies recommended for you:
[2024-08-16T18:05:45.129Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:05:45.129Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:05:45.129Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (11690.521 ms) ======
[2024-08-16T18:05:45.129Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T18:05:45.129Z] GC before operation: completed in 133.255 ms, heap usage 235.710 MB -> 51.894 MB.
[2024-08-16T18:05:47.058Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:05:48.987Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:05:49.927Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:05:51.858Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:05:52.797Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:05:53.735Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:05:55.663Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:05:56.603Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:05:56.604Z] 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.
[2024-08-16T18:05:56.604Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:05:56.604Z] Movies recommended for you:
[2024-08-16T18:05:56.604Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:05:56.604Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:05:56.604Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (11523.428 ms) ======
[2024-08-16T18:05:56.604Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T18:05:56.604Z] GC before operation: completed in 133.768 ms, heap usage 530.120 MB -> 55.290 MB.
[2024-08-16T18:05:58.536Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:06:00.465Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:06:02.395Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:06:04.323Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:06:05.265Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:06:06.206Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:06:07.145Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:06:08.083Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:06:08.084Z] 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.
[2024-08-16T18:06:08.084Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:06:08.084Z] Movies recommended for you:
[2024-08-16T18:06:08.084Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:06:08.084Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:06:08.084Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (11624.217 ms) ======
[2024-08-16T18:06:08.084Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T18:06:08.084Z] GC before operation: completed in 125.712 ms, heap usage 169.518 MB -> 51.946 MB.
[2024-08-16T18:06:10.028Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:06:11.964Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:06:13.890Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:06:15.844Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:06:16.787Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:06:17.726Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:06:18.705Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:06:19.646Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:06:19.646Z] 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.
[2024-08-16T18:06:19.646Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:06:19.646Z] Movies recommended for you:
[2024-08-16T18:06:19.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:06:19.646Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:06:19.646Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (11438.169 ms) ======
[2024-08-16T18:06:19.646Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T18:06:19.646Z] GC before operation: completed in 125.021 ms, heap usage 252.405 MB -> 52.213 MB.
[2024-08-16T18:06:21.738Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:06:23.677Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:06:25.609Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:06:26.549Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:06:27.590Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:06:29.524Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:06:30.463Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:06:31.403Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:06:31.403Z] 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.
[2024-08-16T18:06:31.403Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:06:31.403Z] Movies recommended for you:
[2024-08-16T18:06:31.403Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:06:31.403Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:06:31.403Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11386.392 ms) ======
[2024-08-16T18:06:31.403Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T18:06:31.403Z] GC before operation: completed in 124.438 ms, heap usage 227.545 MB -> 52.037 MB.
[2024-08-16T18:06:33.332Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:06:35.260Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:06:37.188Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:06:38.126Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:06:40.055Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:06:40.993Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:06:41.933Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:06:42.871Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:06:42.871Z] 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.
[2024-08-16T18:06:42.871Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:06:42.871Z] Movies recommended for you:
[2024-08-16T18:06:42.871Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:06:42.871Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:06:42.871Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11509.280 ms) ======
[2024-08-16T18:06:42.871Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T18:06:42.871Z] GC before operation: completed in 146.175 ms, heap usage 181.766 MB -> 52.147 MB.
[2024-08-16T18:06:44.799Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:06:46.727Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:06:48.658Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:06:50.588Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:06:51.527Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:06:52.465Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:06:53.404Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:06:54.342Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:06:54.342Z] 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.
[2024-08-16T18:06:54.342Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:06:54.342Z] Movies recommended for you:
[2024-08-16T18:06:54.342Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:06:54.342Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:06:54.342Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11300.603 ms) ======
[2024-08-16T18:06:54.342Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T18:06:54.342Z] GC before operation: completed in 136.806 ms, heap usage 164.885 MB -> 51.838 MB.
[2024-08-16T18:06:56.273Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:06:58.202Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:07:00.135Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:07:01.073Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:07:02.999Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:07:03.939Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:07:04.877Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:07:05.816Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:07:05.816Z] 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.
[2024-08-16T18:07:05.816Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:07:05.816Z] Movies recommended for you:
[2024-08-16T18:07:05.816Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:07:05.816Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:07:05.816Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11467.952 ms) ======
[2024-08-16T18:07:05.816Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T18:07:05.816Z] GC before operation: completed in 129.893 ms, heap usage 225.872 MB -> 52.128 MB.
[2024-08-16T18:07:07.749Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:07:09.800Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:07:11.728Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:07:13.655Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:07:14.601Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:07:15.540Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:07:16.480Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:07:17.417Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:07:17.417Z] 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.
[2024-08-16T18:07:17.417Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:07:18.356Z] Movies recommended for you:
[2024-08-16T18:07:18.356Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:07:18.356Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:07:18.356Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11716.395 ms) ======
[2024-08-16T18:07:18.356Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T18:07:18.356Z] GC before operation: completed in 138.716 ms, heap usage 198.846 MB -> 52.328 MB.
[2024-08-16T18:07:20.283Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:07:21.224Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:07:23.179Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:07:25.107Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:07:26.045Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:07:26.984Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:07:27.922Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:07:28.860Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:07:29.798Z] 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.
[2024-08-16T18:07:29.798Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:07:29.798Z] Movies recommended for you:
[2024-08-16T18:07:29.798Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:07:29.798Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:07:29.798Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11438.838 ms) ======
[2024-08-16T18:07:29.798Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T18:07:29.798Z] GC before operation: completed in 136.723 ms, heap usage 155.083 MB -> 51.992 MB.
[2024-08-16T18:07:31.725Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:07:33.655Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:07:34.595Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:07:36.521Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:07:37.462Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:07:38.401Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:07:39.339Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:07:41.267Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:07:41.267Z] 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.
[2024-08-16T18:07:41.267Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:07:41.267Z] Movies recommended for you:
[2024-08-16T18:07:41.267Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:07:41.267Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:07:41.267Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11401.705 ms) ======
[2024-08-16T18:07:41.267Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T18:07:41.267Z] GC before operation: completed in 133.396 ms, heap usage 298.422 MB -> 52.243 MB.
[2024-08-16T18:07:43.195Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:07:45.148Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:07:46.097Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:07:48.427Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:07:49.391Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:07:50.334Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:07:51.274Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:07:52.224Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:07:52.224Z] 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.
[2024-08-16T18:07:52.224Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:07:53.193Z] Movies recommended for you:
[2024-08-16T18:07:53.193Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:07:53.193Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:07:53.193Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11514.861 ms) ======
[2024-08-16T18:07:53.193Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T18:07:53.193Z] GC before operation: completed in 136.180 ms, heap usage 544.569 MB -> 55.716 MB.
[2024-08-16T18:07:55.122Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:07:56.062Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:07:57.991Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:07:59.918Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:08:00.857Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:08:01.797Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:08:02.737Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:08:03.677Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:08:04.616Z] 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.
[2024-08-16T18:08:04.616Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:08:04.616Z] Movies recommended for you:
[2024-08-16T18:08:04.616Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:08:04.616Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:08:04.616Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (11404.310 ms) ======
[2024-08-16T18:08:04.616Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T18:08:04.616Z] GC before operation: completed in 139.262 ms, heap usage 470.280 MB -> 52.297 MB.
[2024-08-16T18:08:06.718Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:08:07.658Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:08:09.588Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:08:11.518Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:08:12.462Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:08:13.402Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:08:14.344Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:08:15.324Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:08:16.280Z] 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.
[2024-08-16T18:08:16.280Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:08:16.280Z] Movies recommended for you:
[2024-08-16T18:08:16.280Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:08:16.280Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:08:16.280Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11592.967 ms) ======
[2024-08-16T18:08:16.280Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T18:08:16.280Z] GC before operation: completed in 149.390 ms, heap usage 198.459 MB -> 52.200 MB.
[2024-08-16T18:08:18.215Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:08:20.144Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:08:21.084Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:08:23.152Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:08:24.090Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:08:25.030Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:08:25.969Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:08:26.908Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:08:26.908Z] 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.
[2024-08-16T18:08:27.847Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:08:27.847Z] Movies recommended for you:
[2024-08-16T18:08:27.847Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:08:27.847Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:08:27.847Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11319.039 ms) ======
[2024-08-16T18:08:27.847Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T18:08:27.847Z] GC before operation: completed in 135.139 ms, heap usage 155.325 MB -> 52.336 MB.
[2024-08-16T18:08:29.773Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T18:08:30.712Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T18:08:32.678Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T18:08:34.613Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T18:08:35.552Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T18:08:36.490Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T18:08:37.429Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T18:08:38.367Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T18:08:39.304Z] 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.
[2024-08-16T18:08:39.305Z] The best model improves the baseline by 14.43%.
[2024-08-16T18:08:39.305Z] Movies recommended for you:
[2024-08-16T18:08:39.305Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T18:08:39.305Z] There is no way to check that no silent failure occurred.
[2024-08-16T18:08:39.305Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11484.590 ms) ======
[2024-08-16T18:08:40.244Z] -----------------------------------
[2024-08-16T18:08:40.244Z] renaissance-movie-lens_0_PASSED
[2024-08-16T18:08:40.244Z] -----------------------------------
[2024-08-16T18:08:40.244Z]
[2024-08-16T18:08:40.244Z] TEST TEARDOWN:
[2024-08-16T18:08:40.244Z] Nothing to be done for teardown.
[2024-08-16T18:08:40.244Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 18:08:39 2024 Epoch Time (ms): 1723831719644