renaissance-movie-lens_0
[2024-08-16T16:48:32.864Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T16:48:32.864Z] ===============================================
[2024-08-16T16:48:32.864Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 16:48:32 2024 Epoch Time (ms): 1723826912432
[2024-08-16T16:48:32.864Z] variation: NoOptions
[2024-08-16T16:48:32.864Z] JVM_OPTIONS:
[2024-08-16T16:48:32.864Z] { \
[2024-08-16T16:48:32.864Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T16:48:32.864Z] echo "Nothing to be done for setup."; \
[2024-08-16T16:48:32.864Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238260536247/renaissance-movie-lens_0"; \
[2024-08-16T16:48:32.864Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238260536247/renaissance-movie-lens_0"; \
[2024-08-16T16:48:32.864Z] echo ""; echo "TESTING:"; \
[2024-08-16T16:48:32.864Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238260536247/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T16:48:32.864Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238260536247/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T16:48:32.864Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T16:48:32.864Z] echo "Nothing to be done for teardown."; \
[2024-08-16T16:48:32.864Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238260536247/TestTargetResult";
[2024-08-16T16:48:32.864Z]
[2024-08-16T16:48:32.864Z] TEST SETUP:
[2024-08-16T16:48:32.864Z] Nothing to be done for setup.
[2024-08-16T16:48:32.864Z]
[2024-08-16T16:48:32.864Z] TESTING:
[2024-08-16T16:48:36.965Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T16:48:38.916Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-16T16:48:43.074Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T16:48:44.014Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T16:48:44.014Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T16:48:44.014Z] GC before operation: completed in 64.682 ms, heap usage 162.922 MB -> 39.472 MB.
[2024-08-16T16:48:52.073Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:48:56.211Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:49:00.315Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:49:03.298Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:49:05.229Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:49:07.159Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:49:10.145Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:49:12.086Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:49:12.086Z] 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.
[2024-08-16T16:49:12.086Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:49:12.086Z] Movies recommended for you:
[2024-08-16T16:49:12.086Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:49:12.086Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:49:12.086Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28803.538 ms) ======
[2024-08-16T16:49:12.086Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T16:49:13.028Z] GC before operation: completed in 135.538 ms, heap usage 540.380 MB -> 56.141 MB.
[2024-08-16T16:49:16.015Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:49:19.172Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:49:22.152Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:49:25.139Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:49:27.072Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:49:29.005Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:49:30.939Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:49:32.879Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:49:32.879Z] 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.
[2024-08-16T16:49:32.879Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:49:32.879Z] Movies recommended for you:
[2024-08-16T16:49:32.879Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:49:32.879Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:49:32.879Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20377.712 ms) ======
[2024-08-16T16:49:32.879Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T16:49:32.879Z] GC before operation: completed in 105.650 ms, heap usage 651.717 MB -> 56.631 MB.
[2024-08-16T16:49:37.005Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:49:39.997Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:49:42.661Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:49:44.602Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:49:46.534Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:49:48.463Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:49:50.398Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:49:51.337Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:49:51.337Z] 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.
[2024-08-16T16:49:52.276Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:49:52.276Z] Movies recommended for you:
[2024-08-16T16:49:52.276Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:49:52.276Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:49:52.276Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18886.832 ms) ======
[2024-08-16T16:49:52.276Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T16:49:52.276Z] GC before operation: completed in 111.523 ms, heap usage 384.030 MB -> 53.634 MB.
[2024-08-16T16:49:55.258Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:49:58.240Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:50:00.174Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:50:03.160Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:50:04.099Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:50:06.036Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:50:06.978Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:50:08.910Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:50:08.910Z] 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.
[2024-08-16T16:50:08.910Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:50:08.910Z] Movies recommended for you:
[2024-08-16T16:50:08.910Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:50:08.910Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:50:08.910Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17258.090 ms) ======
[2024-08-16T16:50:08.910Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T16:50:09.949Z] GC before operation: completed in 111.425 ms, heap usage 382.513 MB -> 54.006 MB.
[2024-08-16T16:50:12.928Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:50:14.891Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:50:17.884Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:50:19.816Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:50:21.910Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:50:23.841Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:50:25.773Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:50:26.716Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:50:27.657Z] 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.
[2024-08-16T16:50:27.657Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:50:27.657Z] Movies recommended for you:
[2024-08-16T16:50:27.657Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:50:27.657Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:50:27.657Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18233.636 ms) ======
[2024-08-16T16:50:27.657Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T16:50:27.657Z] GC before operation: completed in 119.521 ms, heap usage 1.164 GB -> 61.834 MB.
[2024-08-16T16:50:30.667Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:50:33.312Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:50:36.296Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:50:38.229Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:50:40.165Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:50:42.097Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:50:43.041Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:50:44.974Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:50:44.974Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-16T16:50:44.974Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:50:44.974Z] Movies recommended for you:
[2024-08-16T16:50:44.974Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:50:44.974Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:50:44.974Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17188.309 ms) ======
[2024-08-16T16:50:44.974Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T16:50:44.974Z] GC before operation: completed in 183.808 ms, heap usage 1.219 GB -> 60.949 MB.
[2024-08-16T16:50:47.972Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:50:50.974Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:50:52.936Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:50:55.923Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:50:56.864Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:50:57.804Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:50:59.763Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:51:00.704Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:51:00.704Z] 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.
[2024-08-16T16:51:00.704Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:51:00.704Z] Movies recommended for you:
[2024-08-16T16:51:00.704Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:51:00.704Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:51:00.704Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15833.499 ms) ======
[2024-08-16T16:51:00.704Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T16:51:00.704Z] GC before operation: completed in 105.374 ms, heap usage 1.242 GB -> 60.576 MB.
[2024-08-16T16:51:03.687Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:51:05.617Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:51:08.655Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:51:10.584Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:51:12.513Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:51:13.453Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:51:14.391Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:51:16.320Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:51:16.320Z] 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.
[2024-08-16T16:51:16.320Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:51:16.320Z] Movies recommended for you:
[2024-08-16T16:51:16.320Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:51:16.320Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:51:16.320Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15263.693 ms) ======
[2024-08-16T16:51:16.320Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T16:51:16.320Z] GC before operation: completed in 114.562 ms, heap usage 851.207 MB -> 62.963 MB.
[2024-08-16T16:51:19.298Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:51:21.243Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:51:23.174Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:51:26.154Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:51:27.093Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:51:28.033Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:51:29.962Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:51:30.903Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:51:30.903Z] 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.
[2024-08-16T16:51:30.903Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:51:30.903Z] Movies recommended for you:
[2024-08-16T16:51:30.903Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:51:30.903Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:51:30.903Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14694.916 ms) ======
[2024-08-16T16:51:30.903Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T16:51:30.903Z] GC before operation: completed in 106.166 ms, heap usage 1.160 GB -> 60.554 MB.
[2024-08-16T16:51:33.882Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:51:35.813Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:51:38.797Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:51:40.728Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:51:42.109Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:51:43.049Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:51:43.989Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:51:45.923Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:51:45.923Z] 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.
[2024-08-16T16:51:45.923Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:51:45.923Z] Movies recommended for you:
[2024-08-16T16:51:45.923Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:51:45.923Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:51:45.923Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14588.581 ms) ======
[2024-08-16T16:51:45.923Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T16:51:45.923Z] GC before operation: completed in 105.846 ms, heap usage 795.323 MB -> 61.367 MB.
[2024-08-16T16:51:47.850Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:51:50.826Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:51:52.755Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:51:54.694Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:51:55.635Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:51:56.575Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:51:58.503Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:51:59.442Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:51:59.442Z] 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.
[2024-08-16T16:51:59.442Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:51:59.442Z] Movies recommended for you:
[2024-08-16T16:51:59.442Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:51:59.442Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:51:59.442Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13848.178 ms) ======
[2024-08-16T16:51:59.442Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T16:52:00.381Z] GC before operation: completed in 100.216 ms, heap usage 722.836 MB -> 60.001 MB.
[2024-08-16T16:52:02.312Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:52:04.239Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:52:06.169Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:52:08.099Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:52:10.026Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:52:10.964Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:52:11.902Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:52:12.840Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:52:13.780Z] 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.
[2024-08-16T16:52:13.780Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:52:13.780Z] Movies recommended for you:
[2024-08-16T16:52:13.780Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:52:13.780Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:52:13.780Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13694.169 ms) ======
[2024-08-16T16:52:13.780Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T16:52:13.780Z] GC before operation: completed in 99.886 ms, heap usage 232.193 MB -> 56.730 MB.
[2024-08-16T16:52:15.710Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:52:17.640Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:52:19.569Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:52:21.581Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:52:22.520Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:52:24.447Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:52:25.386Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:52:26.326Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:52:26.326Z] 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.
[2024-08-16T16:52:26.326Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:52:27.267Z] Movies recommended for you:
[2024-08-16T16:52:27.267Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:52:27.267Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:52:27.267Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13136.527 ms) ======
[2024-08-16T16:52:27.267Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T16:52:27.267Z] GC before operation: completed in 99.830 ms, heap usage 561.075 MB -> 57.952 MB.
[2024-08-16T16:52:29.196Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:52:31.138Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:52:33.070Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:52:35.001Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:52:36.934Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:52:37.873Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:52:38.813Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:52:39.754Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:52:39.754Z] 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.
[2024-08-16T16:52:39.754Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:52:39.754Z] Movies recommended for you:
[2024-08-16T16:52:39.754Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:52:39.754Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:52:39.754Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13113.838 ms) ======
[2024-08-16T16:52:39.754Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T16:52:39.754Z] GC before operation: completed in 102.670 ms, heap usage 1.991 GB -> 59.179 MB.
[2024-08-16T16:52:42.377Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:52:44.305Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:52:46.236Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:52:47.179Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:52:49.113Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:52:50.053Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:52:50.993Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:52:51.933Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:52:51.933Z] 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.
[2024-08-16T16:52:51.933Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:52:51.933Z] Movies recommended for you:
[2024-08-16T16:52:51.933Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:52:51.933Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:52:51.933Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11799.445 ms) ======
[2024-08-16T16:52:51.933Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T16:52:51.933Z] GC before operation: completed in 132.582 ms, heap usage 1.632 GB -> 62.748 MB.
[2024-08-16T16:52:53.875Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:52:55.813Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:52:57.744Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:52:59.675Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:53:00.616Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:53:01.556Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:53:02.497Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:53:03.439Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:53:03.439Z] 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.
[2024-08-16T16:53:03.439Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:53:03.439Z] Movies recommended for you:
[2024-08-16T16:53:03.439Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:53:03.439Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:53:03.439Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11618.238 ms) ======
[2024-08-16T16:53:03.439Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T16:53:03.439Z] GC before operation: completed in 95.676 ms, heap usage 1.044 GB -> 63.124 MB.
[2024-08-16T16:53:05.367Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:53:07.298Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:53:09.232Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:53:11.163Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:53:12.104Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:53:13.047Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:53:14.979Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:53:15.920Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:53:15.920Z] 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.
[2024-08-16T16:53:15.920Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:53:15.920Z] Movies recommended for you:
[2024-08-16T16:53:15.920Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:53:15.920Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:53:15.920Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12344.599 ms) ======
[2024-08-16T16:53:15.920Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T16:53:15.920Z] GC before operation: completed in 136.139 ms, heap usage 825.486 MB -> 60.397 MB.
[2024-08-16T16:53:18.910Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:53:20.840Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:53:22.774Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:53:24.706Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:53:25.648Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:53:26.588Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:53:27.531Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:53:28.474Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:53:28.474Z] 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.
[2024-08-16T16:53:28.474Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:53:28.474Z] Movies recommended for you:
[2024-08-16T16:53:28.474Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:53:28.474Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:53:28.474Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12419.597 ms) ======
[2024-08-16T16:53:28.474Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T16:53:28.474Z] GC before operation: completed in 145.785 ms, heap usage 1.916 GB -> 60.577 MB.
[2024-08-16T16:53:31.463Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:53:33.397Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:53:35.330Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:53:36.272Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:53:37.215Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:53:39.152Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:53:40.093Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:53:41.034Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:53:41.034Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-16T16:53:41.034Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:53:41.034Z] Movies recommended for you:
[2024-08-16T16:53:41.034Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:53:41.034Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:53:41.034Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12344.306 ms) ======
[2024-08-16T16:53:41.034Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T16:53:41.034Z] GC before operation: completed in 91.468 ms, heap usage 458.159 MB -> 57.213 MB.
[2024-08-16T16:53:43.676Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:53:45.612Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:53:46.555Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:53:48.493Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:53:49.436Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:53:50.381Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:53:52.314Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:53:53.263Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:53:53.263Z] 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.
[2024-08-16T16:53:53.263Z] The best model improves the baseline by 14.43%.
[2024-08-16T16:53:53.263Z] Movies recommended for you:
[2024-08-16T16:53:53.263Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:53:53.263Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:53:53.263Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12016.616 ms) ======
[2024-08-16T16:53:55.198Z] -----------------------------------
[2024-08-16T16:53:55.198Z] renaissance-movie-lens_0_PASSED
[2024-08-16T16:53:55.198Z] -----------------------------------
[2024-08-16T16:53:55.198Z]
[2024-08-16T16:53:55.198Z] TEST TEARDOWN:
[2024-08-16T16:53:55.198Z] Nothing to be done for teardown.
[2024-08-16T16:53:55.198Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 16:53:54 2024 Epoch Time (ms): 1723827234718