renaissance-movie-lens_0
[2024-08-07T21:24:32.284Z] Running test renaissance-movie-lens_0 ...
[2024-08-07T21:24:32.284Z] ===============================================
[2024-08-07T21:24:32.284Z] renaissance-movie-lens_0 Start Time: Wed Aug 7 21:24:31 2024 Epoch Time (ms): 1723065871515
[2024-08-07T21:24:32.284Z] variation: NoOptions
[2024-08-07T21:24:32.284Z] JVM_OPTIONS:
[2024-08-07T21:24:32.284Z] { \
[2024-08-07T21:24:32.284Z] echo ""; echo "TEST SETUP:"; \
[2024-08-07T21:24:32.284Z] echo "Nothing to be done for setup."; \
[2024-08-07T21:24:32.285Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17230650242586/renaissance-movie-lens_0"; \
[2024-08-07T21:24:32.285Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17230650242586/renaissance-movie-lens_0"; \
[2024-08-07T21:24:32.285Z] echo ""; echo "TESTING:"; \
[2024-08-07T21:24:32.285Z] "/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_17230650242586/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-07T21:24:32.285Z] 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_17230650242586/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-07T21:24:32.285Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-07T21:24:32.285Z] echo "Nothing to be done for teardown."; \
[2024-08-07T21:24:32.285Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17230650242586/TestTargetResult";
[2024-08-07T21:24:32.285Z]
[2024-08-07T21:24:32.285Z] TEST SETUP:
[2024-08-07T21:24:32.285Z] Nothing to be done for setup.
[2024-08-07T21:24:32.285Z]
[2024-08-07T21:24:32.285Z] TESTING:
[2024-08-07T21:24:35.255Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-07T21:24:38.227Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-07T21:24:42.777Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-07T21:24:42.777Z] Training: 60056, validation: 20285, test: 19854
[2024-08-07T21:24:42.777Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-07T21:24:42.777Z] GC before operation: completed in 51.659 ms, heap usage 76.256 MB -> 39.313 MB.
[2024-08-07T21:24:50.876Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:24:54.994Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:24:59.100Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:25:02.084Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:25:04.019Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:25:05.950Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:25:07.882Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:25:09.813Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:25:10.757Z] 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.
[2024-08-07T21:25:10.757Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:25:10.757Z] Movies recommended for you:
[2024-08-07T21:25:10.757Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:25:10.757Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:25:10.757Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28247.539 ms) ======
[2024-08-07T21:25:10.757Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-07T21:25:10.757Z] GC before operation: completed in 113.165 ms, heap usage 751.033 MB -> 56.298 MB.
[2024-08-07T21:25:14.863Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:25:17.897Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:25:20.878Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:25:23.922Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:25:24.863Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:25:26.968Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:25:28.899Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:25:30.831Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:25:30.831Z] 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.
[2024-08-07T21:25:30.831Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:25:30.831Z] Movies recommended for you:
[2024-08-07T21:25:30.831Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:25:30.831Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:25:30.831Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20210.034 ms) ======
[2024-08-07T21:25:30.831Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-07T21:25:30.831Z] GC before operation: completed in 106.812 ms, heap usage 534.837 MB -> 56.589 MB.
[2024-08-07T21:25:34.938Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:25:37.913Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:25:39.851Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:25:42.834Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:25:44.765Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:25:46.695Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:25:48.625Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:25:49.565Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:25:50.505Z] 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.
[2024-08-07T21:25:50.505Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:25:50.505Z] Movies recommended for you:
[2024-08-07T21:25:50.505Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:25:50.505Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:25:50.505Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19327.969 ms) ======
[2024-08-07T21:25:50.505Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-07T21:25:50.505Z] GC before operation: completed in 103.242 ms, heap usage 358.808 MB -> 53.574 MB.
[2024-08-07T21:25:54.194Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:25:57.173Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:25:59.102Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:26:02.082Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:26:04.041Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:26:05.970Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:26:07.898Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:26:09.826Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:26:09.826Z] 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.
[2024-08-07T21:26:09.826Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:26:09.826Z] Movies recommended for you:
[2024-08-07T21:26:09.826Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:26:09.826Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:26:09.826Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19353.160 ms) ======
[2024-08-07T21:26:09.826Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-07T21:26:09.826Z] GC before operation: completed in 122.005 ms, heap usage 604.558 MB -> 57.401 MB.
[2024-08-07T21:26:13.928Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:26:15.859Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:26:18.833Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:26:21.883Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:26:22.821Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:26:24.753Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:26:26.685Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:26:28.626Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:26:28.626Z] 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.
[2024-08-07T21:26:28.626Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:26:28.626Z] Movies recommended for you:
[2024-08-07T21:26:28.626Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:26:28.626Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:26:28.626Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18586.925 ms) ======
[2024-08-07T21:26:28.626Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-07T21:26:28.626Z] GC before operation: completed in 124.430 ms, heap usage 349.792 MB -> 57.298 MB.
[2024-08-07T21:26:32.730Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:26:34.662Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:26:37.643Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:26:40.627Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:26:42.557Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:26:43.500Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:26:45.429Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:26:47.361Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:26:47.361Z] 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.
[2024-08-07T21:26:47.361Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:26:47.361Z] Movies recommended for you:
[2024-08-07T21:26:47.361Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:26:47.361Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:26:47.361Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18944.852 ms) ======
[2024-08-07T21:26:47.361Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-07T21:26:48.300Z] GC before operation: completed in 123.989 ms, heap usage 282.281 MB -> 53.914 MB.
[2024-08-07T21:26:51.282Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:26:54.273Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:26:56.207Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:26:59.192Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:27:01.124Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:27:03.056Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:27:03.998Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:27:05.959Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:27:07.590Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-07T21:27:07.590Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:27:07.590Z] Movies recommended for you:
[2024-08-07T21:27:07.590Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:27:07.590Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:27:07.590Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18743.078 ms) ======
[2024-08-07T21:27:07.590Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-07T21:27:07.590Z] GC before operation: completed in 122.522 ms, heap usage 595.124 MB -> 57.504 MB.
[2024-08-07T21:27:09.518Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:27:12.499Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:27:15.480Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:27:18.465Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:27:20.399Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:27:21.341Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:27:23.361Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:27:25.293Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:27:25.293Z] 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.
[2024-08-07T21:27:25.293Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:27:25.293Z] Movies recommended for you:
[2024-08-07T21:27:25.293Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:27:25.293Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:27:25.293Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18707.667 ms) ======
[2024-08-07T21:27:25.293Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-07T21:27:25.293Z] GC before operation: completed in 127.295 ms, heap usage 386.425 MB -> 54.479 MB.
[2024-08-07T21:27:28.275Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:27:31.262Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:27:34.249Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:27:37.234Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:27:38.177Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:27:40.112Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:27:42.057Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:27:43.989Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:27:43.989Z] 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.
[2024-08-07T21:27:43.989Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:27:43.989Z] Movies recommended for you:
[2024-08-07T21:27:43.989Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:27:43.989Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:27:43.989Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18579.934 ms) ======
[2024-08-07T21:27:43.989Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-07T21:27:43.989Z] GC before operation: completed in 112.364 ms, heap usage 426.051 MB -> 54.338 MB.
[2024-08-07T21:27:46.972Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:27:49.954Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:27:52.940Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:27:55.926Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:27:57.863Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:27:58.803Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:28:00.740Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:28:02.675Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:28:02.675Z] 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.
[2024-08-07T21:28:02.675Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:28:03.618Z] Movies recommended for you:
[2024-08-07T21:28:03.618Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:28:03.618Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:28:03.618Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18931.634 ms) ======
[2024-08-07T21:28:03.618Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-07T21:28:03.618Z] GC before operation: completed in 124.276 ms, heap usage 526.765 MB -> 57.799 MB.
[2024-08-07T21:28:06.601Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:28:09.587Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:28:12.569Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:28:14.498Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:28:16.424Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:28:18.350Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:28:19.736Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:28:21.672Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:28:21.672Z] 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.
[2024-08-07T21:28:21.672Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:28:21.672Z] Movies recommended for you:
[2024-08-07T21:28:21.672Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:28:21.672Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:28:21.672Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18762.274 ms) ======
[2024-08-07T21:28:21.672Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-07T21:28:22.612Z] GC before operation: completed in 121.456 ms, heap usage 379.796 MB -> 54.188 MB.
[2024-08-07T21:28:25.593Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:28:28.575Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:28:30.508Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:28:33.495Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:28:35.420Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:28:36.370Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:28:38.297Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:28:40.222Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:28:40.222Z] 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.
[2024-08-07T21:28:40.222Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:28:40.222Z] Movies recommended for you:
[2024-08-07T21:28:40.222Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:28:40.222Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:28:40.222Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18441.833 ms) ======
[2024-08-07T21:28:40.222Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-07T21:28:41.163Z] GC before operation: completed in 130.151 ms, heap usage 1.205 GB -> 58.835 MB.
[2024-08-07T21:28:44.140Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:28:47.119Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:28:50.093Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:28:52.024Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:28:53.952Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:28:55.892Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:28:57.827Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:28:58.771Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:28:59.713Z] 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.
[2024-08-07T21:28:59.713Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:28:59.713Z] Movies recommended for you:
[2024-08-07T21:28:59.713Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:28:59.713Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:28:59.713Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18882.567 ms) ======
[2024-08-07T21:28:59.713Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-07T21:28:59.713Z] GC before operation: completed in 130.287 ms, heap usage 264.846 MB -> 54.502 MB.
[2024-08-07T21:29:02.702Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:29:05.691Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:29:08.680Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:29:10.615Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:29:12.545Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:29:14.479Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:29:15.420Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:29:17.356Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:29:17.356Z] 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.
[2024-08-07T21:29:17.356Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:29:17.356Z] Movies recommended for you:
[2024-08-07T21:29:17.356Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:29:17.356Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:29:17.356Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17889.018 ms) ======
[2024-08-07T21:29:17.356Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-07T21:29:18.297Z] GC before operation: completed in 124.149 ms, heap usage 932.337 MB -> 58.273 MB.
[2024-08-07T21:29:21.279Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:29:23.345Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:29:26.333Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:29:29.319Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:29:30.997Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:29:31.940Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:29:33.872Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:29:35.812Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:29:35.812Z] 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.
[2024-08-07T21:29:35.812Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:29:35.812Z] Movies recommended for you:
[2024-08-07T21:29:35.812Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:29:35.812Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:29:35.812Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18233.987 ms) ======
[2024-08-07T21:29:35.812Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-07T21:29:35.812Z] GC before operation: completed in 133.682 ms, heap usage 383.664 MB -> 54.486 MB.
[2024-08-07T21:29:39.933Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:29:41.864Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:29:44.845Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:29:46.777Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:29:48.706Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:29:49.646Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:29:51.570Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:29:53.495Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:29:53.495Z] 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.
[2024-08-07T21:29:53.495Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:29:53.495Z] Movies recommended for you:
[2024-08-07T21:29:53.495Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:29:53.495Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:29:53.495Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17354.045 ms) ======
[2024-08-07T21:29:53.495Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-07T21:29:53.495Z] GC before operation: completed in 126.545 ms, heap usage 381.028 MB -> 54.545 MB.
[2024-08-07T21:29:56.467Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:29:59.439Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:30:01.371Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:30:04.343Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:30:05.280Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:30:07.206Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:30:09.133Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:30:10.072Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:30:11.009Z] 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.
[2024-08-07T21:30:11.009Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:30:11.009Z] Movies recommended for you:
[2024-08-07T21:30:11.009Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:30:11.009Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:30:11.009Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17274.968 ms) ======
[2024-08-07T21:30:11.009Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-07T21:30:11.009Z] GC before operation: completed in 126.806 ms, heap usage 455.803 MB -> 54.504 MB.
[2024-08-07T21:30:14.012Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:30:16.987Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:30:19.965Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:30:21.894Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:30:23.818Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:30:25.744Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:30:26.682Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:30:28.780Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:30:28.780Z] 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.
[2024-08-07T21:30:28.780Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:30:28.780Z] Movies recommended for you:
[2024-08-07T21:30:28.780Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:30:28.780Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:30:28.780Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17985.871 ms) ======
[2024-08-07T21:30:28.780Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-07T21:30:28.780Z] GC before operation: completed in 124.821 ms, heap usage 637.237 MB -> 57.924 MB.
[2024-08-07T21:30:32.882Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:30:34.810Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:30:37.781Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:30:39.708Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:30:41.638Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:30:42.577Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:30:44.263Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:30:46.196Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:30:46.196Z] 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.
[2024-08-07T21:30:46.196Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:30:46.196Z] Movies recommended for you:
[2024-08-07T21:30:46.196Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:30:46.196Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:30:46.196Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17409.628 ms) ======
[2024-08-07T21:30:46.196Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-07T21:30:47.136Z] GC before operation: completed in 120.875 ms, heap usage 358.190 MB -> 54.662 MB.
[2024-08-07T21:30:50.117Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:30:52.044Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:30:55.022Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:30:56.947Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:30:58.875Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:31:00.800Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:31:01.738Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:31:03.664Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:31:03.664Z] 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.
[2024-08-07T21:31:03.664Z] The best model improves the baseline by 14.43%.
[2024-08-07T21:31:04.601Z] Movies recommended for you:
[2024-08-07T21:31:04.601Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:31:04.601Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:31:04.601Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17506.037 ms) ======
[2024-08-07T21:31:06.533Z] -----------------------------------
[2024-08-07T21:31:06.533Z] renaissance-movie-lens_0_PASSED
[2024-08-07T21:31:06.533Z] -----------------------------------
[2024-08-07T21:31:06.533Z]
[2024-08-07T21:31:06.533Z] TEST TEARDOWN:
[2024-08-07T21:31:06.533Z] Nothing to be done for teardown.
[2024-08-07T21:31:06.533Z] renaissance-movie-lens_0 Finish Time: Wed Aug 7 21:31:05 2024 Epoch Time (ms): 1723066265860