renaissance-movie-lens_0
[2024-08-15T16:35:58.944Z] Running test renaissance-movie-lens_0 ...
[2024-08-15T16:35:58.944Z] ===============================================
[2024-08-15T16:35:58.944Z] renaissance-movie-lens_0 Start Time: Thu Aug 15 16:35:58 2024 Epoch Time (ms): 1723739758094
[2024-08-15T16:35:58.944Z] variation: NoOptions
[2024-08-15T16:35:58.944Z] JVM_OPTIONS:
[2024-08-15T16:35:58.944Z] { \
[2024-08-15T16:35:58.944Z] echo ""; echo "TEST SETUP:"; \
[2024-08-15T16:35:58.944Z] echo "Nothing to be done for setup."; \
[2024-08-15T16:35:58.944Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17237384002399/renaissance-movie-lens_0"; \
[2024-08-15T16:35:58.944Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17237384002399/renaissance-movie-lens_0"; \
[2024-08-15T16:35:58.944Z] echo ""; echo "TESTING:"; \
[2024-08-15T16:35:58.944Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17237384002399/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-15T16:35:58.944Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17237384002399/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-15T16:35:58.944Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-15T16:35:58.944Z] echo "Nothing to be done for teardown."; \
[2024-08-15T16:35:58.944Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17237384002399/TestTargetResult";
[2024-08-15T16:35:58.944Z]
[2024-08-15T16:35:58.944Z] TEST SETUP:
[2024-08-15T16:35:58.944Z] Nothing to be done for setup.
[2024-08-15T16:35:58.944Z]
[2024-08-15T16:35:58.944Z] TESTING:
[2024-08-15T16:36:14.936Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-15T16:36:19.753Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 16) threads.
[2024-08-15T16:36:22.731Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-15T16:36:22.731Z] Training: 60056, validation: 20285, test: 19854
[2024-08-15T16:36:22.731Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-15T16:36:22.731Z] GC before operation: completed in 61.369 ms, heap usage 321.301 MB -> 37.336 MB.
[2024-08-15T16:36:29.819Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:36:32.812Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:36:37.775Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:36:40.551Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:36:42.356Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:36:45.128Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:36:47.898Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:36:50.572Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:36:50.572Z] 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.
[2024-08-15T16:36:50.572Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:36:50.572Z] Movies recommended for you:
[2024-08-15T16:36:50.572Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:36:50.572Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:36:50.572Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26958.622 ms) ======
[2024-08-15T16:36:50.572Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-15T16:36:50.572Z] GC before operation: completed in 139.461 ms, heap usage 306.168 MB -> 49.673 MB.
[2024-08-15T16:36:54.318Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:36:57.236Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:37:01.046Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:37:03.823Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:37:05.625Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:37:08.525Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:37:10.713Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:37:13.447Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:37:13.447Z] 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.
[2024-08-15T16:37:13.447Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:37:13.447Z] Movies recommended for you:
[2024-08-15T16:37:13.447Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:37:13.447Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:37:13.447Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22392.018 ms) ======
[2024-08-15T16:37:13.447Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-15T16:37:13.447Z] GC before operation: completed in 141.144 ms, heap usage 210.008 MB -> 51.011 MB.
[2024-08-15T16:37:21.913Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:37:21.913Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:37:22.787Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:37:26.624Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:37:28.531Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:37:29.794Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:37:31.904Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:37:33.695Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:37:35.724Z] 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.
[2024-08-15T16:37:35.724Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:37:35.724Z] Movies recommended for you:
[2024-08-15T16:37:35.724Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:37:35.724Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:37:35.724Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21592.919 ms) ======
[2024-08-15T16:37:35.724Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-15T16:37:35.724Z] GC before operation: completed in 148.078 ms, heap usage 103.030 MB -> 54.327 MB.
[2024-08-15T16:37:38.338Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:37:40.335Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:37:44.531Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:37:47.331Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:37:49.141Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:37:50.934Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:37:53.352Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:37:56.192Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:37:56.192Z] 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.
[2024-08-15T16:37:56.192Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:37:56.192Z] Movies recommended for you:
[2024-08-15T16:37:56.192Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:37:56.192Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:37:56.192Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21293.556 ms) ======
[2024-08-15T16:37:56.192Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-15T16:37:56.192Z] GC before operation: completed in 116.472 ms, heap usage 321.887 MB -> 51.821 MB.
[2024-08-15T16:37:58.939Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:38:01.942Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:38:05.548Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:38:08.571Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:38:10.365Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:38:12.156Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:38:13.953Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:38:15.754Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:38:16.625Z] 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.
[2024-08-15T16:38:16.625Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:38:16.625Z] Movies recommended for you:
[2024-08-15T16:38:16.625Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:38:16.625Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:38:16.625Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20616.571 ms) ======
[2024-08-15T16:38:16.625Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-15T16:38:16.625Z] GC before operation: completed in 115.280 ms, heap usage 574.229 MB -> 55.435 MB.
[2024-08-15T16:38:19.428Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:38:22.926Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:38:26.316Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:38:29.533Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:38:31.733Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:38:33.021Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:38:37.004Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:38:37.004Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:38:37.876Z] 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.
[2024-08-15T16:38:37.876Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:38:37.876Z] Movies recommended for you:
[2024-08-15T16:38:37.876Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:38:37.876Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:38:37.876Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (21195.517 ms) ======
[2024-08-15T16:38:37.876Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-15T16:38:37.876Z] GC before operation: completed in 107.677 ms, heap usage 439.012 MB -> 51.964 MB.
[2024-08-15T16:38:40.682Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:38:44.543Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:38:47.334Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:38:57.599Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:38:57.599Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:38:57.599Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:38:57.599Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:38:58.771Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:38:58.771Z] 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.
[2024-08-15T16:38:58.771Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:38:58.771Z] Movies recommended for you:
[2024-08-15T16:38:58.771Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:38:58.771Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:38:58.771Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20720.954 ms) ======
[2024-08-15T16:38:58.771Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-15T16:38:58.771Z] GC before operation: completed in 110.791 ms, heap usage 543.249 MB -> 55.420 MB.
[2024-08-15T16:39:01.571Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:39:04.347Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:39:08.235Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:39:12.014Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:39:13.822Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:39:14.691Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:39:17.115Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:39:19.903Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:39:19.903Z] 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.
[2024-08-15T16:39:19.903Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:39:19.903Z] Movies recommended for you:
[2024-08-15T16:39:19.903Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:39:19.903Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:39:19.903Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21233.920 ms) ======
[2024-08-15T16:39:19.903Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-15T16:39:19.903Z] GC before operation: completed in 113.369 ms, heap usage 507.645 MB -> 55.660 MB.
[2024-08-15T16:39:22.697Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:39:26.517Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:39:29.721Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:39:32.801Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:39:34.599Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:39:36.520Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:39:38.702Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:39:40.565Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:39:40.565Z] 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.
[2024-08-15T16:39:40.565Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:39:40.565Z] Movies recommended for you:
[2024-08-15T16:39:40.565Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:39:40.565Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:39:40.565Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20505.993 ms) ======
[2024-08-15T16:39:40.565Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-15T16:39:40.565Z] GC before operation: completed in 121.934 ms, heap usage 237.118 MB -> 52.021 MB.
[2024-08-15T16:39:43.337Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:39:47.173Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:39:51.043Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:39:53.260Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:39:55.299Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:39:57.450Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:39:59.252Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:40:00.782Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:40:01.659Z] 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.
[2024-08-15T16:40:01.659Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:40:01.659Z] Movies recommended for you:
[2024-08-15T16:40:01.659Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:40:01.659Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:40:01.659Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20676.981 ms) ======
[2024-08-15T16:40:01.659Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-15T16:40:01.659Z] GC before operation: completed in 138.804 ms, heap usage 536.167 MB -> 55.587 MB.
[2024-08-15T16:40:04.449Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:40:13.740Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:40:13.740Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:40:14.822Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:40:16.624Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:40:18.465Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:40:20.695Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:40:22.503Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:40:22.503Z] 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.
[2024-08-15T16:40:22.503Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:40:22.503Z] Movies recommended for you:
[2024-08-15T16:40:22.503Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:40:22.503Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:40:22.503Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20918.513 ms) ======
[2024-08-15T16:40:22.503Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-15T16:40:22.503Z] GC before operation: completed in 108.469 ms, heap usage 474.437 MB -> 52.081 MB.
[2024-08-15T16:40:25.281Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:40:28.073Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:40:33.057Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:40:35.288Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:40:37.316Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:40:38.592Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:40:42.741Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:40:45.121Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:40:45.121Z] 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.
[2024-08-15T16:40:45.121Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:40:45.121Z] Movies recommended for you:
[2024-08-15T16:40:45.121Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:40:45.121Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:40:45.121Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (21691.779 ms) ======
[2024-08-15T16:40:45.121Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-15T16:40:45.121Z] GC before operation: completed in 134.862 ms, heap usage 206.669 MB -> 52.123 MB.
[2024-08-15T16:40:47.789Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:40:50.907Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:40:54.327Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:40:58.335Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:40:59.587Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:41:00.810Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:41:02.916Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:41:04.210Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:41:05.091Z] 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.
[2024-08-15T16:41:05.091Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:41:05.091Z] Movies recommended for you:
[2024-08-15T16:41:05.091Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:41:05.091Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:41:05.091Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20631.204 ms) ======
[2024-08-15T16:41:05.091Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-15T16:41:05.091Z] GC before operation: completed in 108.056 ms, heap usage 501.833 MB -> 55.759 MB.
[2024-08-15T16:41:07.767Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:41:10.887Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:41:14.715Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:41:17.513Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:41:19.298Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:41:21.106Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:41:25.061Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:41:25.061Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:41:25.061Z] 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.
[2024-08-15T16:41:25.061Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:41:25.061Z] Movies recommended for you:
[2024-08-15T16:41:25.061Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:41:25.061Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:41:25.061Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20193.610 ms) ======
[2024-08-15T16:41:25.061Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-15T16:41:25.061Z] GC before operation: completed in 138.339 ms, heap usage 678.104 MB -> 55.612 MB.
[2024-08-15T16:41:28.281Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:41:36.632Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:41:36.632Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:41:37.598Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:41:39.405Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:41:41.215Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:41:44.922Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:41:47.120Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:41:47.120Z] 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.
[2024-08-15T16:41:47.120Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:41:47.120Z] Movies recommended for you:
[2024-08-15T16:41:47.120Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:41:47.120Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:41:47.120Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (21753.655 ms) ======
[2024-08-15T16:41:47.120Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-15T16:41:47.120Z] GC before operation: completed in 106.242 ms, heap usage 415.101 MB -> 52.311 MB.
[2024-08-15T16:41:50.461Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:41:53.250Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:41:56.525Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:41:59.939Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:42:01.193Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:42:02.980Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:42:06.042Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:42:07.537Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:42:07.537Z] 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.
[2024-08-15T16:42:07.537Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:42:07.537Z] Movies recommended for you:
[2024-08-15T16:42:07.537Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:42:07.537Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:42:07.537Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20168.843 ms) ======
[2024-08-15T16:42:07.537Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-15T16:42:07.537Z] GC before operation: completed in 145.347 ms, heap usage 96.351 MB -> 55.670 MB.
[2024-08-15T16:42:10.220Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:42:13.293Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:42:17.127Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:42:20.318Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:42:22.120Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:42:23.906Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:42:25.694Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:42:27.507Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:42:27.507Z] 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.
[2024-08-15T16:42:27.507Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:42:28.381Z] Movies recommended for you:
[2024-08-15T16:42:28.381Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:42:28.381Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:42:28.381Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20389.032 ms) ======
[2024-08-15T16:42:28.381Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-15T16:42:28.381Z] GC before operation: completed in 141.719 ms, heap usage 277.458 MB -> 52.111 MB.
[2024-08-15T16:42:31.157Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:42:33.942Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:42:38.154Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:42:41.309Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:42:42.186Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:42:44.005Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:42:47.823Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:42:49.618Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:42:49.618Z] 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.
[2024-08-15T16:42:49.618Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:42:49.618Z] Movies recommended for you:
[2024-08-15T16:42:49.618Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:42:49.618Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:42:49.618Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (21768.756 ms) ======
[2024-08-15T16:42:49.618Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-15T16:42:50.402Z] GC before operation: completed in 115.029 ms, heap usage 339.939 MB -> 52.230 MB.
[2024-08-15T16:42:52.878Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:42:56.386Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:43:01.070Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:43:02.872Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:43:04.545Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:43:06.231Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:43:07.898Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:43:09.556Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:43:10.362Z] 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.
[2024-08-15T16:43:10.362Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:43:10.362Z] Movies recommended for you:
[2024-08-15T16:43:10.362Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:43:10.362Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:43:10.362Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20077.002 ms) ======
[2024-08-15T16:43:10.362Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-15T16:43:10.362Z] GC before operation: completed in 125.354 ms, heap usage 213.695 MB -> 52.376 MB.
[2024-08-15T16:43:12.967Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T16:43:16.523Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T16:43:20.122Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T16:43:22.739Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T16:43:24.584Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T16:43:26.237Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T16:43:27.902Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T16:43:29.586Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T16:43:30.391Z] 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.
[2024-08-15T16:43:30.391Z] The best model improves the baseline by 14.43%.
[2024-08-15T16:43:30.391Z] Movies recommended for you:
[2024-08-15T16:43:30.391Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T16:43:30.391Z] There is no way to check that no silent failure occurred.
[2024-08-15T16:43:30.391Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19915.928 ms) ======
[2024-08-15T16:43:30.391Z] -----------------------------------
[2024-08-15T16:43:30.391Z] renaissance-movie-lens_0_PASSED
[2024-08-15T16:43:30.391Z] -----------------------------------
[2024-08-15T16:43:30.391Z]
[2024-08-15T16:43:30.391Z] TEST TEARDOWN:
[2024-08-15T16:43:30.391Z] Nothing to be done for teardown.
[2024-08-15T16:43:30.391Z] renaissance-movie-lens_0 Finish Time: Thu Aug 15 16:43:30 2024 Epoch Time (ms): 1723740210207