renaissance-movie-lens_0
[2025-02-20T07:08:22.936Z] Running test renaissance-movie-lens_0 ...
[2025-02-20T07:08:22.936Z] ===============================================
[2025-02-20T07:08:22.936Z] renaissance-movie-lens_0 Start Time: Thu Feb 20 02:08:22 2025 Epoch Time (ms): 1740035302203
[2025-02-20T07:08:22.936Z] variation: NoOptions
[2025-02-20T07:08:22.936Z] JVM_OPTIONS:
[2025-02-20T07:08:22.936Z] { \
[2025-02-20T07:08:22.936Z] echo ""; echo "TEST SETUP:"; \
[2025-02-20T07:08:22.936Z] echo "Nothing to be done for setup."; \
[2025-02-20T07:08:22.936Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400342377445/renaissance-movie-lens_0"; \
[2025-02-20T07:08:22.936Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400342377445/renaissance-movie-lens_0"; \
[2025-02-20T07:08:22.936Z] echo ""; echo "TESTING:"; \
[2025-02-20T07:08:22.937Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/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_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400342377445/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-20T07:08:22.937Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400342377445/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-20T07:08:22.937Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-20T07:08:22.937Z] echo "Nothing to be done for teardown."; \
[2025-02-20T07:08:22.937Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400342377445/TestTargetResult";
[2025-02-20T07:08:22.937Z]
[2025-02-20T07:08:22.937Z] TEST SETUP:
[2025-02-20T07:08:22.937Z] Nothing to be done for setup.
[2025-02-20T07:08:22.937Z]
[2025-02-20T07:08:22.937Z] TESTING:
[2025-02-20T07:08:25.033Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-20T07:08:26.408Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-02-20T07:08:29.400Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-20T07:08:30.084Z] Training: 60056, validation: 20285, test: 19854
[2025-02-20T07:08:30.084Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-20T07:08:30.084Z] GC before operation: completed in 97.779 ms, heap usage 76.745 MB -> 36.396 MB.
[2025-02-20T07:08:37.533Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:08:40.845Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:08:44.766Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:08:47.717Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:08:49.846Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:08:51.966Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:08:54.076Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:08:55.479Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:08:56.137Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:08:56.137Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:08:56.137Z] Movies recommended for you:
[2025-02-20T07:08:56.137Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:08:56.137Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:08:56.137Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26107.955 ms) ======
[2025-02-20T07:08:56.137Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-20T07:08:56.137Z] GC before operation: completed in 166.501 ms, heap usage 189.335 MB -> 50.044 MB.
[2025-02-20T07:09:00.131Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:09:03.171Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:09:06.126Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:09:09.056Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:09:10.432Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:09:12.544Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:09:14.647Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:09:16.784Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:09:16.784Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:09:16.784Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:09:16.784Z] Movies recommended for you:
[2025-02-20T07:09:16.784Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:09:16.784Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:09:16.784Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20415.382 ms) ======
[2025-02-20T07:09:16.784Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-20T07:09:16.784Z] GC before operation: completed in 116.313 ms, heap usage 115.695 MB -> 48.393 MB.
[2025-02-20T07:09:19.818Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:09:22.777Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:09:26.162Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:09:29.133Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:09:30.588Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:09:32.714Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:09:34.854Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:09:36.213Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:09:36.213Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:09:36.866Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:09:36.866Z] Movies recommended for you:
[2025-02-20T07:09:36.866Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:09:36.866Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:09:36.866Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19689.516 ms) ======
[2025-02-20T07:09:36.866Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-20T07:09:36.866Z] GC before operation: completed in 136.422 ms, heap usage 64.595 MB -> 48.554 MB.
[2025-02-20T07:09:39.833Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:09:42.809Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:09:45.767Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:09:48.750Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:09:50.100Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:09:51.456Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:09:52.802Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:09:54.144Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:09:54.785Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:09:54.785Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:09:54.785Z] Movies recommended for you:
[2025-02-20T07:09:54.785Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:09:54.785Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:09:54.785Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17995.394 ms) ======
[2025-02-20T07:09:54.785Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-20T07:09:54.785Z] GC before operation: completed in 156.966 ms, heap usage 165.519 MB -> 49.013 MB.
[2025-02-20T07:09:57.743Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:10:00.683Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:10:03.723Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:10:06.672Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:10:08.016Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:10:09.368Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:10:11.547Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:10:12.896Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:10:12.896Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:10:12.896Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:10:12.896Z] Movies recommended for you:
[2025-02-20T07:10:12.896Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:10:12.896Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:10:12.896Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18265.514 ms) ======
[2025-02-20T07:10:12.896Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-20T07:10:13.531Z] GC before operation: completed in 124.966 ms, heap usage 133.498 MB -> 49.150 MB.
[2025-02-20T07:10:16.476Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:10:19.486Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:10:22.476Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:10:24.654Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:10:26.761Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:10:28.106Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:10:30.286Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:10:31.683Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:10:31.683Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:10:31.683Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:10:32.347Z] Movies recommended for you:
[2025-02-20T07:10:32.347Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:10:32.347Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:10:32.347Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18761.325 ms) ======
[2025-02-20T07:10:32.347Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-20T07:10:32.347Z] GC before operation: completed in 146.029 ms, heap usage 201.546 MB -> 49.183 MB.
[2025-02-20T07:10:36.332Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:10:39.481Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:10:42.472Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:10:45.431Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:10:47.674Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:10:49.937Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:10:52.135Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:10:53.522Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:10:53.522Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:10:53.522Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:10:53.522Z] Movies recommended for you:
[2025-02-20T07:10:53.522Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:10:53.522Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:10:53.522Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21519.267 ms) ======
[2025-02-20T07:10:53.522Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-20T07:10:54.166Z] GC before operation: completed in 188.480 ms, heap usage 152.594 MB -> 49.307 MB.
[2025-02-20T07:10:57.197Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:11:00.209Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:11:04.499Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:11:07.536Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:11:09.701Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:11:10.799Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:11:13.113Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:11:15.302Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:11:16.017Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:11:16.017Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:11:16.017Z] Movies recommended for you:
[2025-02-20T07:11:16.017Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:11:16.017Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:11:16.017Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21810.247 ms) ======
[2025-02-20T07:11:16.017Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-20T07:11:16.017Z] GC before operation: completed in 188.636 ms, heap usage 149.942 MB -> 49.567 MB.
[2025-02-20T07:11:19.046Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:11:23.004Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:11:26.002Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:11:29.084Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:11:31.268Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:11:33.457Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:11:35.604Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:11:36.947Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:11:37.602Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:11:37.602Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:11:37.602Z] Movies recommended for you:
[2025-02-20T07:11:37.602Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:11:37.602Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:11:37.602Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21469.310 ms) ======
[2025-02-20T07:11:37.603Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-20T07:11:37.603Z] GC before operation: completed in 161.864 ms, heap usage 195.129 MB -> 49.433 MB.
[2025-02-20T07:11:41.496Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:11:43.706Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:11:46.784Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:11:49.776Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:11:51.187Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:11:52.607Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:11:54.853Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:11:57.416Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:11:57.416Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:11:57.416Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:11:57.416Z] Movies recommended for you:
[2025-02-20T07:11:57.416Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:11:57.416Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:11:57.417Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19509.249 ms) ======
[2025-02-20T07:11:57.417Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-20T07:11:57.417Z] GC before operation: completed in 150.042 ms, heap usage 159.742 MB -> 49.526 MB.
[2025-02-20T07:11:59.723Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:12:02.916Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:12:05.126Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:12:07.257Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:12:09.386Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:12:10.746Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:12:12.111Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:12:13.456Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:12:14.096Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:12:14.096Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:12:14.096Z] Movies recommended for you:
[2025-02-20T07:12:14.096Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:12:14.096Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:12:14.096Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16733.649 ms) ======
[2025-02-20T07:12:14.096Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-20T07:12:14.096Z] GC before operation: completed in 163.918 ms, heap usage 148.155 MB -> 49.232 MB.
[2025-02-20T07:12:17.096Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:12:19.175Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:12:22.226Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:12:24.392Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:12:26.536Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:12:27.902Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:12:30.058Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:12:31.414Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:12:32.080Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:12:32.080Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:12:32.080Z] Movies recommended for you:
[2025-02-20T07:12:32.080Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:12:32.080Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:12:32.080Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17800.301 ms) ======
[2025-02-20T07:12:32.080Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-20T07:12:32.080Z] GC before operation: completed in 155.079 ms, heap usage 253.027 MB -> 49.545 MB.
[2025-02-20T07:12:35.470Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:12:38.467Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:12:41.447Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:12:44.420Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:12:45.855Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:12:48.017Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:12:50.146Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:12:52.276Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:12:52.276Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:12:52.276Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:12:52.276Z] Movies recommended for you:
[2025-02-20T07:12:52.276Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:12:52.276Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:12:52.276Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20342.644 ms) ======
[2025-02-20T07:12:52.276Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-20T07:12:52.916Z] GC before operation: completed in 166.628 ms, heap usage 143.394 MB -> 49.605 MB.
[2025-02-20T07:12:55.946Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:12:58.943Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:13:02.075Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:13:05.076Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:13:06.444Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:13:07.834Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:13:10.112Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:13:12.676Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:13:12.676Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:13:12.676Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:13:12.676Z] Movies recommended for you:
[2025-02-20T07:13:12.676Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:13:12.676Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:13:12.676Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19807.457 ms) ======
[2025-02-20T07:13:12.676Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-20T07:13:12.676Z] GC before operation: completed in 144.331 ms, heap usage 150.758 MB -> 49.397 MB.
[2025-02-20T07:13:15.806Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:13:18.859Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:13:21.012Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:13:24.029Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:13:25.377Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:13:27.526Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:13:28.906Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:13:31.067Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:13:31.067Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:13:31.067Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:13:31.067Z] Movies recommended for you:
[2025-02-20T07:13:31.067Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:13:31.067Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:13:31.067Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18447.066 ms) ======
[2025-02-20T07:13:31.067Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-20T07:13:31.067Z] GC before operation: completed in 150.600 ms, heap usage 64.997 MB -> 49.677 MB.
[2025-02-20T07:13:34.036Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:13:37.034Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:13:40.046Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:13:42.147Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:13:43.504Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:13:44.880Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:13:47.006Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:13:48.346Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:13:48.346Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:13:48.346Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:13:49.023Z] Movies recommended for you:
[2025-02-20T07:13:49.023Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:13:49.023Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:13:49.023Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17523.217 ms) ======
[2025-02-20T07:13:49.023Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-20T07:13:49.023Z] GC before operation: completed in 146.496 ms, heap usage 183.091 MB -> 49.633 MB.
[2025-02-20T07:13:51.993Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:13:54.136Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:13:58.038Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:14:01.512Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:14:02.944Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:14:05.166Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:14:07.333Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:14:08.708Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:14:09.414Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:14:09.414Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:14:09.414Z] Movies recommended for you:
[2025-02-20T07:14:09.414Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:14:09.414Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:14:09.414Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20688.892 ms) ======
[2025-02-20T07:14:09.414Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-20T07:14:09.414Z] GC before operation: completed in 208.549 ms, heap usage 137.460 MB -> 49.433 MB.
[2025-02-20T07:14:13.352Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:14:17.314Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:14:20.422Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:14:24.416Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:14:25.872Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:14:28.068Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:14:29.438Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:14:32.536Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:14:32.536Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:14:32.536Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:14:32.536Z] Movies recommended for you:
[2025-02-20T07:14:32.536Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:14:32.536Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:14:32.536Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (22785.375 ms) ======
[2025-02-20T07:14:32.536Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-20T07:14:32.536Z] GC before operation: completed in 166.976 ms, heap usage 152.795 MB -> 49.605 MB.
[2025-02-20T07:14:36.496Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:14:38.609Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:14:41.567Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:14:44.599Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:14:45.989Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:14:47.355Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:14:49.659Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:14:51.080Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:14:51.080Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:14:51.080Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:14:51.080Z] Movies recommended for you:
[2025-02-20T07:14:51.080Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:14:51.080Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:14:51.080Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18352.529 ms) ======
[2025-02-20T07:14:51.080Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-20T07:14:51.080Z] GC before operation: completed in 121.552 ms, heap usage 135.939 MB -> 49.676 MB.
[2025-02-20T07:14:54.039Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T07:14:57.007Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T07:15:00.858Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T07:15:02.980Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T07:15:04.350Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T07:15:05.747Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T07:15:07.936Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T07:15:09.284Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T07:15:09.284Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T07:15:09.284Z] The best model improves the baseline by 14.34%.
[2025-02-20T07:15:09.956Z] Movies recommended for you:
[2025-02-20T07:15:09.957Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T07:15:09.957Z] There is no way to check that no silent failure occurred.
[2025-02-20T07:15:09.957Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18531.048 ms) ======
[2025-02-20T07:15:09.957Z] -----------------------------------
[2025-02-20T07:15:09.957Z] renaissance-movie-lens_0_PASSED
[2025-02-20T07:15:09.957Z] -----------------------------------
[2025-02-20T07:15:09.957Z]
[2025-02-20T07:15:09.957Z] TEST TEARDOWN:
[2025-02-20T07:15:09.957Z] Nothing to be done for teardown.
[2025-02-20T07:15:09.957Z] renaissance-movie-lens_0 Finish Time: Thu Feb 20 02:15:09 2025 Epoch Time (ms): 1740035709838