renaissance-movie-lens_0
[2025-02-20T06:31:07.198Z] Running test renaissance-movie-lens_0 ...
[2025-02-20T06:31:07.198Z] ===============================================
[2025-02-20T06:31:07.198Z] renaissance-movie-lens_0 Start Time: Thu Feb 20 06:31:06 2025 Epoch Time (ms): 1740033066473
[2025-02-20T06:31:07.198Z] variation: NoOptions
[2025-02-20T06:31:07.198Z] JVM_OPTIONS:
[2025-02-20T06:31:07.198Z] { \
[2025-02-20T06:31:07.198Z] echo ""; echo "TEST SETUP:"; \
[2025-02-20T06:31:07.198Z] echo "Nothing to be done for setup."; \
[2025-02-20T06:31:07.198Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400320262692/renaissance-movie-lens_0"; \
[2025-02-20T06:31:07.198Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400320262692/renaissance-movie-lens_0"; \
[2025-02-20T06:31:07.198Z] echo ""; echo "TESTING:"; \
[2025-02-20T06:31:07.198Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400320262692/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-20T06:31:07.198Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400320262692/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-20T06:31:07.198Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-20T06:31:07.198Z] echo "Nothing to be done for teardown."; \
[2025-02-20T06:31:07.198Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17400320262692/TestTargetResult";
[2025-02-20T06:31:07.198Z]
[2025-02-20T06:31:07.198Z] TEST SETUP:
[2025-02-20T06:31:07.198Z] Nothing to be done for setup.
[2025-02-20T06:31:07.198Z]
[2025-02-20T06:31:07.198Z] TESTING:
[2025-02-20T06:31:09.306Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-20T06:31:11.830Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-02-20T06:31:14.758Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-20T06:31:14.758Z] Training: 60056, validation: 20285, test: 19854
[2025-02-20T06:31:14.758Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-20T06:31:15.407Z] GC before operation: completed in 90.851 ms, heap usage 143.679 MB -> 37.175 MB.
[2025-02-20T06:31:21.385Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:31:25.142Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:31:29.974Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:31:32.831Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:31:34.896Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:31:36.212Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:31:38.314Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:31:40.418Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:31:41.040Z] 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.
[2025-02-20T06:31:41.040Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:31:41.040Z] Movies recommended for you:
[2025-02-20T06:31:41.040Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:31:41.040Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:31:41.040Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25890.259 ms) ======
[2025-02-20T06:31:41.040Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-20T06:31:41.040Z] GC before operation: completed in 111.780 ms, heap usage 257.592 MB -> 51.193 MB.
[2025-02-20T06:31:43.925Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:31:47.691Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:31:50.573Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:31:53.451Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:31:54.791Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:31:57.214Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:31:58.533Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:31:59.838Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:32:00.493Z] 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.
[2025-02-20T06:32:00.493Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:32:00.493Z] Movies recommended for you:
[2025-02-20T06:32:00.493Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:32:00.493Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:32:00.493Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19504.080 ms) ======
[2025-02-20T06:32:00.493Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-20T06:32:00.493Z] GC before operation: completed in 98.772 ms, heap usage 249.587 MB -> 49.115 MB.
[2025-02-20T06:32:03.376Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:32:06.302Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:32:09.204Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:32:12.126Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:32:13.453Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:32:14.785Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:32:16.856Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:32:18.182Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:32:18.818Z] 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.
[2025-02-20T06:32:18.818Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:32:18.818Z] Movies recommended for you:
[2025-02-20T06:32:18.818Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:32:18.818Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:32:18.818Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18248.842 ms) ======
[2025-02-20T06:32:18.818Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-20T06:32:18.818Z] GC before operation: completed in 128.184 ms, heap usage 179.465 MB -> 49.329 MB.
[2025-02-20T06:32:21.695Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:32:23.789Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:32:26.648Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:32:29.519Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:32:30.165Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:32:31.494Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:32:33.574Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:32:34.879Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:32:34.879Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T06:32:34.879Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:32:35.542Z] Movies recommended for you:
[2025-02-20T06:32:35.542Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:32:35.542Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:32:35.542Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16155.082 ms) ======
[2025-02-20T06:32:35.542Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-20T06:32:35.543Z] GC before operation: completed in 94.250 ms, heap usage 236.752 MB -> 49.731 MB.
[2025-02-20T06:32:38.189Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:32:40.407Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:32:43.315Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:32:46.197Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:32:47.517Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:32:48.827Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:32:50.881Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:32:52.312Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:32:52.312Z] 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.
[2025-02-20T06:32:52.312Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:32:52.312Z] Movies recommended for you:
[2025-02-20T06:32:52.312Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:32:52.312Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:32:52.312Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17036.984 ms) ======
[2025-02-20T06:32:52.312Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-20T06:32:52.312Z] GC before operation: completed in 90.760 ms, heap usage 321.843 MB -> 49.993 MB.
[2025-02-20T06:32:55.212Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:32:58.178Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:33:01.114Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:33:03.232Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:33:05.307Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:33:06.624Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:33:07.959Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:33:10.029Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:33:10.029Z] 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.
[2025-02-20T06:33:10.029Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:33:10.029Z] Movies recommended for you:
[2025-02-20T06:33:10.029Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:33:10.029Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:33:10.029Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17808.198 ms) ======
[2025-02-20T06:33:10.029Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-20T06:33:10.671Z] GC before operation: completed in 106.553 ms, heap usage 319.564 MB -> 50.039 MB.
[2025-02-20T06:33:12.777Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:33:15.689Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:33:18.209Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:33:21.166Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:33:22.512Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:33:23.875Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:33:25.988Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:33:28.085Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:33:28.085Z] 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.
[2025-02-20T06:33:28.085Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:33:28.085Z] Movies recommended for you:
[2025-02-20T06:33:28.085Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:33:28.085Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:33:28.085Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17953.741 ms) ======
[2025-02-20T06:33:28.085Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-20T06:33:28.740Z] GC before operation: completed in 115.875 ms, heap usage 271.926 MB -> 50.206 MB.
[2025-02-20T06:33:31.813Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:33:34.712Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:33:37.592Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:33:40.515Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:33:41.873Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:33:43.204Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:33:45.327Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:33:47.516Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:33:47.516Z] 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.
[2025-02-20T06:33:47.516Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:33:47.516Z] Movies recommended for you:
[2025-02-20T06:33:47.516Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:33:47.516Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:33:47.516Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19308.335 ms) ======
[2025-02-20T06:33:47.516Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-20T06:33:48.156Z] GC before operation: completed in 107.342 ms, heap usage 155.976 MB -> 50.419 MB.
[2025-02-20T06:33:50.235Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:33:53.154Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:33:56.147Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:33:58.225Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:33:59.959Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:34:01.307Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:34:03.460Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:34:04.771Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:34:04.771Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-02-20T06:34:04.771Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:34:04.771Z] Movies recommended for you:
[2025-02-20T06:34:04.771Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:34:04.771Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:34:04.771Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17203.859 ms) ======
[2025-02-20T06:34:04.771Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-20T06:34:05.395Z] GC before operation: completed in 106.685 ms, heap usage 343.378 MB -> 53.568 MB.
[2025-02-20T06:34:07.461Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:34:10.406Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:34:13.271Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:34:15.388Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:34:17.462Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:34:18.783Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:34:20.892Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:34:22.219Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:34:22.219Z] 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.
[2025-02-20T06:34:22.219Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:34:22.219Z] Movies recommended for you:
[2025-02-20T06:34:22.219Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:34:22.219Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:34:22.219Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17188.251 ms) ======
[2025-02-20T06:34:22.219Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-20T06:34:22.219Z] GC before operation: completed in 115.243 ms, heap usage 186.925 MB -> 50.222 MB.
[2025-02-20T06:34:25.130Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:34:27.210Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:34:30.076Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:34:32.172Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:34:34.236Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:34:35.582Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:34:36.894Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:34:38.200Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:34:38.200Z] 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.
[2025-02-20T06:34:38.839Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:34:38.839Z] Movies recommended for you:
[2025-02-20T06:34:38.839Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:34:38.839Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:34:38.839Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16187.358 ms) ======
[2025-02-20T06:34:38.839Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-20T06:34:38.839Z] GC before operation: completed in 102.406 ms, heap usage 336.878 MB -> 53.352 MB.
[2025-02-20T06:34:40.941Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:34:43.571Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:34:46.483Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:34:48.569Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:34:49.906Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:34:51.227Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:34:53.333Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:34:54.654Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:34:54.654Z] 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.
[2025-02-20T06:34:54.654Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:34:54.654Z] Movies recommended for you:
[2025-02-20T06:34:54.654Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:34:54.654Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:34:54.654Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16155.261 ms) ======
[2025-02-20T06:34:54.654Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-20T06:34:55.287Z] GC before operation: completed in 106.008 ms, heap usage 242.221 MB -> 50.256 MB.
[2025-02-20T06:34:57.600Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:35:00.539Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:35:03.470Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:35:06.370Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:35:08.431Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:35:09.871Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:35:11.233Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:35:13.327Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:35:13.958Z] 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.
[2025-02-20T06:35:13.958Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:35:13.958Z] Movies recommended for you:
[2025-02-20T06:35:13.958Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:35:13.958Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:35:13.958Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18793.847 ms) ======
[2025-02-20T06:35:13.958Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-20T06:35:13.958Z] GC before operation: completed in 90.165 ms, heap usage 275.205 MB -> 50.499 MB.
[2025-02-20T06:35:16.341Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:35:19.288Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:35:22.170Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:35:24.228Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:35:25.590Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:35:27.671Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:35:29.011Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:35:30.346Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:35:30.971Z] 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.
[2025-02-20T06:35:30.971Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:35:30.971Z] Movies recommended for you:
[2025-02-20T06:35:30.971Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:35:30.971Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:35:30.971Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17042.232 ms) ======
[2025-02-20T06:35:30.971Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-20T06:35:30.971Z] GC before operation: completed in 94.374 ms, heap usage 156.749 MB -> 50.209 MB.
[2025-02-20T06:35:33.166Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:35:35.195Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:35:38.045Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:35:40.119Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:35:41.420Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:35:42.716Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:35:44.013Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:35:45.318Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:35:45.318Z] 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.
[2025-02-20T06:35:45.318Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:35:45.318Z] Movies recommended for you:
[2025-02-20T06:35:45.318Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:35:45.318Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:35:45.318Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14383.470 ms) ======
[2025-02-20T06:35:45.318Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-20T06:35:45.318Z] GC before operation: completed in 86.830 ms, heap usage 181.419 MB -> 50.400 MB.
[2025-02-20T06:35:47.351Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:35:49.403Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:35:52.249Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:35:54.302Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:35:55.609Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:35:56.629Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:35:58.721Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:36:00.032Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:36:00.032Z] 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.
[2025-02-20T06:36:00.032Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:36:00.032Z] Movies recommended for you:
[2025-02-20T06:36:00.032Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:36:00.032Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:36:00.033Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14540.247 ms) ======
[2025-02-20T06:36:00.033Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-20T06:36:00.033Z] GC before operation: completed in 100.101 ms, heap usage 336.022 MB -> 50.581 MB.
[2025-02-20T06:36:02.134Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:36:05.075Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:36:07.145Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:36:09.222Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:36:11.312Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:36:12.673Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:36:14.034Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:36:15.368Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:36:15.368Z] 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.
[2025-02-20T06:36:15.368Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:36:16.001Z] Movies recommended for you:
[2025-02-20T06:36:16.001Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:36:16.001Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:36:16.001Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15582.275 ms) ======
[2025-02-20T06:36:16.001Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-20T06:36:16.001Z] GC before operation: completed in 107.795 ms, heap usage 277.953 MB -> 50.393 MB.
[2025-02-20T06:36:18.072Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:36:21.023Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:36:23.950Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:36:26.022Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:36:27.354Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:36:28.784Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:36:30.926Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:36:32.270Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:36:32.270Z] 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.
[2025-02-20T06:36:32.270Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:36:32.270Z] Movies recommended for you:
[2025-02-20T06:36:32.270Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:36:32.270Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:36:32.270Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16554.584 ms) ======
[2025-02-20T06:36:32.270Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-20T06:36:32.270Z] GC before operation: completed in 96.621 ms, heap usage 339.672 MB -> 53.672 MB.
[2025-02-20T06:36:34.772Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:36:37.680Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:36:40.558Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:36:42.610Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:36:44.703Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:36:46.112Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:36:48.249Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:36:50.453Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:36:50.453Z] 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.
[2025-02-20T06:36:50.453Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:36:50.453Z] Movies recommended for you:
[2025-02-20T06:36:50.453Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:36:50.453Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:36:50.453Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17935.399 ms) ======
[2025-02-20T06:36:50.453Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-20T06:36:50.453Z] GC before operation: completed in 131.036 ms, heap usage 199.426 MB -> 50.513 MB.
[2025-02-20T06:36:53.418Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T06:36:56.359Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T06:37:00.243Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T06:37:02.326Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T06:37:03.668Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T06:37:05.078Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T06:37:07.215Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T06:37:09.360Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T06:37:09.360Z] 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.
[2025-02-20T06:37:09.360Z] The best model improves the baseline by 14.34%.
[2025-02-20T06:37:10.017Z] Movies recommended for you:
[2025-02-20T06:37:10.017Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T06:37:10.017Z] There is no way to check that no silent failure occurred.
[2025-02-20T06:37:10.017Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19143.806 ms) ======
[2025-02-20T06:37:10.017Z] -----------------------------------
[2025-02-20T06:37:10.017Z] renaissance-movie-lens_0_PASSED
[2025-02-20T06:37:10.017Z] -----------------------------------
[2025-02-20T06:37:10.017Z]
[2025-02-20T06:37:10.017Z] TEST TEARDOWN:
[2025-02-20T06:37:10.017Z] Nothing to be done for teardown.
[2025-02-20T06:37:10.017Z] renaissance-movie-lens_0 Finish Time: Thu Feb 20 06:37:09 2025 Epoch Time (ms): 1740033429815