renaissance-movie-lens_0
[2024-08-08T05:21:36.462Z] Running test renaissance-movie-lens_0 ...
[2024-08-08T05:21:36.462Z] ===============================================
[2024-08-08T05:21:36.462Z] renaissance-movie-lens_0 Start Time: Thu Aug 8 05:21:35 2024 Epoch Time (ms): 1723094496002
[2024-08-08T05:21:36.462Z] variation: NoOptions
[2024-08-08T05:21:36.462Z] JVM_OPTIONS:
[2024-08-08T05:21:36.462Z] { \
[2024-08-08T05:21:36.462Z] echo ""; echo "TEST SETUP:"; \
[2024-08-08T05:21:36.462Z] echo "Nothing to be done for setup."; \
[2024-08-08T05:21:36.462Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17230927128773/renaissance-movie-lens_0"; \
[2024-08-08T05:21:36.462Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17230927128773/renaissance-movie-lens_0"; \
[2024-08-08T05:21:36.462Z] echo ""; echo "TESTING:"; \
[2024-08-08T05:21:36.462Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17230927128773/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-08T05:21:36.462Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17230927128773/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-08T05:21:36.462Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-08T05:21:36.462Z] echo "Nothing to be done for teardown."; \
[2024-08-08T05:21:36.462Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17230927128773/TestTargetResult";
[2024-08-08T05:21:36.462Z]
[2024-08-08T05:21:36.462Z] TEST SETUP:
[2024-08-08T05:21:36.462Z] Nothing to be done for setup.
[2024-08-08T05:21:36.462Z]
[2024-08-08T05:21:36.462Z] TESTING:
[2024-08-08T05:22:17.852Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-08T05:22:20.329Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 16) threads.
[2024-08-08T05:22:27.199Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-08T05:22:27.967Z] Training: 60056, validation: 20285, test: 19854
[2024-08-08T05:22:27.967Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-08T05:22:27.967Z] GC before operation: completed in 62.591 ms, heap usage 109.843 MB -> 37.483 MB.
[2024-08-08T05:22:33.551Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:22:36.959Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:22:55.772Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:22:59.216Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:23:01.683Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:23:03.278Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:23:06.706Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:23:08.291Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:23:09.079Z] 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.
[2024-08-08T05:23:09.079Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:23:09.079Z] Movies recommended for you:
[2024-08-08T05:23:09.079Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:23:09.079Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:23:09.079Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (41223.069 ms) ======
[2024-08-08T05:23:09.079Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-08T05:23:09.079Z] GC before operation: completed in 95.323 ms, heap usage 471.958 MB -> 48.809 MB.
[2024-08-08T05:23:12.501Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:23:15.925Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:23:21.514Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:23:24.931Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:23:26.547Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:23:29.192Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:23:31.697Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:23:34.193Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:23:34.193Z] 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.
[2024-08-08T05:23:34.193Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:23:34.193Z] Movies recommended for you:
[2024-08-08T05:23:34.193Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:23:34.193Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:23:34.193Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25424.120 ms) ======
[2024-08-08T05:23:34.193Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-08T05:23:34.961Z] GC before operation: completed in 123.241 ms, heap usage 1.137 GB -> 55.678 MB.
[2024-08-08T05:23:38.397Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:23:41.815Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:23:50.086Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:23:52.549Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:23:55.040Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:23:56.643Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:24:00.065Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:24:02.531Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:24:03.296Z] 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.
[2024-08-08T05:24:03.296Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:24:03.296Z] Movies recommended for you:
[2024-08-08T05:24:03.296Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:24:03.296Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:24:03.296Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (28568.911 ms) ======
[2024-08-08T05:24:03.296Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-08T05:24:03.296Z] GC before operation: completed in 125.206 ms, heap usage 1.035 GB -> 55.835 MB.
[2024-08-08T05:24:06.710Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:24:12.575Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:24:20.827Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:24:24.344Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:24:26.891Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:24:28.488Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:24:31.908Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:24:33.496Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:24:34.264Z] 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.
[2024-08-08T05:24:34.264Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:24:34.264Z] Movies recommended for you:
[2024-08-08T05:24:34.264Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:24:34.264Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:24:34.264Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (30922.077 ms) ======
[2024-08-08T05:24:34.264Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-08T05:24:34.264Z] GC before operation: completed in 109.456 ms, heap usage 280.024 MB -> 51.961 MB.
[2024-08-08T05:24:37.728Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:24:42.180Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:24:49.103Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:24:51.561Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:24:53.163Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:24:55.629Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:25:00.070Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:25:02.555Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:25:02.556Z] 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.
[2024-08-08T05:25:02.556Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:25:03.323Z] Movies recommended for you:
[2024-08-08T05:25:03.323Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:25:03.323Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:25:03.323Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (28579.301 ms) ======
[2024-08-08T05:25:03.323Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-08T05:25:03.323Z] GC before operation: completed in 88.263 ms, heap usage 433.052 MB -> 52.235 MB.
[2024-08-08T05:25:05.791Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:25:10.304Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:25:26.381Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:25:28.846Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:25:32.258Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:25:36.419Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:25:46.269Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:25:47.037Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:25:47.804Z] 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.
[2024-08-08T05:25:47.804Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:25:47.804Z] Movies recommended for you:
[2024-08-08T05:25:47.804Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:25:47.804Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:25:47.804Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (44701.907 ms) ======
[2024-08-08T05:25:47.804Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-08T05:25:47.804Z] GC before operation: completed in 135.233 ms, heap usage 2.571 GB -> 57.090 MB.
[2024-08-08T05:25:51.218Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:25:58.077Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:26:04.983Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:26:08.493Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:26:10.968Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:26:13.437Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:26:17.890Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:26:20.364Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:26:20.365Z] 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.
[2024-08-08T05:26:20.365Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:26:20.365Z] Movies recommended for you:
[2024-08-08T05:26:20.365Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:26:20.365Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:26:20.365Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (32857.359 ms) ======
[2024-08-08T05:26:20.365Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-08T05:26:21.130Z] GC before operation: completed in 107.754 ms, heap usage 389.303 MB -> 52.318 MB.
[2024-08-08T05:26:24.559Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:26:27.973Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:26:33.570Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:26:36.036Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:26:38.502Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:26:40.086Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:26:48.340Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:26:50.803Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:26:50.803Z] 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.
[2024-08-08T05:26:50.803Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:26:51.570Z] Movies recommended for you:
[2024-08-08T05:26:51.570Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:26:51.570Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:26:51.570Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (30357.614 ms) ======
[2024-08-08T05:26:51.570Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-08T05:26:51.570Z] GC before operation: completed in 115.738 ms, heap usage 329.858 MB -> 52.601 MB.
[2024-08-08T05:26:55.023Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:26:59.653Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:27:08.108Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:27:11.523Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:27:13.994Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:27:15.593Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:27:19.002Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:27:20.604Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:27:21.370Z] 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.
[2024-08-08T05:27:21.370Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:27:21.370Z] Movies recommended for you:
[2024-08-08T05:27:21.370Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:27:21.370Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:27:21.370Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (29951.728 ms) ======
[2024-08-08T05:27:21.370Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-08T05:27:21.370Z] GC before operation: completed in 126.821 ms, heap usage 1.195 GB -> 56.752 MB.
[2024-08-08T05:27:24.777Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:27:28.202Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:27:36.484Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:27:38.946Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:27:41.504Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:27:43.093Z] RMSE (validation) = 1.117495376637101 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:27:46.508Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:27:48.089Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:27:48.859Z] 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.
[2024-08-08T05:27:48.859Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:27:48.859Z] Movies recommended for you:
[2024-08-08T05:27:48.859Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:27:48.859Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:27:48.859Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (27480.766 ms) ======
[2024-08-08T05:27:48.859Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-08T05:27:48.859Z] GC before operation: completed in 108.296 ms, heap usage 448.294 MB -> 52.646 MB.
[2024-08-08T05:27:52.278Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:28:00.562Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:28:07.410Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:28:09.998Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:28:11.586Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:28:14.046Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:28:19.016Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:28:21.486Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:28:21.486Z] 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.
[2024-08-08T05:28:21.486Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:28:22.260Z] Movies recommended for you:
[2024-08-08T05:28:22.260Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:28:22.260Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:28:22.260Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (32965.074 ms) ======
[2024-08-08T05:28:22.260Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-08T05:28:22.260Z] GC before operation: completed in 118.292 ms, heap usage 439.192 MB -> 52.316 MB.
[2024-08-08T05:28:25.682Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:28:29.115Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:28:38.953Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:28:41.421Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:28:43.904Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:28:46.390Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:28:51.980Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:28:53.578Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:28:53.578Z] 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.
[2024-08-08T05:28:53.578Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:28:54.348Z] Movies recommended for you:
[2024-08-08T05:28:54.348Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:28:54.348Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:28:54.348Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (32002.862 ms) ======
[2024-08-08T05:28:54.348Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-08T05:28:54.348Z] GC before operation: completed in 118.353 ms, heap usage 397.776 MB -> 52.461 MB.
[2024-08-08T05:28:57.763Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:29:01.181Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:29:20.056Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:29:21.641Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:29:24.102Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:29:25.689Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:29:29.097Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:29:30.706Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:29:31.473Z] 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.
[2024-08-08T05:29:31.474Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:29:31.474Z] Movies recommended for you:
[2024-08-08T05:29:31.474Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:29:31.474Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:29:31.474Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (37200.138 ms) ======
[2024-08-08T05:29:31.474Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-08T05:29:31.474Z] GC before operation: completed in 105.936 ms, heap usage 508.944 MB -> 52.720 MB.
[2024-08-08T05:29:34.886Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:29:38.316Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:29:42.769Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:29:46.172Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:29:47.759Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:29:50.224Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:29:53.418Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:29:55.005Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:29:55.005Z] 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.
[2024-08-08T05:29:55.005Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:29:55.773Z] Movies recommended for you:
[2024-08-08T05:29:55.773Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:29:55.773Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:29:55.773Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (24000.977 ms) ======
[2024-08-08T05:29:55.773Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-08T05:29:55.773Z] GC before operation: completed in 119.025 ms, heap usage 807.425 MB -> 55.903 MB.
[2024-08-08T05:29:59.209Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:30:02.634Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:30:07.090Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:30:10.527Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:30:12.987Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:30:14.570Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:30:19.016Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:30:21.489Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:30:21.489Z] 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.
[2024-08-08T05:30:21.489Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:30:21.489Z] Movies recommended for you:
[2024-08-08T05:30:21.489Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:30:21.489Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:30:21.489Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (25904.035 ms) ======
[2024-08-08T05:30:21.489Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-08T05:30:21.489Z] GC before operation: completed in 121.725 ms, heap usage 561.188 MB -> 55.937 MB.
[2024-08-08T05:30:24.902Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:30:28.327Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:30:33.910Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:30:37.323Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:30:39.785Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:30:41.374Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:30:44.785Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:30:47.261Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:30:47.261Z] 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.
[2024-08-08T05:30:47.261Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:30:47.261Z] Movies recommended for you:
[2024-08-08T05:30:47.261Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:30:47.261Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:30:47.261Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (25572.403 ms) ======
[2024-08-08T05:30:47.261Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-08T05:30:47.261Z] GC before operation: completed in 125.482 ms, heap usage 563.913 MB -> 56.036 MB.
[2024-08-08T05:30:50.676Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:30:54.088Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:30:58.540Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:31:01.953Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:31:03.548Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:31:06.022Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:31:08.664Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:31:10.447Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:31:11.217Z] 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.
[2024-08-08T05:31:11.217Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:31:11.217Z] Movies recommended for you:
[2024-08-08T05:31:11.217Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:31:11.217Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:31:11.217Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (23670.526 ms) ======
[2024-08-08T05:31:11.217Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-08T05:31:11.217Z] GC before operation: completed in 136.206 ms, heap usage 2.797 GB -> 57.377 MB.
[2024-08-08T05:31:14.625Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:31:17.107Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:31:22.698Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:31:26.106Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:31:28.575Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:31:30.161Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:31:33.566Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:31:35.157Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:31:35.157Z] 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.
[2024-08-08T05:31:35.157Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:31:35.928Z] Movies recommended for you:
[2024-08-08T05:31:35.928Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:31:35.928Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:31:35.928Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (24474.980 ms) ======
[2024-08-08T05:31:35.928Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-08T05:31:35.928Z] GC before operation: completed in 122.444 ms, heap usage 283.829 MB -> 52.484 MB.
[2024-08-08T05:31:39.348Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:31:42.764Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:31:48.342Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:31:50.807Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:31:53.279Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:31:54.866Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:31:58.466Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:32:00.076Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:32:00.076Z] 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.
[2024-08-08T05:32:00.076Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:32:00.843Z] Movies recommended for you:
[2024-08-08T05:32:00.843Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:32:00.843Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:32:00.843Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (24783.068 ms) ======
[2024-08-08T05:32:00.843Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-08T05:32:00.843Z] GC before operation: completed in 123.912 ms, heap usage 450.061 MB -> 52.776 MB.
[2024-08-08T05:32:04.272Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T05:32:06.730Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T05:32:11.342Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T05:32:14.769Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T05:32:16.361Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T05:32:18.840Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T05:32:21.320Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T05:32:23.464Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T05:32:23.464Z] 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.
[2024-08-08T05:32:23.464Z] The best model improves the baseline by 14.43%.
[2024-08-08T05:32:23.464Z] Movies recommended for you:
[2024-08-08T05:32:23.464Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T05:32:23.464Z] There is no way to check that no silent failure occurred.
[2024-08-08T05:32:23.464Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (22597.032 ms) ======
[2024-08-08T05:32:24.282Z] -----------------------------------
[2024-08-08T05:32:24.282Z] renaissance-movie-lens_0_PASSED
[2024-08-08T05:32:24.282Z] -----------------------------------
[2024-08-08T05:32:24.282Z]
[2024-08-08T05:32:24.282Z] TEST TEARDOWN:
[2024-08-08T05:32:24.282Z] Nothing to be done for teardown.
[2024-08-08T05:32:24.282Z] renaissance-movie-lens_0 Finish Time: Thu Aug 8 05:32:23 2024 Epoch Time (ms): 1723095143624