renaissance-movie-lens_0
[2024-07-31T22:17:57.051Z] Running test renaissance-movie-lens_0 ...
[2024-07-31T22:17:57.051Z] ===============================================
[2024-07-31T22:17:57.051Z] renaissance-movie-lens_0 Start Time: Wed Jul 31 22:17:56 2024 Epoch Time (ms): 1722464276406
[2024-07-31T22:17:57.051Z] variation: NoOptions
[2024-07-31T22:17:57.051Z] JVM_OPTIONS:
[2024-07-31T22:17:57.051Z] { \
[2024-07-31T22:17:57.051Z] echo ""; echo "TEST SETUP:"; \
[2024-07-31T22:17:57.051Z] echo "Nothing to be done for setup."; \
[2024-07-31T22:17:57.051Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17224635699248/renaissance-movie-lens_0"; \
[2024-07-31T22:17:57.051Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17224635699248/renaissance-movie-lens_0"; \
[2024-07-31T22:17:57.051Z] echo ""; echo "TESTING:"; \
[2024-07-31T22:17:57.051Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17224635699248/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-07-31T22:17:57.051Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17224635699248/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-07-31T22:17:57.051Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-07-31T22:17:57.051Z] echo "Nothing to be done for teardown."; \
[2024-07-31T22:17:57.051Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17224635699248/TestTargetResult";
[2024-07-31T22:17:57.051Z]
[2024-07-31T22:17:57.051Z] TEST SETUP:
[2024-07-31T22:17:57.051Z] Nothing to be done for setup.
[2024-07-31T22:17:57.051Z]
[2024-07-31T22:17:57.051Z] TESTING:
[2024-07-31T22:17:58.976Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-07-31T22:18:00.906Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-07-31T22:18:02.831Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-07-31T22:18:03.419Z] Training: 60056, validation: 20285, test: 19854
[2024-07-31T22:18:03.419Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-07-31T22:18:03.419Z] GC before operation: completed in 55.409 ms, heap usage 44.479 MB -> 37.054 MB.
[2024-07-31T22:18:07.930Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:18:11.483Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:18:14.178Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:18:16.124Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:18:18.067Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:18:19.294Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:18:20.526Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:18:22.462Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:18:22.462Z] 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.
[2024-07-31T22:18:22.462Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:18:23.049Z] Movies recommended for you:
[2024-07-31T22:18:23.049Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:18:23.049Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:18:23.049Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (19434.907 ms) ======
[2024-07-31T22:18:23.049Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-07-31T22:18:23.049Z] GC before operation: completed in 106.521 ms, heap usage 164.955 MB -> 50.139 MB.
[2024-07-31T22:18:24.970Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:18:27.666Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:18:29.592Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:18:31.556Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:18:33.481Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:18:34.067Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:18:35.992Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:18:36.579Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:18:37.166Z] 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.
[2024-07-31T22:18:37.166Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:18:37.166Z] Movies recommended for you:
[2024-07-31T22:18:37.166Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:18:37.166Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:18:37.166Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (14326.980 ms) ======
[2024-07-31T22:18:37.166Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-07-31T22:18:37.166Z] GC before operation: completed in 71.195 ms, heap usage 66.813 MB -> 48.972 MB.
[2024-07-31T22:18:39.861Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:18:41.785Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:18:43.708Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:18:45.632Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:18:46.861Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:18:47.449Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:18:49.403Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:18:49.999Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:18:50.588Z] 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.
[2024-07-31T22:18:50.588Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:18:50.588Z] Movies recommended for you:
[2024-07-31T22:18:50.588Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:18:50.588Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:18:50.588Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13110.856 ms) ======
[2024-07-31T22:18:50.588Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-07-31T22:18:50.588Z] GC before operation: completed in 79.540 ms, heap usage 207.677 MB -> 49.276 MB.
[2024-07-31T22:18:52.516Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:18:54.450Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:18:56.390Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:18:58.315Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:18:59.542Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:19:00.768Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:19:01.997Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:19:03.224Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:19:03.224Z] 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.
[2024-07-31T22:19:03.224Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:19:03.813Z] Movies recommended for you:
[2024-07-31T22:19:03.813Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:19:03.813Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:19:03.813Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (12998.270 ms) ======
[2024-07-31T22:19:03.813Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-07-31T22:19:03.813Z] GC before operation: completed in 87.567 ms, heap usage 119.641 MB -> 49.594 MB.
[2024-07-31T22:19:05.739Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:19:07.661Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:19:09.632Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:19:11.581Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:19:12.889Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:19:14.112Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:19:15.335Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:19:16.561Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:19:17.154Z] 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.
[2024-07-31T22:19:17.154Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:19:17.154Z] Movies recommended for you:
[2024-07-31T22:19:17.154Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:19:17.154Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:19:17.154Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13350.676 ms) ======
[2024-07-31T22:19:17.154Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-07-31T22:19:17.154Z] GC before operation: completed in 107.679 ms, heap usage 249.848 MB -> 49.971 MB.
[2024-07-31T22:19:19.078Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:19:21.004Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:19:22.932Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:19:24.855Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:19:26.080Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:19:27.305Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:19:28.533Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:19:29.758Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:19:29.758Z] 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.
[2024-07-31T22:19:29.758Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:19:29.758Z] Movies recommended for you:
[2024-07-31T22:19:29.758Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:19:29.758Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:19:29.758Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12913.469 ms) ======
[2024-07-31T22:19:29.758Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-07-31T22:19:30.346Z] GC before operation: completed in 95.888 ms, heap usage 183.934 MB -> 49.870 MB.
[2024-07-31T22:19:32.272Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:19:34.220Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:19:36.147Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:19:38.094Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:19:39.324Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:19:40.550Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:19:41.777Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:19:43.001Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:19:43.588Z] 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.
[2024-07-31T22:19:43.588Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:19:43.588Z] Movies recommended for you:
[2024-07-31T22:19:43.588Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:19:43.588Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:19:43.588Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13385.511 ms) ======
[2024-07-31T22:19:43.588Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-07-31T22:19:43.588Z] GC before operation: completed in 71.096 ms, heap usage 280.193 MB -> 50.197 MB.
[2024-07-31T22:19:45.511Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:19:47.431Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:19:49.352Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:19:51.276Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:19:51.863Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:19:53.789Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:19:55.013Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:19:55.601Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:19:56.188Z] 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.
[2024-07-31T22:19:56.188Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:19:56.188Z] Movies recommended for you:
[2024-07-31T22:19:56.188Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:19:56.188Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:19:56.188Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12683.041 ms) ======
[2024-07-31T22:19:56.188Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-07-31T22:19:56.188Z] GC before operation: completed in 81.463 ms, heap usage 58.470 MB -> 50.147 MB.
[2024-07-31T22:19:58.111Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:20:00.032Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:20:01.970Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:20:03.891Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:20:05.117Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:20:06.345Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:20:07.571Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:20:08.800Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:20:08.800Z] 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.
[2024-07-31T22:20:08.800Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:20:08.800Z] Movies recommended for you:
[2024-07-31T22:20:08.800Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:20:08.800Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:20:08.800Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12766.447 ms) ======
[2024-07-31T22:20:08.800Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-07-31T22:20:09.391Z] GC before operation: completed in 88.602 ms, heap usage 268.434 MB -> 50.307 MB.
[2024-07-31T22:20:11.324Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:20:13.249Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:20:15.173Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:20:17.099Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:20:18.335Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:20:18.922Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:20:20.149Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:20:21.378Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:20:21.971Z] 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.
[2024-07-31T22:20:21.971Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:20:21.971Z] Movies recommended for you:
[2024-07-31T22:20:21.971Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:20:21.971Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:20:21.971Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12781.371 ms) ======
[2024-07-31T22:20:21.971Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-07-31T22:20:21.971Z] GC before operation: completed in 88.462 ms, heap usage 189.229 MB -> 50.227 MB.
[2024-07-31T22:20:23.897Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:20:25.820Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:20:27.747Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:20:29.673Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:20:30.272Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:20:31.505Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:20:32.751Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:20:33.978Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:20:33.978Z] 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.
[2024-07-31T22:20:33.978Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:20:34.584Z] Movies recommended for you:
[2024-07-31T22:20:34.584Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:20:34.584Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:20:34.584Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12323.807 ms) ======
[2024-07-31T22:20:34.584Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-07-31T22:20:34.584Z] GC before operation: completed in 98.702 ms, heap usage 162.524 MB -> 49.941 MB.
[2024-07-31T22:20:36.527Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:20:38.463Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:20:41.166Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:20:43.101Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:20:44.331Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:20:45.561Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:20:46.815Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:20:48.055Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:20:48.055Z] 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.
[2024-07-31T22:20:48.055Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:20:48.055Z] Movies recommended for you:
[2024-07-31T22:20:48.055Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:20:48.055Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:20:48.055Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13673.794 ms) ======
[2024-07-31T22:20:48.055Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-07-31T22:20:48.055Z] GC before operation: completed in 102.718 ms, heap usage 213.131 MB -> 50.182 MB.
[2024-07-31T22:20:49.991Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:20:52.726Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:20:54.652Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:20:56.579Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:20:57.806Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:20:59.049Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:21:00.274Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:21:01.498Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:21:01.498Z] 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.
[2024-07-31T22:21:01.498Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:21:01.498Z] Movies recommended for you:
[2024-07-31T22:21:01.498Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:21:01.498Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:21:01.498Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13550.465 ms) ======
[2024-07-31T22:21:01.498Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-07-31T22:21:02.087Z] GC before operation: completed in 72.280 ms, heap usage 257.203 MB -> 50.360 MB.
[2024-07-31T22:21:04.010Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:21:05.931Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:21:07.855Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:21:09.798Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:21:11.111Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:21:11.699Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:21:12.927Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:21:14.155Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:21:14.743Z] 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.
[2024-07-31T22:21:14.743Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:21:14.743Z] Movies recommended for you:
[2024-07-31T22:21:14.743Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:21:14.743Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:21:14.743Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12769.886 ms) ======
[2024-07-31T22:21:14.743Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-07-31T22:21:14.743Z] GC before operation: completed in 77.047 ms, heap usage 117.146 MB -> 50.009 MB.
[2024-07-31T22:21:16.672Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:21:18.607Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:21:20.534Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:21:21.761Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:21:22.989Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:21:24.220Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:21:25.446Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:21:26.044Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:21:26.632Z] 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.
[2024-07-31T22:21:26.632Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:21:26.632Z] Movies recommended for you:
[2024-07-31T22:21:26.632Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:21:26.632Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:21:26.632Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11826.212 ms) ======
[2024-07-31T22:21:26.632Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-07-31T22:21:26.632Z] GC before operation: completed in 87.456 ms, heap usage 245.416 MB -> 50.320 MB.
[2024-07-31T22:21:28.562Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:21:29.788Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:21:31.717Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:21:33.233Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:21:34.583Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:21:35.884Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:21:37.114Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:21:38.349Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:21:38.349Z] 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.
[2024-07-31T22:21:38.349Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:21:38.349Z] Movies recommended for you:
[2024-07-31T22:21:38.349Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:21:38.349Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:21:38.349Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11754.480 ms) ======
[2024-07-31T22:21:38.349Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-07-31T22:21:38.349Z] GC before operation: completed in 84.240 ms, heap usage 269.166 MB -> 50.451 MB.
[2024-07-31T22:21:40.276Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:21:42.215Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:21:44.915Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:21:46.146Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:21:47.377Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:21:47.966Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:21:49.194Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:21:50.443Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:21:50.443Z] 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.
[2024-07-31T22:21:50.443Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:21:50.443Z] Movies recommended for you:
[2024-07-31T22:21:50.443Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:21:50.443Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:21:50.443Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12170.949 ms) ======
[2024-07-31T22:21:50.443Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-07-31T22:21:50.443Z] GC before operation: completed in 66.728 ms, heap usage 297.729 MB -> 50.261 MB.
[2024-07-31T22:21:52.375Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:21:54.356Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:21:55.584Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:21:56.814Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:21:58.044Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:21:59.274Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:22:00.505Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:22:01.095Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:22:01.693Z] 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.
[2024-07-31T22:22:01.693Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:22:01.693Z] Movies recommended for you:
[2024-07-31T22:22:01.693Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:22:01.693Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:22:01.693Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (10955.461 ms) ======
[2024-07-31T22:22:01.693Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-07-31T22:22:01.693Z] GC before operation: completed in 81.723 ms, heap usage 162.593 MB -> 50.283 MB.
[2024-07-31T22:22:03.630Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:22:05.946Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:22:07.964Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:22:09.194Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:22:10.430Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:22:11.657Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:22:12.884Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:22:14.112Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:22:14.112Z] 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.
[2024-07-31T22:22:14.112Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:22:14.112Z] Movies recommended for you:
[2024-07-31T22:22:14.112Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:22:14.112Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:22:14.112Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12520.863 ms) ======
[2024-07-31T22:22:14.112Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-07-31T22:22:14.112Z] GC before operation: completed in 62.436 ms, heap usage 131.120 MB -> 50.337 MB.
[2024-07-31T22:22:16.050Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T22:22:17.975Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T22:22:19.899Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T22:22:21.823Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T22:22:22.411Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T22:22:23.634Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T22:22:24.858Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T22:22:25.445Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T22:22:25.445Z] 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.
[2024-07-31T22:22:25.445Z] The best model improves the baseline by 14.34%.
[2024-07-31T22:22:26.031Z] Movies recommended for you:
[2024-07-31T22:22:26.031Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T22:22:26.031Z] There is no way to check that no silent failure occurred.
[2024-07-31T22:22:26.031Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11441.738 ms) ======
[2024-07-31T22:22:26.031Z] -----------------------------------
[2024-07-31T22:22:26.031Z] renaissance-movie-lens_0_PASSED
[2024-07-31T22:22:26.031Z] -----------------------------------
[2024-07-31T22:22:26.031Z]
[2024-07-31T22:22:26.031Z] TEST TEARDOWN:
[2024-07-31T22:22:26.031Z] Nothing to be done for teardown.
[2024-07-31T22:22:26.031Z] renaissance-movie-lens_0 Finish Time: Wed Jul 31 22:22:25 2024 Epoch Time (ms): 1722464545778