renaissance-movie-lens_0
[2024-08-23T22:42:25.018Z] Running test renaissance-movie-lens_0 ...
[2024-08-23T22:42:25.018Z] ===============================================
[2024-08-23T22:42:25.018Z] renaissance-movie-lens_0 Start Time: Fri Aug 23 18:42:24 2024 Epoch Time (ms): 1724452944571
[2024-08-23T22:42:25.018Z] variation: NoOptions
[2024-08-23T22:42:25.018Z] JVM_OPTIONS:
[2024-08-23T22:42:25.018Z] { \
[2024-08-23T22:42:25.018Z] echo ""; echo "TEST SETUP:"; \
[2024-08-23T22:42:25.018Z] echo "Nothing to be done for setup."; \
[2024-08-23T22:42:25.018Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17244503772563/renaissance-movie-lens_0"; \
[2024-08-23T22:42:25.018Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17244503772563/renaissance-movie-lens_0"; \
[2024-08-23T22:42:25.018Z] echo ""; echo "TESTING:"; \
[2024-08-23T22:42:25.018Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17244503772563/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-23T22:42:25.018Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17244503772563/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-23T22:42:25.018Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-23T22:42:25.018Z] echo "Nothing to be done for teardown."; \
[2024-08-23T22:42:25.018Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17244503772563/TestTargetResult";
[2024-08-23T22:42:25.018Z]
[2024-08-23T22:42:25.018Z] TEST SETUP:
[2024-08-23T22:42:25.018Z] Nothing to be done for setup.
[2024-08-23T22:42:25.018Z]
[2024-08-23T22:42:25.018Z] TESTING:
[2024-08-23T22:42:29.983Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-23T22:42:34.340Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-23T22:42:44.694Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-23T22:42:47.414Z] Training: 60056, validation: 20285, test: 19854
[2024-08-23T22:42:47.414Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-23T22:42:49.679Z] GC before operation: completed in 824.602 ms, heap usage 131.559 MB -> 36.460 MB.
[2024-08-23T22:43:11.839Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:43:22.746Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:43:33.694Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:43:44.791Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:43:48.946Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:43:54.714Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:44:03.230Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:44:08.524Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:44:08.524Z] 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.
[2024-08-23T22:44:08.524Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:44:09.160Z] Movies recommended for you:
[2024-08-23T22:44:09.160Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:44:09.160Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:44:09.160Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (80749.419 ms) ======
[2024-08-23T22:44:09.160Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-23T22:44:09.160Z] GC before operation: completed in 303.650 ms, heap usage 319.701 MB -> 49.583 MB.
[2024-08-23T22:44:15.124Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:44:22.755Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:44:32.592Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:44:40.910Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:44:46.488Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:44:54.783Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:44:59.154Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:45:06.046Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:45:06.046Z] 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.
[2024-08-23T22:45:06.046Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:45:06.864Z] Movies recommended for you:
[2024-08-23T22:45:06.864Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:45:06.864Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:45:06.864Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (57226.743 ms) ======
[2024-08-23T22:45:06.864Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-23T22:45:06.864Z] GC before operation: completed in 621.522 ms, heap usage 252.757 MB -> 49.737 MB.
[2024-08-23T22:45:18.388Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:45:29.532Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:45:37.395Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:45:43.415Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:45:48.445Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:45:52.714Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:45:57.819Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:46:01.804Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:46:01.804Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-23T22:46:01.804Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:46:02.425Z] Movies recommended for you:
[2024-08-23T22:46:02.425Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:46:02.425Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:46:02.425Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (55193.531 ms) ======
[2024-08-23T22:46:02.425Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-23T22:46:02.425Z] GC before operation: completed in 254.691 ms, heap usage 107.263 MB -> 51.328 MB.
[2024-08-23T22:46:17.292Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:46:28.705Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:46:35.384Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:46:45.777Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:46:48.770Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:46:54.537Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:46:58.811Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:47:04.386Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:47:04.386Z] 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.
[2024-08-23T22:47:04.386Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:47:05.041Z] Movies recommended for you:
[2024-08-23T22:47:05.041Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:47:05.041Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:47:05.041Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (62113.345 ms) ======
[2024-08-23T22:47:05.041Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-23T22:47:05.041Z] GC before operation: completed in 294.291 ms, heap usage 150.051 MB -> 49.066 MB.
[2024-08-23T22:47:13.323Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:47:19.851Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:47:29.030Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:47:34.285Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:47:38.377Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:47:41.291Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:47:43.788Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:47:46.857Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:47:47.504Z] 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.
[2024-08-23T22:47:47.504Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:47:47.504Z] Movies recommended for you:
[2024-08-23T22:47:47.504Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:47:47.504Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:47:47.504Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (42712.035 ms) ======
[2024-08-23T22:47:47.504Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-23T22:47:48.152Z] GC before operation: completed in 229.381 ms, heap usage 222.430 MB -> 49.254 MB.
[2024-08-23T22:47:53.197Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:47:59.295Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:48:04.612Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:48:10.912Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:48:15.128Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:48:19.251Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:48:22.639Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:48:27.167Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:48:27.838Z] 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.
[2024-08-23T22:48:27.838Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:48:27.838Z] Movies recommended for you:
[2024-08-23T22:48:27.838Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:48:27.838Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:48:27.838Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (40072.324 ms) ======
[2024-08-23T22:48:27.838Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-23T22:48:28.527Z] GC before operation: completed in 178.541 ms, heap usage 241.265 MB -> 50.947 MB.
[2024-08-23T22:48:35.265Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:48:43.659Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:48:50.147Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:48:58.403Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:49:00.577Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:49:03.529Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:49:06.524Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:49:10.545Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:49:10.545Z] 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.
[2024-08-23T22:49:10.545Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:49:11.284Z] Movies recommended for you:
[2024-08-23T22:49:11.284Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:49:11.284Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:49:11.284Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42912.253 ms) ======
[2024-08-23T22:49:11.284Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-23T22:49:11.284Z] GC before operation: completed in 241.184 ms, heap usage 338.518 MB -> 52.652 MB.
[2024-08-23T22:49:17.316Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:49:23.476Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:49:28.451Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:49:34.704Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:49:38.743Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:49:41.002Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:49:45.054Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:49:47.274Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:49:47.893Z] 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.
[2024-08-23T22:49:47.893Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:49:48.585Z] Movies recommended for you:
[2024-08-23T22:49:48.585Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:49:48.585Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:49:48.585Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (36950.344 ms) ======
[2024-08-23T22:49:48.585Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-23T22:49:48.585Z] GC before operation: completed in 232.348 ms, heap usage 301.470 MB -> 49.718 MB.
[2024-08-23T22:49:56.080Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:50:01.218Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:50:09.159Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:50:14.156Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:50:16.340Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:50:20.256Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:50:24.315Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:50:28.094Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:50:28.095Z] 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.
[2024-08-23T22:50:28.095Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:50:28.964Z] Movies recommended for you:
[2024-08-23T22:50:28.964Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:50:28.964Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:50:28.964Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (39963.539 ms) ======
[2024-08-23T22:50:28.964Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-23T22:50:28.964Z] GC before operation: completed in 509.430 ms, heap usage 250.494 MB -> 49.478 MB.
[2024-08-23T22:50:37.002Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:50:44.896Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:50:51.227Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:50:56.186Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:50:58.276Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:51:01.382Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:51:06.202Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:51:08.465Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:51:09.168Z] 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.
[2024-08-23T22:51:09.866Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:51:09.866Z] Movies recommended for you:
[2024-08-23T22:51:09.866Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:51:09.866Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:51:09.866Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (40713.324 ms) ======
[2024-08-23T22:51:09.866Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-23T22:51:09.866Z] GC before operation: completed in 411.694 ms, heap usage 275.394 MB -> 49.643 MB.
[2024-08-23T22:51:18.144Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:51:24.766Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:51:31.155Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:51:38.182Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:51:43.272Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:51:45.446Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:51:49.559Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:51:52.533Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:51:52.533Z] 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.
[2024-08-23T22:51:53.144Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:51:53.144Z] Movies recommended for you:
[2024-08-23T22:51:53.144Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:51:53.144Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:51:53.144Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (42891.243 ms) ======
[2024-08-23T22:51:53.144Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-23T22:51:53.144Z] GC before operation: completed in 162.932 ms, heap usage 93.623 MB -> 49.192 MB.
[2024-08-23T22:52:00.909Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:52:08.750Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:52:13.878Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:52:19.994Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:52:23.408Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:52:26.568Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:52:32.138Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:52:35.246Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:52:35.246Z] 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.
[2024-08-23T22:52:35.246Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:52:35.887Z] Movies recommended for you:
[2024-08-23T22:52:35.887Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:52:35.887Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:52:35.887Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (42430.401 ms) ======
[2024-08-23T22:52:35.887Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-23T22:52:35.887Z] GC before operation: completed in 217.756 ms, heap usage 199.536 MB -> 49.425 MB.
[2024-08-23T22:52:41.215Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:52:45.048Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:52:50.104Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:52:55.116Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:53:00.667Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:53:03.713Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:53:09.549Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:53:11.698Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:53:12.375Z] 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.
[2024-08-23T22:53:12.375Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:53:12.375Z] Movies recommended for you:
[2024-08-23T22:53:12.375Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:53:12.375Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:53:12.375Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36622.825 ms) ======
[2024-08-23T22:53:12.375Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-23T22:53:12.375Z] GC before operation: completed in 158.979 ms, heap usage 272.231 MB -> 49.737 MB.
[2024-08-23T22:53:18.372Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:53:23.189Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:53:29.553Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:53:33.891Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:53:37.057Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:53:41.180Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:53:44.616Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:53:46.824Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:53:46.824Z] 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.
[2024-08-23T22:53:47.587Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:53:47.587Z] Movies recommended for you:
[2024-08-23T22:53:47.587Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:53:47.587Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:53:47.587Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (34691.409 ms) ======
[2024-08-23T22:53:47.587Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-23T22:53:47.587Z] GC before operation: completed in 296.843 ms, heap usage 241.904 MB -> 49.422 MB.
[2024-08-23T22:53:54.027Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:54:03.762Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:54:13.466Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:54:16.557Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:54:19.729Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:54:25.189Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:54:28.257Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:54:30.459Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:54:30.459Z] 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.
[2024-08-23T22:54:30.459Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:54:31.092Z] Movies recommended for you:
[2024-08-23T22:54:31.092Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:54:31.092Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:54:31.092Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43333.706 ms) ======
[2024-08-23T22:54:31.092Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-23T22:54:31.092Z] GC before operation: completed in 182.568 ms, heap usage 92.107 MB -> 52.116 MB.
[2024-08-23T22:54:37.343Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:54:45.034Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:54:55.169Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:55:02.328Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:55:06.386Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:55:09.931Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:55:15.493Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:55:23.134Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:55:24.796Z] 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.
[2024-08-23T22:55:24.796Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:55:25.516Z] Movies recommended for you:
[2024-08-23T22:55:25.516Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:55:25.516Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:55:25.516Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54347.579 ms) ======
[2024-08-23T22:55:25.516Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-23T22:55:26.477Z] GC before operation: completed in 745.527 ms, heap usage 281.675 MB -> 49.731 MB.
[2024-08-23T22:55:34.941Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:55:41.486Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:55:47.623Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:55:55.613Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:55:56.973Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:55:59.883Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:56:05.477Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:56:09.924Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:56:11.307Z] 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.
[2024-08-23T22:56:11.307Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:56:11.307Z] Movies recommended for you:
[2024-08-23T22:56:11.307Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:56:11.307Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:56:11.307Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (45297.439 ms) ======
[2024-08-23T22:56:11.307Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-23T22:56:12.074Z] GC before operation: completed in 668.901 ms, heap usage 126.853 MB -> 51.297 MB.
[2024-08-23T22:56:18.505Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:56:22.495Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:56:32.938Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:56:42.320Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:56:47.198Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:56:49.306Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:56:51.455Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:56:53.615Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:56:54.252Z] 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.
[2024-08-23T22:56:54.252Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:56:54.252Z] Movies recommended for you:
[2024-08-23T22:56:54.252Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:56:54.252Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:56:54.252Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (42241.232 ms) ======
[2024-08-23T22:56:54.252Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-23T22:56:54.902Z] GC before operation: completed in 162.839 ms, heap usage 110.574 MB -> 49.458 MB.
[2024-08-23T22:56:59.939Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:57:06.299Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:57:12.800Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:57:17.954Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:57:21.903Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:57:24.874Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:57:27.915Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:57:30.207Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:57:30.207Z] 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.
[2024-08-23T22:57:30.207Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:57:31.156Z] Movies recommended for you:
[2024-08-23T22:57:31.156Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:57:31.156Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:57:31.156Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (36025.247 ms) ======
[2024-08-23T22:57:31.156Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-23T22:57:31.156Z] GC before operation: completed in 292.611 ms, heap usage 234.147 MB -> 48.678 MB.
[2024-08-23T22:57:37.234Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:57:42.107Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:57:46.983Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:57:53.214Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:57:56.306Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:58:00.436Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:58:02.656Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:58:05.674Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:58:06.304Z] 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.
[2024-08-23T22:58:06.304Z] The best model improves the baseline by 14.34%.
[2024-08-23T22:58:06.304Z] Movies recommended for you:
[2024-08-23T22:58:06.304Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:58:06.304Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:58:06.915Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (35707.864 ms) ======
[2024-08-23T22:58:07.597Z] -----------------------------------
[2024-08-23T22:58:07.597Z] renaissance-movie-lens_0_PASSED
[2024-08-23T22:58:07.597Z] -----------------------------------
[2024-08-23T22:58:07.597Z]
[2024-08-23T22:58:07.597Z] TEST TEARDOWN:
[2024-08-23T22:58:07.597Z] Nothing to be done for teardown.
[2024-08-23T22:58:07.597Z] renaissance-movie-lens_0 Finish Time: Fri Aug 23 18:58:07 2024 Epoch Time (ms): 1724453887057