renaissance-movie-lens_0
[2024-08-10T08:04:00.060Z] Running test renaissance-movie-lens_0 ...
[2024-08-10T08:04:00.060Z] ===============================================
[2024-08-10T08:04:00.060Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 08:03:59 2024 Epoch Time (ms): 1723277039542
[2024-08-10T08:04:00.060Z] variation: NoOptions
[2024-08-10T08:04:00.060Z] JVM_OPTIONS:
[2024-08-10T08:04:00.060Z] { \
[2024-08-10T08:04:00.060Z] echo ""; echo "TEST SETUP:"; \
[2024-08-10T08:04:00.060Z] echo "Nothing to be done for setup."; \
[2024-08-10T08:04:00.060Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232755595588/renaissance-movie-lens_0"; \
[2024-08-10T08:04:00.060Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232755595588/renaissance-movie-lens_0"; \
[2024-08-10T08:04:00.060Z] echo ""; echo "TESTING:"; \
[2024-08-10T08:04:00.060Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232755595588/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-10T08:04:00.060Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232755595588/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-10T08:04:00.060Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-10T08:04:00.060Z] echo "Nothing to be done for teardown."; \
[2024-08-10T08:04:00.060Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232755595588/TestTargetResult";
[2024-08-10T08:04:00.060Z]
[2024-08-10T08:04:00.060Z] TEST SETUP:
[2024-08-10T08:04:00.060Z] Nothing to be done for setup.
[2024-08-10T08:04:00.060Z]
[2024-08-10T08:04:00.060Z] TESTING:
[2024-08-10T08:04:03.898Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-10T08:04:07.003Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-10T08:04:14.515Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-10T08:04:14.515Z] Training: 60056, validation: 20285, test: 19854
[2024-08-10T08:04:14.515Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-10T08:04:14.515Z] GC before operation: completed in 180.680 ms, heap usage 68.840 MB -> 36.202 MB.
[2024-08-10T08:04:26.875Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:04:32.895Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:04:40.207Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:04:46.783Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:04:49.713Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:04:53.417Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:04:57.334Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:05:02.502Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:05:02.502Z] 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.
[2024-08-10T08:05:03.188Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:05:03.188Z] Movies recommended for you:
[2024-08-10T08:05:03.188Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:05:03.188Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:05:03.188Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (48608.280 ms) ======
[2024-08-10T08:05:03.188Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-10T08:05:03.845Z] GC before operation: completed in 259.925 ms, heap usage 140.686 MB -> 51.044 MB.
[2024-08-10T08:05:10.015Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:05:17.618Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:05:25.067Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:05:30.934Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:05:35.794Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:05:40.003Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:05:45.033Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:05:49.218Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:05:49.218Z] 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.
[2024-08-10T08:05:49.218Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:05:49.218Z] Movies recommended for you:
[2024-08-10T08:05:49.218Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:05:49.218Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:05:49.218Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45891.539 ms) ======
[2024-08-10T08:05:49.219Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-10T08:05:49.827Z] GC before operation: completed in 152.498 ms, heap usage 205.731 MB -> 48.250 MB.
[2024-08-10T08:05:54.665Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:05:59.506Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:06:07.185Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:06:13.160Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:06:16.590Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:06:19.632Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:06:23.624Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:06:26.466Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:06:27.107Z] 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.
[2024-08-10T08:06:27.107Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:06:27.108Z] Movies recommended for you:
[2024-08-10T08:06:27.108Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:06:27.108Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:06:27.108Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (37536.678 ms) ======
[2024-08-10T08:06:27.108Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-10T08:06:27.108Z] GC before operation: completed in 220.216 ms, heap usage 178.831 MB -> 48.485 MB.
[2024-08-10T08:06:33.052Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:06:38.852Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:06:44.906Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:06:49.608Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:06:52.541Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:06:55.514Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:06:58.527Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:07:01.474Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:07:02.116Z] 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.
[2024-08-10T08:07:02.116Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:07:02.116Z] Movies recommended for you:
[2024-08-10T08:07:02.116Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:07:02.116Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:07:02.116Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (34744.390 ms) ======
[2024-08-10T08:07:02.116Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-10T08:07:02.116Z] GC before operation: completed in 142.411 ms, heap usage 164.299 MB -> 48.832 MB.
[2024-08-10T08:07:09.425Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:07:14.215Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:07:19.045Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:07:23.759Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:07:26.641Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:07:29.568Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:07:33.434Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:07:37.374Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:07:38.135Z] 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.
[2024-08-10T08:07:38.135Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:07:38.775Z] Movies recommended for you:
[2024-08-10T08:07:38.775Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:07:38.775Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:07:38.775Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (36296.319 ms) ======
[2024-08-10T08:07:38.775Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-10T08:07:38.775Z] GC before operation: completed in 356.094 ms, heap usage 118.986 MB -> 48.928 MB.
[2024-08-10T08:07:45.131Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:07:51.242Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:07:57.378Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:08:01.155Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:08:04.079Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:08:06.944Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:08:09.773Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:08:11.816Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:08:12.455Z] 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.
[2024-08-10T08:08:12.455Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:08:13.064Z] Movies recommended for you:
[2024-08-10T08:08:13.064Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:08:13.064Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:08:13.064Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (33960.864 ms) ======
[2024-08-10T08:08:13.064Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-10T08:08:13.064Z] GC before operation: completed in 246.142 ms, heap usage 136.717 MB -> 48.924 MB.
[2024-08-10T08:08:18.144Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:08:25.005Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:08:29.869Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:08:34.889Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:08:38.658Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:08:41.588Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:08:44.552Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:08:48.349Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:08:48.349Z] 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.
[2024-08-10T08:08:48.349Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:08:48.349Z] Movies recommended for you:
[2024-08-10T08:08:48.349Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:08:48.349Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:08:48.349Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (35279.139 ms) ======
[2024-08-10T08:08:48.349Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-10T08:08:48.349Z] GC before operation: completed in 168.215 ms, heap usage 235.980 MB -> 49.181 MB.
[2024-08-10T08:08:54.337Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:08:59.168Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:09:04.455Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:09:09.319Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:09:12.164Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:09:15.110Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:09:18.036Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:09:21.196Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:09:21.196Z] 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.
[2024-08-10T08:09:21.196Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:09:21.833Z] Movies recommended for you:
[2024-08-10T08:09:21.833Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:09:21.833Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:09:21.833Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (33112.777 ms) ======
[2024-08-10T08:09:21.833Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-10T08:09:21.833Z] GC before operation: completed in 206.139 ms, heap usage 168.690 MB -> 49.471 MB.
[2024-08-10T08:09:26.744Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:09:32.642Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:09:38.701Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:09:42.553Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:09:45.989Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:09:48.924Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:09:51.925Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:09:54.786Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:09:54.786Z] 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.
[2024-08-10T08:09:55.430Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:09:55.430Z] Movies recommended for you:
[2024-08-10T08:09:55.430Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:09:55.430Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:09:55.430Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (33505.158 ms) ======
[2024-08-10T08:09:55.430Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-10T08:09:55.430Z] GC before operation: completed in 182.661 ms, heap usage 113.447 MB -> 49.165 MB.
[2024-08-10T08:10:00.256Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:10:05.046Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:10:09.894Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:10:13.709Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:10:15.776Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:10:18.706Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:10:22.608Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:10:24.780Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:10:25.428Z] 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.
[2024-08-10T08:10:26.046Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:10:26.046Z] Movies recommended for you:
[2024-08-10T08:10:26.046Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:10:26.046Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:10:26.046Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (30713.712 ms) ======
[2024-08-10T08:10:26.046Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-10T08:10:26.720Z] GC before operation: completed in 298.079 ms, heap usage 72.664 MB -> 49.194 MB.
[2024-08-10T08:10:32.808Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:10:37.727Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:10:41.491Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:10:46.370Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:10:49.265Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:10:52.155Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:10:55.187Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:10:58.097Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:10:58.722Z] 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.
[2024-08-10T08:10:58.722Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:10:58.722Z] Movies recommended for you:
[2024-08-10T08:10:58.722Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:10:58.722Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:10:58.722Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (32284.907 ms) ======
[2024-08-10T08:10:58.723Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-10T08:10:58.723Z] GC before operation: completed in 187.852 ms, heap usage 230.385 MB -> 49.133 MB.
[2024-08-10T08:11:04.245Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:11:09.158Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:11:15.170Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:11:21.269Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:11:25.132Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:11:27.998Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:11:31.043Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:11:35.136Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:11:35.756Z] 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.
[2024-08-10T08:11:35.756Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:11:35.756Z] Movies recommended for you:
[2024-08-10T08:11:35.756Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:11:35.756Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:11:35.756Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (36810.953 ms) ======
[2024-08-10T08:11:35.756Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-10T08:11:35.757Z] GC before operation: completed in 220.700 ms, heap usage 327.062 MB -> 52.590 MB.
[2024-08-10T08:11:41.855Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:11:48.181Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:11:54.171Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:11:58.955Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:12:01.800Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:12:05.615Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:12:08.741Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:12:11.821Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:12:12.468Z] 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.
[2024-08-10T08:12:12.468Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:12:12.468Z] Movies recommended for you:
[2024-08-10T08:12:12.468Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:12:12.468Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:12:12.468Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36480.215 ms) ======
[2024-08-10T08:12:12.468Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-10T08:12:12.468Z] GC before operation: completed in 188.374 ms, heap usage 96.613 MB -> 49.327 MB.
[2024-08-10T08:12:18.450Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:12:24.593Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:12:29.437Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:12:33.304Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:12:37.234Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:12:40.066Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:12:45.198Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:12:48.043Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:12:48.687Z] 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.
[2024-08-10T08:12:48.687Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:12:48.687Z] Movies recommended for you:
[2024-08-10T08:12:48.687Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:12:48.687Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:12:48.687Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (36197.644 ms) ======
[2024-08-10T08:12:48.687Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-10T08:12:49.368Z] GC before operation: completed in 198.004 ms, heap usage 102.415 MB -> 49.086 MB.
[2024-08-10T08:12:54.249Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:13:00.369Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:13:06.465Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:13:11.746Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:13:14.808Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:13:17.755Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:13:21.494Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:13:23.644Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:13:24.245Z] 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.
[2024-08-10T08:13:24.245Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:13:24.245Z] Movies recommended for you:
[2024-08-10T08:13:24.245Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:13:24.245Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:13:24.245Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (35293.442 ms) ======
[2024-08-10T08:13:24.245Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-10T08:13:24.879Z] GC before operation: completed in 168.924 ms, heap usage 161.418 MB -> 49.356 MB.
[2024-08-10T08:13:29.745Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:13:34.608Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:13:40.814Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:13:45.698Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:13:49.059Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:13:52.985Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:13:57.086Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:13:59.955Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:14:00.608Z] 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.
[2024-08-10T08:14:00.608Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:14:00.608Z] Movies recommended for you:
[2024-08-10T08:14:00.608Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:14:00.608Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:14:00.608Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (36210.143 ms) ======
[2024-08-10T08:14:00.608Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-10T08:14:01.253Z] GC before operation: completed in 237.430 ms, heap usage 244.642 MB -> 49.498 MB.
[2024-08-10T08:14:07.335Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:14:13.337Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:14:18.176Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:14:23.212Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:14:26.128Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:14:29.956Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:14:33.266Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:14:38.415Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:14:38.415Z] 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.
[2024-08-10T08:14:38.415Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:14:39.036Z] Movies recommended for you:
[2024-08-10T08:14:39.036Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:14:39.036Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:14:39.036Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (37782.956 ms) ======
[2024-08-10T08:14:39.036Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-10T08:14:39.036Z] GC before operation: completed in 203.030 ms, heap usage 149.566 MB -> 49.221 MB.
[2024-08-10T08:14:45.135Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:14:51.133Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:14:55.970Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:15:01.952Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:15:04.817Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:15:08.855Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:15:12.055Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:15:14.221Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:15:14.870Z] 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.
[2024-08-10T08:15:14.870Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:15:14.870Z] Movies recommended for you:
[2024-08-10T08:15:14.870Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:15:14.870Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:15:14.870Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (36071.203 ms) ======
[2024-08-10T08:15:14.870Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-10T08:15:15.504Z] GC before operation: completed in 240.056 ms, heap usage 313.987 MB -> 49.518 MB.
[2024-08-10T08:15:20.334Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:15:26.366Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:15:30.150Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:15:34.937Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:15:36.965Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:15:39.889Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:15:42.994Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:15:44.259Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:15:44.944Z] 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.
[2024-08-10T08:15:44.944Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:15:44.944Z] Movies recommended for you:
[2024-08-10T08:15:44.944Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:15:44.944Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:15:44.944Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (29823.057 ms) ======
[2024-08-10T08:15:44.944Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-10T08:15:45.565Z] GC before operation: completed in 155.895 ms, heap usage 230.008 MB -> 49.597 MB.
[2024-08-10T08:15:50.277Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:15:54.047Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:15:58.982Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:16:02.819Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:16:05.637Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:16:08.597Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:16:11.420Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:16:14.237Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:16:14.237Z] 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.
[2024-08-10T08:16:14.867Z] The best model improves the baseline by 14.34%.
[2024-08-10T08:16:14.867Z] Movies recommended for you:
[2024-08-10T08:16:14.867Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:16:14.867Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:16:14.867Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (29587.855 ms) ======
[2024-08-10T08:16:15.468Z] -----------------------------------
[2024-08-10T08:16:15.468Z] renaissance-movie-lens_0_PASSED
[2024-08-10T08:16:15.468Z] -----------------------------------
[2024-08-10T08:16:15.468Z]
[2024-08-10T08:16:15.468Z] TEST TEARDOWN:
[2024-08-10T08:16:15.468Z] Nothing to be done for teardown.
[2024-08-10T08:16:15.468Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 08:16:15 2024 Epoch Time (ms): 1723277775204