renaissance-movie-lens_0
[2024-11-15T21:23:27.384Z] Running test renaissance-movie-lens_0 ...
[2024-11-15T21:23:27.384Z] ===============================================
[2024-11-15T21:23:27.384Z] renaissance-movie-lens_0 Start Time: Fri Nov 15 21:23:26 2024 Epoch Time (ms): 1731705806641
[2024-11-15T21:23:27.384Z] variation: NoOptions
[2024-11-15T21:23:27.384Z] JVM_OPTIONS:
[2024-11-15T21:23:27.384Z] { \
[2024-11-15T21:23:27.384Z] echo ""; echo "TEST SETUP:"; \
[2024-11-15T21:23:27.384Z] echo "Nothing to be done for setup."; \
[2024-11-15T21:23:27.384Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17317049706210/renaissance-movie-lens_0"; \
[2024-11-15T21:23:27.384Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17317049706210/renaissance-movie-lens_0"; \
[2024-11-15T21:23:27.384Z] echo ""; echo "TESTING:"; \
[2024-11-15T21:23:27.384Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17317049706210/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-15T21:23:27.384Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17317049706210/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-15T21:23:27.384Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-15T21:23:27.384Z] echo "Nothing to be done for teardown."; \
[2024-11-15T21:23:27.384Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17317049706210/TestTargetResult";
[2024-11-15T21:23:27.384Z]
[2024-11-15T21:23:27.384Z] TEST SETUP:
[2024-11-15T21:23:27.384Z] Nothing to be done for setup.
[2024-11-15T21:23:27.384Z]
[2024-11-15T21:23:27.384Z] TESTING:
[2024-11-15T21:23:30.348Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-15T21:23:31.280Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-15T21:23:34.243Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-15T21:23:34.243Z] Training: 60056, validation: 20285, test: 19854
[2024-11-15T21:23:34.243Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-15T21:23:34.243Z] GC before operation: completed in 49.128 ms, heap usage 65.994 MB -> 37.296 MB.
[2024-11-15T21:23:39.520Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:23:42.481Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:23:45.439Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:23:47.359Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:23:49.278Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:23:50.213Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:23:52.134Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:23:53.070Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:23:53.070Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:23:53.070Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:23:54.004Z] Movies recommended for you:
[2024-11-15T21:23:54.004Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:23:54.004Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:23:54.004Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (18934.354 ms) ======
[2024-11-15T21:23:54.004Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-15T21:23:54.004Z] GC before operation: completed in 64.351 ms, heap usage 168.037 MB -> 49.511 MB.
[2024-11-15T21:23:55.921Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:23:57.862Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:24:00.840Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:24:02.763Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:24:03.704Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:24:05.621Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:24:06.556Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:24:08.473Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:24:08.473Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:24:08.473Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:24:08.473Z] Movies recommended for you:
[2024-11-15T21:24:08.473Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:24:08.473Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:24:08.473Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (14865.490 ms) ======
[2024-11-15T21:24:08.473Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-15T21:24:08.473Z] GC before operation: completed in 59.118 ms, heap usage 274.862 MB -> 49.908 MB.
[2024-11-15T21:24:10.391Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:24:13.526Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:24:15.444Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:24:17.381Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:24:18.314Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:24:19.247Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:24:21.169Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:24:22.105Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:24:22.105Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:24:22.105Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:24:22.105Z] Movies recommended for you:
[2024-11-15T21:24:22.105Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:24:22.105Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:24:22.105Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13955.387 ms) ======
[2024-11-15T21:24:22.105Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-15T21:24:23.042Z] GC before operation: completed in 61.831 ms, heap usage 290.905 MB -> 50.231 MB.
[2024-11-15T21:24:24.963Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:24:26.884Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:24:28.802Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:24:30.772Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:24:31.705Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:24:32.640Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:24:34.737Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:24:35.671Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:24:35.671Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:24:35.671Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:24:35.672Z] Movies recommended for you:
[2024-11-15T21:24:35.672Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:24:35.672Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:24:35.672Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13397.215 ms) ======
[2024-11-15T21:24:35.672Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-15T21:24:35.672Z] GC before operation: completed in 70.792 ms, heap usage 278.262 MB -> 50.579 MB.
[2024-11-15T21:24:38.637Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:24:40.556Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:24:42.481Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:24:44.401Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:24:45.338Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:24:47.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:24:48.190Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:24:49.144Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:24:50.081Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:24:50.081Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:24:50.081Z] Movies recommended for you:
[2024-11-15T21:24:50.081Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:24:50.081Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:24:50.081Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13795.683 ms) ======
[2024-11-15T21:24:50.081Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-15T21:24:50.081Z] GC before operation: completed in 66.593 ms, heap usage 244.855 MB -> 50.729 MB.
[2024-11-15T21:24:52.002Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:24:53.923Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:24:55.844Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:24:57.766Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:24:58.700Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:25:00.620Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:25:01.555Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:25:02.488Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:25:02.488Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:25:02.488Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:25:02.488Z] Movies recommended for you:
[2024-11-15T21:25:02.488Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:25:02.488Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:25:02.488Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12972.182 ms) ======
[2024-11-15T21:25:02.488Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-15T21:25:03.422Z] GC before operation: completed in 73.834 ms, heap usage 152.388 MB -> 50.645 MB.
[2024-11-15T21:25:04.358Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:25:07.332Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:25:09.250Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:25:10.184Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:25:13.193Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:25:13.193Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:25:14.127Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:25:15.061Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:25:15.061Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:25:15.061Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:25:16.000Z] Movies recommended for you:
[2024-11-15T21:25:16.000Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:25:16.000Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:25:16.000Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12596.711 ms) ======
[2024-11-15T21:25:16.000Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-15T21:25:16.000Z] GC before operation: completed in 78.022 ms, heap usage 426.250 MB -> 54.286 MB.
[2024-11-15T21:25:17.919Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:25:18.855Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:25:20.788Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:25:22.708Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:25:24.628Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:25:25.567Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:25:26.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:25:27.436Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:25:28.369Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:25:28.369Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:25:28.369Z] Movies recommended for you:
[2024-11-15T21:25:28.369Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:25:28.369Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:25:28.369Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12407.361 ms) ======
[2024-11-15T21:25:28.369Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-15T21:25:28.369Z] GC before operation: completed in 78.552 ms, heap usage 137.885 MB -> 51.066 MB.
[2024-11-15T21:25:30.287Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:25:32.206Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:25:34.131Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:25:36.056Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:25:36.993Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:25:37.928Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:25:38.864Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:25:40.787Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:25:40.787Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:25:40.787Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:25:40.787Z] Movies recommended for you:
[2024-11-15T21:25:40.787Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:25:40.787Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:25:40.787Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12608.324 ms) ======
[2024-11-15T21:25:40.787Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-15T21:25:40.787Z] GC before operation: completed in 80.884 ms, heap usage 415.261 MB -> 54.342 MB.
[2024-11-15T21:25:42.725Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:25:44.656Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:25:46.602Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:25:48.522Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:25:49.455Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:25:50.388Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:25:52.305Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:25:53.239Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:25:53.239Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:25:53.239Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:25:53.239Z] Movies recommended for you:
[2024-11-15T21:25:53.239Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:25:53.239Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:25:53.239Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12617.154 ms) ======
[2024-11-15T21:25:53.239Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-15T21:25:53.239Z] GC before operation: completed in 78.569 ms, heap usage 316.694 MB -> 51.167 MB.
[2024-11-15T21:25:55.160Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:25:57.083Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:25:59.003Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:26:00.924Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:26:02.848Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:26:03.783Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:26:04.717Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:26:05.674Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:26:06.610Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:26:06.610Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:26:06.610Z] Movies recommended for you:
[2024-11-15T21:26:06.610Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:26:06.610Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:26:06.610Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12834.909 ms) ======
[2024-11-15T21:26:06.610Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-15T21:26:06.610Z] GC before operation: completed in 77.503 ms, heap usage 414.374 MB -> 54.224 MB.
[2024-11-15T21:26:08.540Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:26:10.480Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:26:12.536Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:26:14.458Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:26:15.394Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:26:16.329Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:26:18.250Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:26:19.188Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:26:19.188Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:26:19.188Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:26:19.188Z] Movies recommended for you:
[2024-11-15T21:26:19.188Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:26:19.188Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:26:19.188Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12953.806 ms) ======
[2024-11-15T21:26:19.188Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-15T21:26:19.188Z] GC before operation: completed in 65.952 ms, heap usage 132.892 MB -> 50.951 MB.
[2024-11-15T21:26:21.109Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:26:23.032Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:26:24.980Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:26:26.905Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:26:28.828Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:26:29.766Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:26:30.719Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:26:32.644Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:26:32.644Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:26:32.644Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:26:32.644Z] Movies recommended for you:
[2024-11-15T21:26:32.644Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:26:32.644Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:26:32.644Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13175.182 ms) ======
[2024-11-15T21:26:32.644Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-15T21:26:32.644Z] GC before operation: completed in 70.071 ms, heap usage 77.085 MB -> 51.036 MB.
[2024-11-15T21:26:34.568Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:26:36.490Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:26:38.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:26:40.354Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:26:41.291Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:26:43.218Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:26:44.157Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:26:45.093Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:26:46.031Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:26:46.031Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:26:46.031Z] Movies recommended for you:
[2024-11-15T21:26:46.031Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:26:46.031Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:26:46.031Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13083.515 ms) ======
[2024-11-15T21:26:46.031Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-15T21:26:46.031Z] GC before operation: completed in 70.037 ms, heap usage 413.681 MB -> 54.295 MB.
[2024-11-15T21:26:47.957Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:26:49.890Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:26:51.818Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:26:53.761Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:26:55.688Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:26:56.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:26:58.547Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:26:59.484Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:26:59.484Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:26:59.484Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:26:59.484Z] Movies recommended for you:
[2024-11-15T21:26:59.484Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:26:59.484Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:26:59.484Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14072.034 ms) ======
[2024-11-15T21:26:59.484Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-15T21:27:00.432Z] GC before operation: completed in 69.716 ms, heap usage 178.923 MB -> 50.986 MB.
[2024-11-15T21:27:02.366Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:27:05.349Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:27:07.276Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:27:09.200Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:27:10.140Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:27:12.273Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:27:13.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:27:14.144Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:27:14.144Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:27:14.144Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:27:14.144Z] Movies recommended for you:
[2024-11-15T21:27:14.144Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:27:14.144Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:27:14.144Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14192.903 ms) ======
[2024-11-15T21:27:14.144Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-15T21:27:14.144Z] GC before operation: completed in 74.498 ms, heap usage 608.547 MB -> 60.082 MB.
[2024-11-15T21:27:16.068Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:27:18.001Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:27:19.921Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:27:21.846Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:27:23.769Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:27:24.704Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:27:25.641Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:27:27.562Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:27:27.562Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:27:27.562Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:27:27.562Z] Movies recommended for you:
[2024-11-15T21:27:27.562Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:27:27.562Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:27:27.562Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13134.663 ms) ======
[2024-11-15T21:27:27.562Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-15T21:27:27.562Z] GC before operation: completed in 89.705 ms, heap usage 330.975 MB -> 53.294 MB.
[2024-11-15T21:27:30.542Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:27:32.464Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:27:34.389Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:27:35.327Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:27:37.249Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:27:38.185Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:27:39.121Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:27:40.058Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:27:40.058Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:27:40.058Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:27:40.998Z] Movies recommended for you:
[2024-11-15T21:27:40.998Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:27:40.998Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:27:40.998Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13085.873 ms) ======
[2024-11-15T21:27:40.998Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-15T21:27:40.998Z] GC before operation: completed in 74.491 ms, heap usage 375.826 MB -> 51.236 MB.
[2024-11-15T21:27:42.924Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:27:44.850Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:27:46.775Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:27:48.705Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:27:49.642Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:27:51.572Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:27:52.508Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:27:53.453Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:27:53.453Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:27:53.453Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:27:53.453Z] Movies recommended for you:
[2024-11-15T21:27:53.453Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:27:53.453Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:27:53.453Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12996.672 ms) ======
[2024-11-15T21:27:53.453Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-15T21:27:53.453Z] GC before operation: completed in 84.834 ms, heap usage 609.817 MB -> 56.307 MB.
[2024-11-15T21:27:55.378Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T21:27:57.300Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T21:27:59.223Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T21:28:01.162Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T21:28:02.098Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T21:28:03.034Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T21:28:04.962Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T21:28:05.898Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T21:28:05.898Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-15T21:28:05.898Z] The best model improves the baseline by 14.52%.
[2024-11-15T21:28:05.898Z] Movies recommended for you:
[2024-11-15T21:28:05.898Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T21:28:05.898Z] There is no way to check that no silent failure occurred.
[2024-11-15T21:28:05.899Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12384.541 ms) ======
[2024-11-15T21:28:06.835Z] -----------------------------------
[2024-11-15T21:28:06.835Z] renaissance-movie-lens_0_PASSED
[2024-11-15T21:28:06.835Z] -----------------------------------
[2024-11-15T21:28:06.835Z]
[2024-11-15T21:28:06.835Z] TEST TEARDOWN:
[2024-11-15T21:28:06.835Z] Nothing to be done for teardown.
[2024-11-15T21:28:06.835Z] renaissance-movie-lens_0 Finish Time: Fri Nov 15 21:28:06 2024 Epoch Time (ms): 1731706086098