renaissance-movie-lens_0
[2024-08-16T17:36:40.575Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T17:36:40.575Z] ===============================================
[2024-08-16T17:36:40.575Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 17:36:40 2024 Epoch Time (ms): 1723829800400
[2024-08-16T17:36:40.575Z] variation: NoOptions
[2024-08-16T17:36:40.575Z] JVM_OPTIONS:
[2024-08-16T17:36:40.575Z] { \
[2024-08-16T17:36:40.575Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T17:36:40.575Z] echo "Nothing to be done for setup."; \
[2024-08-16T17:36:40.575Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238288279794/renaissance-movie-lens_0"; \
[2024-08-16T17:36:40.575Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238288279794/renaissance-movie-lens_0"; \
[2024-08-16T17:36:40.575Z] echo ""; echo "TESTING:"; \
[2024-08-16T17:36:40.575Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_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_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238288279794/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T17:36:40.575Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238288279794/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T17:36:40.575Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T17:36:40.575Z] echo "Nothing to be done for teardown."; \
[2024-08-16T17:36:40.575Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238288279794/TestTargetResult";
[2024-08-16T17:36:40.575Z]
[2024-08-16T17:36:40.575Z] TEST SETUP:
[2024-08-16T17:36:40.575Z] Nothing to be done for setup.
[2024-08-16T17:36:40.575Z]
[2024-08-16T17:36:40.575Z] TESTING:
[2024-08-16T17:36:44.640Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T17:36:46.555Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-16T17:36:49.516Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T17:36:49.516Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T17:36:49.516Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T17:36:50.449Z] GC before operation: completed in 78.907 ms, heap usage 101.200 MB -> 36.455 MB.
[2024-08-16T17:36:55.730Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:36:58.685Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:37:01.691Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:37:04.645Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:37:06.564Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:37:07.497Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:37:09.414Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:37:11.077Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:37:11.077Z] 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.
[2024-08-16T17:37:11.077Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:37:11.077Z] Movies recommended for you:
[2024-08-16T17:37:11.077Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:37:11.077Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:37:11.077Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21546.115 ms) ======
[2024-08-16T17:37:11.077Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T17:37:12.010Z] GC before operation: completed in 88.564 ms, heap usage 290.616 MB -> 48.259 MB.
[2024-08-16T17:37:13.926Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:37:16.924Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:37:18.834Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:37:21.926Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:37:22.858Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:37:24.807Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:37:25.741Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:37:27.654Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:37:27.654Z] 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.
[2024-08-16T17:37:27.654Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:37:27.654Z] Movies recommended for you:
[2024-08-16T17:37:27.654Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:37:27.654Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:37:27.654Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16167.363 ms) ======
[2024-08-16T17:37:27.654Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T17:37:27.654Z] GC before operation: completed in 91.538 ms, heap usage 184.217 MB -> 49.157 MB.
[2024-08-16T17:37:30.632Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:37:32.561Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:37:35.513Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:37:37.426Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:37:38.359Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:37:40.287Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:37:41.227Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:37:43.144Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:37:43.144Z] 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.
[2024-08-16T17:37:43.144Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:37:43.144Z] Movies recommended for you:
[2024-08-16T17:37:43.144Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:37:43.144Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:37:43.144Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15309.602 ms) ======
[2024-08-16T17:37:43.144Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T17:37:43.144Z] GC before operation: completed in 84.644 ms, heap usage 186.850 MB -> 49.391 MB.
[2024-08-16T17:37:46.097Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:37:48.022Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:37:49.937Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:37:52.890Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:37:53.822Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:37:55.734Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:37:56.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:37:57.597Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:37:58.528Z] 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.
[2024-08-16T17:37:58.528Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:37:58.528Z] Movies recommended for you:
[2024-08-16T17:37:58.528Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:37:58.528Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:37:58.528Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15077.437 ms) ======
[2024-08-16T17:37:58.528Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T17:37:58.528Z] GC before operation: completed in 83.283 ms, heap usage 349.499 MB -> 49.916 MB.
[2024-08-16T17:38:01.485Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:38:03.395Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:38:05.332Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:38:08.287Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:38:09.218Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:38:10.149Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:38:12.059Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:38:12.992Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:38:12.992Z] 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.
[2024-08-16T17:38:12.992Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:38:13.924Z] Movies recommended for you:
[2024-08-16T17:38:13.924Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:38:13.924Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:38:13.924Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15088.163 ms) ======
[2024-08-16T17:38:13.924Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T17:38:13.924Z] GC before operation: completed in 81.762 ms, heap usage 116.609 MB -> 49.823 MB.
[2024-08-16T17:38:16.016Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:38:17.473Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:38:20.439Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:38:22.358Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:38:23.289Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:38:25.204Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:38:26.137Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:38:27.069Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:38:28.002Z] 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.
[2024-08-16T17:38:28.002Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:38:28.002Z] Movies recommended for you:
[2024-08-16T17:38:28.002Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:38:28.002Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:38:28.002Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14207.079 ms) ======
[2024-08-16T17:38:28.002Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T17:38:28.002Z] GC before operation: completed in 93.956 ms, heap usage 96.111 MB -> 49.782 MB.
[2024-08-16T17:38:29.915Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:38:31.832Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:38:34.786Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:38:36.703Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:38:37.633Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:38:38.564Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:38:40.473Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:38:41.404Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:38:41.404Z] 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.
[2024-08-16T17:38:41.404Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:38:41.404Z] Movies recommended for you:
[2024-08-16T17:38:41.404Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:38:41.404Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:38:41.404Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13740.215 ms) ======
[2024-08-16T17:38:41.404Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T17:38:41.404Z] GC before operation: completed in 86.255 ms, heap usage 268.474 MB -> 50.056 MB.
[2024-08-16T17:38:44.363Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:38:46.274Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:38:48.182Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:38:50.093Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:38:51.023Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:38:52.936Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:38:53.866Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:38:54.797Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:38:55.728Z] 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.
[2024-08-16T17:38:55.728Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:38:55.728Z] Movies recommended for you:
[2024-08-16T17:38:55.728Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:38:55.728Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:38:55.728Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13695.074 ms) ======
[2024-08-16T17:38:55.728Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T17:38:55.728Z] GC before operation: completed in 83.162 ms, heap usage 103.762 MB -> 50.200 MB.
[2024-08-16T17:38:57.656Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:38:59.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:39:01.487Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:39:04.440Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:39:05.371Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:39:06.303Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:39:08.214Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:39:09.155Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:39:09.155Z] 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.
[2024-08-16T17:39:09.155Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:39:09.155Z] Movies recommended for you:
[2024-08-16T17:39:09.155Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:39:09.155Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:39:09.155Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13836.988 ms) ======
[2024-08-16T17:39:09.155Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T17:39:09.155Z] GC before operation: completed in 82.036 ms, heap usage 321.914 MB -> 50.196 MB.
[2024-08-16T17:39:11.070Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:39:14.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:39:15.665Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:39:17.575Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:39:19.488Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:39:20.547Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:39:21.482Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:39:22.412Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:39:23.346Z] 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.
[2024-08-16T17:39:23.346Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:39:23.346Z] Movies recommended for you:
[2024-08-16T17:39:23.346Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:39:23.346Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:39:23.346Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13649.267 ms) ======
[2024-08-16T17:39:23.346Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T17:39:23.346Z] GC before operation: completed in 96.576 ms, heap usage 173.182 MB -> 50.211 MB.
[2024-08-16T17:39:25.267Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:39:27.179Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:39:30.138Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:39:32.048Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:39:32.978Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:39:33.910Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:39:35.839Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:39:36.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:39:36.796Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T17:39:36.796Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:39:36.796Z] Movies recommended for you:
[2024-08-16T17:39:36.796Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:39:36.796Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:39:36.796Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14046.915 ms) ======
[2024-08-16T17:39:36.796Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T17:39:37.736Z] GC before operation: completed in 84.446 ms, heap usage 259.452 MB -> 50.039 MB.
[2024-08-16T17:39:39.661Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:39:41.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:39:43.494Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:39:45.415Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:39:47.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:39:48.266Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:39:49.198Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:39:51.109Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:39:51.109Z] 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.
[2024-08-16T17:39:51.109Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:39:51.109Z] Movies recommended for you:
[2024-08-16T17:39:51.109Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:39:51.109Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:39:51.109Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13810.488 ms) ======
[2024-08-16T17:39:51.109Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T17:39:51.109Z] GC before operation: completed in 84.831 ms, heap usage 296.762 MB -> 50.173 MB.
[2024-08-16T17:39:53.046Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:39:54.965Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:39:57.962Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:39:58.892Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:40:00.808Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:40:01.740Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:40:03.655Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:40:04.586Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:40:04.586Z] 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.
[2024-08-16T17:40:04.586Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:40:04.586Z] Movies recommended for you:
[2024-08-16T17:40:04.586Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:40:04.586Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:40:04.586Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13706.727 ms) ======
[2024-08-16T17:40:04.586Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T17:40:04.586Z] GC before operation: completed in 81.361 ms, heap usage 131.501 MB -> 50.241 MB.
[2024-08-16T17:40:07.535Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:40:09.445Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:40:11.360Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:40:13.271Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:40:14.210Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:40:16.128Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:40:17.057Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:40:18.457Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:40:18.457Z] 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.
[2024-08-16T17:40:18.457Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:40:18.457Z] Movies recommended for you:
[2024-08-16T17:40:18.457Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:40:18.457Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:40:18.457Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13752.565 ms) ======
[2024-08-16T17:40:18.457Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T17:40:18.457Z] GC before operation: completed in 79.845 ms, heap usage 218.793 MB -> 50.092 MB.
[2024-08-16T17:40:20.373Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:40:23.326Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:40:25.237Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:40:27.149Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:40:28.080Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:40:29.011Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:40:31.101Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:40:32.031Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:40:32.032Z] 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.
[2024-08-16T17:40:32.032Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:40:32.032Z] Movies recommended for you:
[2024-08-16T17:40:32.032Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:40:32.032Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:40:32.032Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13542.559 ms) ======
[2024-08-16T17:40:32.032Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T17:40:32.032Z] GC before operation: completed in 80.289 ms, heap usage 77.730 MB -> 50.059 MB.
[2024-08-16T17:40:34.992Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:40:36.915Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:40:38.827Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:40:40.738Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:40:41.675Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:40:43.591Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:40:44.524Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:40:46.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:40:46.437Z] 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.
[2024-08-16T17:40:46.437Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:40:46.437Z] Movies recommended for you:
[2024-08-16T17:40:46.437Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:40:46.437Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:40:46.437Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13948.790 ms) ======
[2024-08-16T17:40:46.438Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T17:40:46.438Z] GC before operation: completed in 85.418 ms, heap usage 240.114 MB -> 50.384 MB.
[2024-08-16T17:40:48.353Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:40:51.317Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:40:53.233Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:40:55.149Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:40:56.081Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:40:57.014Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:40:58.929Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:40:59.861Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:40:59.861Z] 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.
[2024-08-16T17:40:59.861Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:40:59.861Z] Movies recommended for you:
[2024-08-16T17:40:59.861Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:40:59.861Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:40:59.861Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13676.140 ms) ======
[2024-08-16T17:40:59.861Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T17:40:59.861Z] GC before operation: completed in 96.146 ms, heap usage 113.993 MB -> 50.031 MB.
[2024-08-16T17:41:02.832Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:41:04.770Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:41:06.684Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:41:08.601Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:41:09.542Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:41:11.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:41:12.399Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:41:13.329Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:41:14.259Z] 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.
[2024-08-16T17:41:14.259Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:41:14.259Z] Movies recommended for you:
[2024-08-16T17:41:14.259Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:41:14.259Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:41:14.259Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13699.070 ms) ======
[2024-08-16T17:41:14.259Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T17:41:14.259Z] GC before operation: completed in 81.353 ms, heap usage 81.768 MB -> 50.060 MB.
[2024-08-16T17:41:16.170Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:41:18.781Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:41:19.716Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:41:21.629Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:41:23.542Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:41:24.473Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:41:26.391Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:41:27.323Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:41:27.323Z] 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.
[2024-08-16T17:41:27.323Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:41:28.259Z] Movies recommended for you:
[2024-08-16T17:41:28.259Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:41:28.259Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:41:28.259Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13767.035 ms) ======
[2024-08-16T17:41:28.259Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T17:41:28.259Z] GC before operation: completed in 80.015 ms, heap usage 107.120 MB -> 50.330 MB.
[2024-08-16T17:41:30.174Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:41:32.091Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:41:34.018Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:41:35.956Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:41:36.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:41:37.820Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:41:39.746Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:41:40.677Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:41:40.677Z] 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.
[2024-08-16T17:41:40.677Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:41:40.678Z] Movies recommended for you:
[2024-08-16T17:41:40.678Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:41:40.678Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:41:40.678Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12985.620 ms) ======
[2024-08-16T17:41:41.609Z] -----------------------------------
[2024-08-16T17:41:41.609Z] renaissance-movie-lens_0_PASSED
[2024-08-16T17:41:41.609Z] -----------------------------------
[2024-08-16T17:41:41.609Z]
[2024-08-16T17:41:41.609Z] TEST TEARDOWN:
[2024-08-16T17:41:41.609Z] Nothing to be done for teardown.
[2024-08-16T17:41:41.609Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 17:41:40 2024 Epoch Time (ms): 1723830100810