renaissance-movie-lens_0
[2024-08-28T21:28:57.000Z] Running test renaissance-movie-lens_0 ...
[2024-08-28T21:28:57.000Z] ===============================================
[2024-08-28T21:28:57.000Z] renaissance-movie-lens_0 Start Time: Wed Aug 28 21:28:56 2024 Epoch Time (ms): 1724880536330
[2024-08-28T21:28:57.000Z] variation: NoOptions
[2024-08-28T21:28:57.000Z] JVM_OPTIONS:
[2024-08-28T21:28:57.000Z] { \
[2024-08-28T21:28:57.000Z] echo ""; echo "TEST SETUP:"; \
[2024-08-28T21:28:57.000Z] echo "Nothing to be done for setup."; \
[2024-08-28T21:28:57.000Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17248796737808/renaissance-movie-lens_0"; \
[2024-08-28T21:28:57.000Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17248796737808/renaissance-movie-lens_0"; \
[2024-08-28T21:28:57.000Z] echo ""; echo "TESTING:"; \
[2024-08-28T21:28:57.000Z] "/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_17248796737808/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-28T21:28:57.000Z] 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_17248796737808/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-28T21:28:57.000Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-28T21:28:57.000Z] echo "Nothing to be done for teardown."; \
[2024-08-28T21:28:57.000Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17248796737808/TestTargetResult";
[2024-08-28T21:28:57.000Z]
[2024-08-28T21:28:57.000Z] TEST SETUP:
[2024-08-28T21:28:57.000Z] Nothing to be done for setup.
[2024-08-28T21:28:57.000Z]
[2024-08-28T21:28:57.000Z] TESTING:
[2024-08-28T21:28:59.926Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-28T21:29:01.864Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-28T21:29:03.819Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-28T21:29:04.747Z] Training: 60056, validation: 20285, test: 19854
[2024-08-28T21:29:04.747Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-28T21:29:04.747Z] GC before operation: completed in 58.252 ms, heap usage 92.948 MB -> 37.179 MB.
[2024-08-28T21:29:09.993Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:29:12.915Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:29:15.843Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:29:17.732Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:29:19.622Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:29:20.541Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:29:22.430Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:29:24.320Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:29:24.321Z] 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.
[2024-08-28T21:29:24.321Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:29:24.321Z] Movies recommended for you:
[2024-08-28T21:29:24.321Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:29:24.321Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:29:24.321Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (19961.221 ms) ======
[2024-08-28T21:29:24.321Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-28T21:29:24.321Z] GC before operation: completed in 74.828 ms, heap usage 220.736 MB -> 52.591 MB.
[2024-08-28T21:29:27.239Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:29:29.128Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:29:32.386Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:29:34.278Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:29:36.176Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:29:37.262Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:29:39.149Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:29:40.837Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:29:40.837Z] 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.
[2024-08-28T21:29:40.837Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:29:40.837Z] Movies recommended for you:
[2024-08-28T21:29:40.837Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:29:40.837Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:29:40.837Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15908.513 ms) ======
[2024-08-28T21:29:40.837Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-28T21:29:40.837Z] GC before operation: completed in 70.333 ms, heap usage 369.679 MB -> 49.956 MB.
[2024-08-28T21:29:42.752Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:29:44.657Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:29:47.589Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:29:49.475Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:29:50.394Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:29:52.284Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:29:53.204Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:29:54.124Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:29:55.047Z] 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.
[2024-08-28T21:29:55.047Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:29:55.047Z] Movies recommended for you:
[2024-08-28T21:29:55.047Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:29:55.047Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:29:55.047Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14396.680 ms) ======
[2024-08-28T21:29:55.047Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-28T21:29:55.047Z] GC before operation: completed in 62.027 ms, heap usage 195.845 MB -> 50.028 MB.
[2024-08-28T21:29:56.941Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:29:58.834Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:00.722Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:03.641Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:04.561Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:05.479Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:30:07.369Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:30:08.291Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:30:08.291Z] 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.
[2024-08-28T21:30:08.291Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:30:08.291Z] Movies recommended for you:
[2024-08-28T21:30:08.291Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:30:08.291Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:30:08.291Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13461.810 ms) ======
[2024-08-28T21:30:08.291Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-28T21:30:08.291Z] GC before operation: completed in 55.058 ms, heap usage 117.100 MB -> 50.415 MB.
[2024-08-28T21:30:10.184Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:30:12.074Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:14.996Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:16.888Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:17.809Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:18.728Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:30:20.618Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:30:21.538Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:30:21.538Z] 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.
[2024-08-28T21:30:21.538Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:30:21.538Z] Movies recommended for you:
[2024-08-28T21:30:21.538Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:30:21.538Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:30:21.538Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13320.964 ms) ======
[2024-08-28T21:30:21.538Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-28T21:30:21.538Z] GC before operation: completed in 57.838 ms, heap usage 127.145 MB -> 50.472 MB.
[2024-08-28T21:30:23.426Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:30:25.319Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:27.211Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:29.110Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:31.023Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:31.942Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:30:32.863Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:30:33.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:30:33.783Z] 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.
[2024-08-28T21:30:34.703Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:30:34.703Z] Movies recommended for you:
[2024-08-28T21:30:34.703Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:30:34.703Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:30:34.703Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12433.168 ms) ======
[2024-08-28T21:30:34.703Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-28T21:30:34.703Z] GC before operation: completed in 60.431 ms, heap usage 74.709 MB -> 51.450 MB.
[2024-08-28T21:30:36.606Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:30:38.499Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:40.788Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:41.724Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:43.615Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:44.538Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:30:45.459Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:30:46.379Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:30:46.379Z] 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.
[2024-08-28T21:30:46.379Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:30:47.299Z] Movies recommended for you:
[2024-08-28T21:30:47.299Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:30:47.299Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:30:47.299Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12498.461 ms) ======
[2024-08-28T21:30:47.299Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-28T21:30:47.299Z] GC before operation: completed in 66.864 ms, heap usage 115.678 MB -> 50.698 MB.
[2024-08-28T21:30:49.188Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:30:50.107Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:53.030Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:53.953Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:55.853Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:56.773Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:30:57.694Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:30:58.623Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:30:58.623Z] 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.
[2024-08-28T21:30:58.623Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:30:59.542Z] Movies recommended for you:
[2024-08-28T21:30:59.542Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:30:59.542Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:30:59.542Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12128.494 ms) ======
[2024-08-28T21:30:59.542Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-28T21:30:59.542Z] GC before operation: completed in 77.349 ms, heap usage 83.046 MB -> 54.567 MB.
[2024-08-28T21:31:01.430Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:02.349Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:04.239Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:06.131Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:31:07.050Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:31:08.939Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:09.859Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:31:10.779Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:31:10.779Z] 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.
[2024-08-28T21:31:10.779Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:31:10.779Z] Movies recommended for you:
[2024-08-28T21:31:10.779Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:31:10.779Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:31:10.779Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12040.379 ms) ======
[2024-08-28T21:31:10.779Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-28T21:31:11.700Z] GC before operation: completed in 62.098 ms, heap usage 346.735 MB -> 50.968 MB.
[2024-08-28T21:31:12.621Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:14.513Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:16.403Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:18.290Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:31:19.209Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:31:21.098Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:22.021Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:31:22.939Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:31:22.939Z] 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.
[2024-08-28T21:31:22.939Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:31:22.939Z] Movies recommended for you:
[2024-08-28T21:31:22.939Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:31:22.939Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:31:22.939Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12066.977 ms) ======
[2024-08-28T21:31:22.939Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-28T21:31:23.859Z] GC before operation: completed in 61.774 ms, heap usage 130.101 MB -> 50.803 MB.
[2024-08-28T21:31:24.779Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:26.667Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:28.556Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:30.447Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:31:31.377Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:31:33.266Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:34.189Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:31:35.107Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:31:35.107Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-28T21:31:35.107Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:31:35.107Z] Movies recommended for you:
[2024-08-28T21:31:35.107Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:31:35.107Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:31:35.107Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12009.415 ms) ======
[2024-08-28T21:31:35.107Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-28T21:31:35.107Z] GC before operation: completed in 61.083 ms, heap usage 87.466 MB -> 50.553 MB.
[2024-08-28T21:31:36.994Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:38.880Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:40.846Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:42.900Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:31:43.823Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:31:44.748Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:45.670Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:31:47.563Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:31:47.563Z] 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.
[2024-08-28T21:31:47.563Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:31:47.563Z] Movies recommended for you:
[2024-08-28T21:31:47.563Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:31:47.563Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:31:47.563Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12068.456 ms) ======
[2024-08-28T21:31:47.563Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-28T21:31:47.563Z] GC before operation: completed in 61.252 ms, heap usage 103.351 MB -> 50.836 MB.
[2024-08-28T21:31:49.454Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:51.345Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:53.241Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:55.145Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:31:56.066Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:31:56.986Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:59.083Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:00.003Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:00.003Z] 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.
[2024-08-28T21:32:00.003Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:32:00.003Z] Movies recommended for you:
[2024-08-28T21:32:00.003Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:00.003Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:00.003Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12440.890 ms) ======
[2024-08-28T21:32:00.003Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-28T21:32:00.003Z] GC before operation: completed in 66.804 ms, heap usage 89.028 MB -> 50.930 MB.
[2024-08-28T21:32:01.892Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:03.779Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:32:05.687Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:32:07.603Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:08.525Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:09.447Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:11.357Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:12.279Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:12.279Z] 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.
[2024-08-28T21:32:12.279Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:32:12.279Z] Movies recommended for you:
[2024-08-28T21:32:12.279Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:12.279Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:12.279Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12233.321 ms) ======
[2024-08-28T21:32:12.279Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-28T21:32:12.279Z] GC before operation: completed in 63.659 ms, heap usage 84.872 MB -> 50.569 MB.
[2024-08-28T21:32:14.168Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:16.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:32:17.978Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:32:19.871Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:20.789Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:21.725Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:23.614Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:24.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:24.533Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-28T21:32:24.533Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:32:24.534Z] Movies recommended for you:
[2024-08-28T21:32:24.534Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:24.534Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:24.534Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12155.766 ms) ======
[2024-08-28T21:32:24.534Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-28T21:32:24.534Z] GC before operation: completed in 61.854 ms, heap usage 86.401 MB -> 50.851 MB.
[2024-08-28T21:32:26.429Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:28.325Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:32:30.222Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:32:32.112Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:33.032Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:33.954Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:34.875Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:36.765Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:36.765Z] 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.
[2024-08-28T21:32:36.765Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:32:36.765Z] Movies recommended for you:
[2024-08-28T21:32:36.765Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:36.765Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:36.765Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12081.514 ms) ======
[2024-08-28T21:32:36.765Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-28T21:32:36.765Z] GC before operation: completed in 60.119 ms, heap usage 86.382 MB -> 50.922 MB.
[2024-08-28T21:32:38.660Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:41.232Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:32:42.475Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:32:44.368Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:45.286Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:46.207Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:47.134Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:48.061Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:48.986Z] 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.
[2024-08-28T21:32:48.986Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:32:48.986Z] Movies recommended for you:
[2024-08-28T21:32:48.986Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:48.986Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:48.986Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (11878.915 ms) ======
[2024-08-28T21:32:48.986Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-28T21:32:48.986Z] GC before operation: completed in 64.194 ms, heap usage 87.142 MB -> 50.836 MB.
[2024-08-28T21:32:50.881Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:51.799Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:32:53.688Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:32:55.580Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:56.498Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:58.388Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:59.306Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:33:00.226Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:33:00.226Z] 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.
[2024-08-28T21:33:00.226Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:33:00.226Z] Movies recommended for you:
[2024-08-28T21:33:00.226Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:33:00.226Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:33:00.226Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11848.610 ms) ======
[2024-08-28T21:33:00.226Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-28T21:33:00.226Z] GC before operation: completed in 68.641 ms, heap usage 109.470 MB -> 50.801 MB.
[2024-08-28T21:33:02.125Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:33:04.017Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:33:05.909Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:33:07.799Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:33:08.717Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:33:09.641Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:33:11.568Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:33:12.499Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:33:12.499Z] 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.
[2024-08-28T21:33:12.499Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:33:12.500Z] Movies recommended for you:
[2024-08-28T21:33:12.500Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:33:12.500Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:33:12.500Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12139.810 ms) ======
[2024-08-28T21:33:12.500Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-28T21:33:12.500Z] GC before operation: completed in 77.409 ms, heap usage 115.353 MB -> 51.018 MB.
[2024-08-28T21:33:14.403Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:33:16.292Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:33:18.182Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:33:20.079Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:33:21.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:33:22.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:33:23.847Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:33:24.768Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:33:25.688Z] 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.
[2024-08-28T21:33:25.688Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:33:25.688Z] Movies recommended for you:
[2024-08-28T21:33:25.688Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:33:25.688Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:33:25.688Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12540.136 ms) ======
[2024-08-28T21:33:25.688Z] -----------------------------------
[2024-08-28T21:33:25.688Z] renaissance-movie-lens_0_PASSED
[2024-08-28T21:33:25.688Z] -----------------------------------
[2024-08-28T21:33:25.688Z]
[2024-08-28T21:33:25.688Z] TEST TEARDOWN:
[2024-08-28T21:33:25.688Z] Nothing to be done for teardown.
[2024-08-28T21:33:25.688Z] renaissance-movie-lens_0 Finish Time: Wed Aug 28 21:33:25 2024 Epoch Time (ms): 1724880805416