renaissance-movie-lens_0
[2024-11-14T22:11:36.561Z] Running test renaissance-movie-lens_0 ...
[2024-11-14T22:11:36.561Z] ===============================================
[2024-11-14T22:11:36.561Z] renaissance-movie-lens_0 Start Time: Thu Nov 14 22:11:35 2024 Epoch Time (ms): 1731622295604
[2024-11-14T22:11:36.561Z] variation: NoOptions
[2024-11-14T22:11:36.561Z] JVM_OPTIONS:
[2024-11-14T22:11:36.561Z] { \
[2024-11-14T22:11:36.561Z] echo ""; echo "TEST SETUP:"; \
[2024-11-14T22:11:36.561Z] echo "Nothing to be done for setup."; \
[2024-11-14T22:11:36.561Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17316214058948/renaissance-movie-lens_0"; \
[2024-11-14T22:11:36.561Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17316214058948/renaissance-movie-lens_0"; \
[2024-11-14T22:11:36.561Z] echo ""; echo "TESTING:"; \
[2024-11-14T22:11:36.561Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17316214058948/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-14T22:11:36.561Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17316214058948/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-14T22:11:36.561Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-14T22:11:36.561Z] echo "Nothing to be done for teardown."; \
[2024-11-14T22:11:36.561Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17316214058948/TestTargetResult";
[2024-11-14T22:11:36.561Z]
[2024-11-14T22:11:36.561Z] TEST SETUP:
[2024-11-14T22:11:36.561Z] Nothing to be done for setup.
[2024-11-14T22:11:36.561Z]
[2024-11-14T22:11:36.561Z] TESTING:
[2024-11-14T22:11:39.505Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-14T22:11:42.818Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-11-14T22:11:48.081Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-14T22:11:48.081Z] Training: 60056, validation: 20285, test: 19854
[2024-11-14T22:11:48.081Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-14T22:11:48.081Z] GC before operation: completed in 184.685 ms, heap usage 59.211 MB -> 28.780 MB.
[2024-11-14T22:11:56.214Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:11:59.151Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:12:03.201Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:12:06.142Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:12:09.081Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:12:10.983Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:12:12.886Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:12:14.807Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:12:15.735Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:12:15.735Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:12:15.735Z] Movies recommended for you:
[2024-11-14T22:12:15.735Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:12:15.735Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:12:15.735Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27302.261 ms) ======
[2024-11-14T22:12:15.735Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-14T22:12:15.735Z] GC before operation: completed in 314.294 ms, heap usage 117.006 MB -> 47.137 MB.
[2024-11-14T22:12:19.791Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:12:22.734Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:12:25.690Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:12:28.633Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:12:30.534Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:12:32.441Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:12:34.348Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:12:36.258Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:12:36.258Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:12:36.258Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:12:37.186Z] Movies recommended for you:
[2024-11-14T22:12:37.186Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:12:37.186Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:12:37.186Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20754.192 ms) ======
[2024-11-14T22:12:37.186Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-14T22:12:37.186Z] GC before operation: completed in 239.034 ms, heap usage 410.615 MB -> 45.596 MB.
[2024-11-14T22:12:40.133Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:12:42.441Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:12:45.388Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:12:48.347Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:12:50.251Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:12:51.179Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:12:53.096Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:12:55.003Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:12:55.932Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:12:55.932Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:12:55.932Z] Movies recommended for you:
[2024-11-14T22:12:55.932Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:12:55.932Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:12:55.932Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18828.068 ms) ======
[2024-11-14T22:12:55.932Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-14T22:12:55.932Z] GC before operation: completed in 212.883 ms, heap usage 353.577 MB -> 45.991 MB.
[2024-11-14T22:12:58.882Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:13:00.785Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:13:03.730Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:13:06.670Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:13:08.575Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:13:09.504Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:13:11.409Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:13:13.313Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:13:14.250Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:13:14.250Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:13:14.250Z] Movies recommended for you:
[2024-11-14T22:13:14.250Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:13:14.250Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:13:14.250Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17964.436 ms) ======
[2024-11-14T22:13:14.250Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-14T22:13:14.250Z] GC before operation: completed in 179.891 ms, heap usage 109.526 MB -> 46.904 MB.
[2024-11-14T22:13:17.198Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:13:19.106Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:13:22.050Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:13:24.994Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:13:25.922Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:13:27.831Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:13:29.742Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:13:31.646Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:13:31.646Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:13:31.646Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:13:31.646Z] Movies recommended for you:
[2024-11-14T22:13:31.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:13:31.646Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:13:31.646Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17576.697 ms) ======
[2024-11-14T22:13:31.646Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-14T22:13:31.646Z] GC before operation: completed in 218.303 ms, heap usage 1.284 GB -> 55.295 MB.
[2024-11-14T22:13:34.597Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:13:37.543Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:13:39.446Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:13:42.026Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:13:43.933Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:13:45.838Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:13:46.770Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:13:48.678Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:13:49.607Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:13:49.607Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:13:49.607Z] Movies recommended for you:
[2024-11-14T22:13:49.607Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:13:49.607Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:13:49.607Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17512.787 ms) ======
[2024-11-14T22:13:49.607Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-14T22:13:49.607Z] GC before operation: completed in 202.156 ms, heap usage 101.129 MB -> 49.524 MB.
[2024-11-14T22:13:52.548Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:13:54.453Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:13:57.391Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:13:59.305Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:14:01.209Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:14:03.113Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:14:04.040Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:14:05.947Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:14:06.874Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:14:06.874Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:14:06.874Z] Movies recommended for you:
[2024-11-14T22:14:06.874Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:14:06.874Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:14:06.874Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16920.502 ms) ======
[2024-11-14T22:14:06.874Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-14T22:14:06.874Z] GC before operation: completed in 189.948 ms, heap usage 93.553 MB -> 49.922 MB.
[2024-11-14T22:14:09.817Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:14:11.721Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:14:14.665Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:14:16.569Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:14:18.476Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:14:20.378Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:14:22.446Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:14:23.374Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:14:24.300Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:14:24.300Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:14:24.300Z] Movies recommended for you:
[2024-11-14T22:14:24.300Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:14:24.300Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:14:24.300Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17296.860 ms) ======
[2024-11-14T22:14:24.300Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-14T22:14:24.300Z] GC before operation: completed in 195.868 ms, heap usage 103.060 MB -> 48.244 MB.
[2024-11-14T22:14:27.240Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:14:29.151Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:14:32.097Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:14:34.009Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:14:35.916Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:14:37.822Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:14:39.198Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:14:41.103Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:14:41.103Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:14:41.103Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:14:41.103Z] Movies recommended for you:
[2024-11-14T22:14:41.103Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:14:41.103Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:14:41.103Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17103.584 ms) ======
[2024-11-14T22:14:41.103Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-14T22:14:42.032Z] GC before operation: completed in 180.345 ms, heap usage 126.511 MB -> 47.702 MB.
[2024-11-14T22:14:43.937Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:14:46.879Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:14:48.846Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:14:51.790Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:14:53.701Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:14:54.628Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:14:56.535Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:14:58.438Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:14:58.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:14:58.438Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:14:58.438Z] Movies recommended for you:
[2024-11-14T22:14:58.438Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:14:58.438Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:14:58.438Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17181.185 ms) ======
[2024-11-14T22:14:58.438Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-14T22:14:59.363Z] GC before operation: completed in 215.828 ms, heap usage 124.374 MB -> 46.132 MB.
[2024-11-14T22:15:01.268Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:15:04.215Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:15:07.154Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:15:09.055Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:15:10.958Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:15:12.861Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:15:14.763Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:15:16.668Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:15:16.668Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:15:16.668Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:15:16.668Z] Movies recommended for you:
[2024-11-14T22:15:16.668Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:15:16.668Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:15:16.668Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17976.164 ms) ======
[2024-11-14T22:15:16.668Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-14T22:15:17.594Z] GC before operation: completed in 186.345 ms, heap usage 1.311 GB -> 54.516 MB.
[2024-11-14T22:15:19.497Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:15:22.438Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:15:25.385Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:15:27.291Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:15:29.193Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:15:31.096Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:15:33.002Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:15:34.907Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:15:34.907Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:15:34.907Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:15:34.907Z] Movies recommended for you:
[2024-11-14T22:15:34.907Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:15:34.907Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:15:34.907Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17919.779 ms) ======
[2024-11-14T22:15:34.907Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-14T22:15:34.907Z] GC before operation: completed in 181.380 ms, heap usage 1.306 GB -> 54.447 MB.
[2024-11-14T22:15:37.512Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:15:40.453Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:15:43.395Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:15:45.302Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:15:47.213Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:15:49.117Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:15:51.020Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:15:52.926Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:15:52.926Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:15:52.926Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:15:52.926Z] Movies recommended for you:
[2024-11-14T22:15:52.926Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:15:52.926Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:15:52.926Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18053.595 ms) ======
[2024-11-14T22:15:52.926Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-14T22:15:53.854Z] GC before operation: completed in 185.421 ms, heap usage 1.313 GB -> 55.016 MB.
[2024-11-14T22:15:55.759Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:15:58.694Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:16:01.634Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:16:03.537Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:16:05.440Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:16:07.345Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:16:09.250Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:16:11.153Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:16:11.153Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:16:11.153Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:16:11.153Z] Movies recommended for you:
[2024-11-14T22:16:11.153Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:16:11.153Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:16:11.153Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17982.377 ms) ======
[2024-11-14T22:16:11.153Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-14T22:16:12.080Z] GC before operation: completed in 161.792 ms, heap usage 137.705 MB -> 45.920 MB.
[2024-11-14T22:16:13.996Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:16:16.939Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:16:19.885Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:16:21.791Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:16:23.792Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:16:25.693Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:16:27.686Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:16:28.611Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:16:29.536Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:16:29.536Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:16:29.536Z] Movies recommended for you:
[2024-11-14T22:16:29.536Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:16:29.536Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:16:29.536Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17831.313 ms) ======
[2024-11-14T22:16:29.536Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-14T22:16:29.536Z] GC before operation: completed in 199.913 ms, heap usage 84.928 MB -> 50.697 MB.
[2024-11-14T22:16:32.475Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:16:34.379Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:16:36.961Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:16:39.903Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:16:41.808Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:16:43.715Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:16:45.619Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:16:46.546Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:16:47.473Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:16:47.473Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:16:47.473Z] Movies recommended for you:
[2024-11-14T22:16:47.473Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:16:47.473Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:16:47.473Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17777.740 ms) ======
[2024-11-14T22:16:47.473Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-14T22:16:47.473Z] GC before operation: completed in 162.915 ms, heap usage 139.574 MB -> 46.360 MB.
[2024-11-14T22:16:50.589Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:16:52.498Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:16:55.437Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:16:57.342Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:16:59.246Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:17:01.153Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:17:03.092Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:17:04.020Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:17:04.952Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:17:04.952Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:17:04.952Z] Movies recommended for you:
[2024-11-14T22:17:04.952Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:17:04.952Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:17:04.952Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17377.719 ms) ======
[2024-11-14T22:17:04.952Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-14T22:17:04.952Z] GC before operation: completed in 199.416 ms, heap usage 1.298 GB -> 60.612 MB.
[2024-11-14T22:17:07.901Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:17:10.849Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:17:12.756Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:17:15.699Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:17:16.627Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:17:18.535Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:17:20.440Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:17:22.406Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:17:22.406Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-14T22:17:22.406Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:17:22.406Z] Movies recommended for you:
[2024-11-14T22:17:22.406Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:17:22.406Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:17:22.406Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17442.956 ms) ======
[2024-11-14T22:17:22.406Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-14T22:17:23.358Z] GC before operation: completed in 209.201 ms, heap usage 110.558 MB -> 49.338 MB.
[2024-11-14T22:17:25.261Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:17:28.208Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:17:30.114Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:17:33.061Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:17:34.663Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:17:36.570Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:17:38.477Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:17:39.404Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:17:40.332Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:17:40.332Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:17:40.332Z] Movies recommended for you:
[2024-11-14T22:17:40.332Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:17:40.332Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:17:40.332Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17332.739 ms) ======
[2024-11-14T22:17:40.332Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-14T22:17:40.332Z] GC before operation: completed in 189.773 ms, heap usage 112.560 MB -> 48.560 MB.
[2024-11-14T22:17:43.276Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T22:17:45.182Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T22:17:48.125Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T22:17:50.029Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T22:17:51.930Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T22:17:53.836Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T22:17:54.764Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T22:17:56.678Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T22:17:57.607Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-14T22:17:57.607Z] The best model improves the baseline by 14.43%.
[2024-11-14T22:17:57.607Z] Movies recommended for you:
[2024-11-14T22:17:57.607Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T22:17:57.607Z] There is no way to check that no silent failure occurred.
[2024-11-14T22:17:57.607Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16986.304 ms) ======
[2024-11-14T22:17:58.535Z] -----------------------------------
[2024-11-14T22:17:58.535Z] renaissance-movie-lens_0_PASSED
[2024-11-14T22:17:58.535Z] -----------------------------------
[2024-11-14T22:17:58.535Z]
[2024-11-14T22:17:58.535Z] TEST TEARDOWN:
[2024-11-14T22:17:58.535Z] Nothing to be done for teardown.
[2024-11-14T22:17:58.535Z] renaissance-movie-lens_0 Finish Time: Thu Nov 14 22:17:58 2024 Epoch Time (ms): 1731622678350