renaissance-movie-lens_0
[2024-09-26T22:48:19.672Z] Running test renaissance-movie-lens_0 ...
[2024-09-26T22:48:19.672Z] ===============================================
[2024-09-26T22:48:19.672Z] renaissance-movie-lens_0 Start Time: Thu Sep 26 22:48:19 2024 Epoch Time (ms): 1727390899516
[2024-09-26T22:48:19.672Z] variation: NoOptions
[2024-09-26T22:48:19.672Z] JVM_OPTIONS:
[2024-09-26T22:48:19.672Z] { \
[2024-09-26T22:48:19.672Z] echo ""; echo "TEST SETUP:"; \
[2024-09-26T22:48:19.672Z] echo "Nothing to be done for setup."; \
[2024-09-26T22:48:19.672Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17273896177516/renaissance-movie-lens_0"; \
[2024-09-26T22:48:19.672Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17273896177516/renaissance-movie-lens_0"; \
[2024-09-26T22:48:19.672Z] echo ""; echo "TESTING:"; \
[2024-09-26T22:48:19.672Z] "/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_17273896177516/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-26T22:48:19.672Z] 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_17273896177516/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-26T22:48:19.672Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-26T22:48:19.672Z] echo "Nothing to be done for teardown."; \
[2024-09-26T22:48:19.672Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17273896177516/TestTargetResult";
[2024-09-26T22:48:19.672Z]
[2024-09-26T22:48:19.672Z] TEST SETUP:
[2024-09-26T22:48:19.672Z] Nothing to be done for setup.
[2024-09-26T22:48:19.672Z]
[2024-09-26T22:48:19.672Z] TESTING:
[2024-09-26T22:48:24.988Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-26T22:48:30.302Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-09-26T22:48:36.937Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-26T22:48:37.883Z] Training: 60056, validation: 20285, test: 19854
[2024-09-26T22:48:37.883Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-26T22:48:37.883Z] GC before operation: completed in 262.205 ms, heap usage 232.208 MB -> 29.329 MB.
[2024-09-26T22:48:49.328Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:48:54.657Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:48:59.997Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:49:05.340Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:49:07.275Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:49:10.264Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:49:13.264Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:49:16.258Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:49:17.202Z] 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.
[2024-09-26T22:49:17.202Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:49:17.202Z] Movies recommended for you:
[2024-09-26T22:49:17.202Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:49:17.202Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:49:17.202Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (39667.053 ms) ======
[2024-09-26T22:49:17.202Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-26T22:49:18.154Z] GC before operation: completed in 375.316 ms, heap usage 808.904 MB -> 49.231 MB.
[2024-09-26T22:49:22.264Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:49:25.653Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:49:29.792Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:49:33.906Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:49:36.897Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:49:38.827Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:49:41.823Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:49:44.810Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:49:44.810Z] 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.
[2024-09-26T22:49:44.810Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:49:45.754Z] Movies recommended for you:
[2024-09-26T22:49:45.754Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:49:45.754Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:49:45.754Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (27565.683 ms) ======
[2024-09-26T22:49:45.754Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-26T22:49:45.754Z] GC before operation: completed in 291.424 ms, heap usage 378.340 MB -> 45.504 MB.
[2024-09-26T22:49:49.873Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:49:52.868Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:49:56.977Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:50:01.085Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:50:03.018Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:50:04.953Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:50:06.887Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:50:09.870Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:50:09.870Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-09-26T22:50:09.870Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:50:09.870Z] Movies recommended for you:
[2024-09-26T22:50:09.870Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:50:09.870Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:50:09.870Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24728.259 ms) ======
[2024-09-26T22:50:09.870Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-26T22:50:10.851Z] GC before operation: completed in 276.989 ms, heap usage 244.965 MB -> 45.745 MB.
[2024-09-26T22:50:13.834Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:50:17.938Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:50:21.043Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:50:25.160Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:50:27.098Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:50:29.726Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:50:31.663Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:50:33.601Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:50:34.544Z] 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.
[2024-09-26T22:50:34.544Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:50:34.544Z] Movies recommended for you:
[2024-09-26T22:50:34.544Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:50:34.544Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:50:34.544Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23913.650 ms) ======
[2024-09-26T22:50:34.544Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-26T22:50:34.544Z] GC before operation: completed in 264.111 ms, heap usage 1.264 GB -> 54.118 MB.
[2024-09-26T22:50:38.660Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:50:41.648Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:50:45.766Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:50:48.762Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:50:50.695Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:50:52.629Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:50:55.609Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:50:57.550Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:50:57.550Z] 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.
[2024-09-26T22:50:57.550Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:50:58.492Z] Movies recommended for you:
[2024-09-26T22:50:58.492Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:50:58.492Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:50:58.492Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (23244.358 ms) ======
[2024-09-26T22:50:58.492Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-26T22:50:58.492Z] GC before operation: completed in 284.724 ms, heap usage 1.274 GB -> 54.413 MB.
[2024-09-26T22:51:01.487Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:51:05.607Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:51:08.599Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:51:12.712Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:51:14.649Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:51:16.591Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:51:18.528Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:51:21.519Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:51:21.519Z] 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.
[2024-09-26T22:51:21.519Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:51:21.519Z] Movies recommended for you:
[2024-09-26T22:51:21.519Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:51:21.519Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:51:21.519Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (23334.858 ms) ======
[2024-09-26T22:51:21.519Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-26T22:51:21.519Z] GC before operation: completed in 269.000 ms, heap usage 1.284 GB -> 54.489 MB.
[2024-09-26T22:51:25.634Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:51:28.676Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:51:31.818Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:51:35.534Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:51:37.469Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:51:39.409Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:51:42.404Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:51:44.343Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:51:44.343Z] 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.
[2024-09-26T22:51:44.343Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:51:45.286Z] Movies recommended for you:
[2024-09-26T22:51:45.286Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:51:45.286Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:51:45.286Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23009.003 ms) ======
[2024-09-26T22:51:45.286Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-26T22:51:45.286Z] GC before operation: completed in 249.798 ms, heap usage 1.224 GB -> 53.679 MB.
[2024-09-26T22:51:48.287Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:51:52.410Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:51:55.404Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:51:59.521Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:52:01.460Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:52:03.397Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:52:05.507Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:52:07.444Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:52:08.390Z] 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.
[2024-09-26T22:52:08.391Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:52:08.391Z] Movies recommended for you:
[2024-09-26T22:52:08.391Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:52:08.391Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:52:08.391Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (23252.192 ms) ======
[2024-09-26T22:52:08.391Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-26T22:52:08.391Z] GC before operation: completed in 277.016 ms, heap usage 1.219 GB -> 54.549 MB.
[2024-09-26T22:52:12.504Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:52:15.487Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:52:19.634Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:52:22.623Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:52:25.619Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:52:27.553Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:52:29.489Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:52:31.536Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:52:32.481Z] 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.
[2024-09-26T22:52:32.481Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:52:32.481Z] Movies recommended for you:
[2024-09-26T22:52:32.481Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:52:32.481Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:52:32.481Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (24139.868 ms) ======
[2024-09-26T22:52:32.481Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-26T22:52:33.426Z] GC before operation: completed in 250.540 ms, heap usage 1.239 GB -> 58.509 MB.
[2024-09-26T22:52:36.436Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:52:40.178Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:52:43.168Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:52:47.302Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:52:49.241Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:52:51.176Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:52:54.179Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:52:56.113Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:52:56.113Z] 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.
[2024-09-26T22:52:57.058Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:52:57.058Z] Movies recommended for you:
[2024-09-26T22:52:57.058Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:52:57.058Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:52:57.058Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (23723.562 ms) ======
[2024-09-26T22:52:57.058Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-26T22:52:57.058Z] GC before operation: completed in 350.914 ms, heap usage 1.322 GB -> 54.569 MB.
[2024-09-26T22:53:01.212Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:53:04.204Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:53:08.317Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:53:11.314Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:53:13.248Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:53:16.236Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:53:18.173Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:53:20.112Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:53:21.056Z] 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.
[2024-09-26T22:53:21.056Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:53:21.056Z] Movies recommended for you:
[2024-09-26T22:53:21.056Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:53:21.056Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:53:21.056Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (24002.854 ms) ======
[2024-09-26T22:53:21.056Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-26T22:53:21.056Z] GC before operation: completed in 262.971 ms, heap usage 121.563 MB -> 45.777 MB.
[2024-09-26T22:53:25.172Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:53:28.165Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:53:32.291Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:53:35.287Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:53:37.223Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:53:39.165Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:53:42.159Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:53:43.104Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:53:44.739Z] 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.
[2024-09-26T22:53:44.740Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:53:44.740Z] Movies recommended for you:
[2024-09-26T22:53:44.740Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:53:44.740Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:53:44.740Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22753.695 ms) ======
[2024-09-26T22:53:44.740Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-26T22:53:44.740Z] GC before operation: completed in 252.170 ms, heap usage 1.239 GB -> 55.818 MB.
[2024-09-26T22:53:47.741Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:53:50.732Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:53:53.722Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:53:56.715Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:53:59.717Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:54:01.653Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:54:03.588Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:54:05.532Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:54:05.532Z] 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.
[2024-09-26T22:54:05.532Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:54:06.474Z] Movies recommended for you:
[2024-09-26T22:54:06.474Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:54:06.474Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:54:06.474Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (21657.843 ms) ======
[2024-09-26T22:54:06.474Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-26T22:54:06.474Z] GC before operation: completed in 253.638 ms, heap usage 1.256 GB -> 54.342 MB.
[2024-09-26T22:54:09.462Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:54:12.448Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:54:16.564Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:54:19.576Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:54:21.511Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:54:23.443Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:54:25.379Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:54:27.314Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:54:28.256Z] 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.
[2024-09-26T22:54:28.256Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:54:28.256Z] Movies recommended for you:
[2024-09-26T22:54:28.256Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:54:28.256Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:54:28.256Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (21746.366 ms) ======
[2024-09-26T22:54:28.256Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-26T22:54:28.256Z] GC before operation: completed in 243.400 ms, heap usage 121.069 MB -> 51.273 MB.
[2024-09-26T22:54:31.241Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:54:34.225Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:54:38.339Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:54:41.330Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:54:43.270Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:54:45.204Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:54:47.139Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:54:49.470Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:54:49.470Z] 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.
[2024-09-26T22:54:49.470Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:54:49.470Z] Movies recommended for you:
[2024-09-26T22:54:49.470Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:54:49.470Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:54:49.470Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (21480.494 ms) ======
[2024-09-26T22:54:49.470Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-26T22:54:50.411Z] GC before operation: completed in 245.547 ms, heap usage 120.861 MB -> 48.859 MB.
[2024-09-26T22:54:53.395Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:54:56.385Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:54:59.375Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:55:03.513Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:55:05.448Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:55:07.383Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:55:09.321Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:55:11.271Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:55:12.228Z] 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.
[2024-09-26T22:55:12.228Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:55:12.228Z] Movies recommended for you:
[2024-09-26T22:55:12.228Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:55:12.228Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:55:12.228Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (22020.477 ms) ======
[2024-09-26T22:55:12.228Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-26T22:55:12.228Z] GC before operation: completed in 205.095 ms, heap usage 1.238 GB -> 54.296 MB.
[2024-09-26T22:55:15.224Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:55:19.343Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:55:22.346Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:55:25.334Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:55:27.275Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:55:29.209Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:55:31.145Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:55:33.083Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:55:34.028Z] 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.
[2024-09-26T22:55:34.028Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:55:34.028Z] Movies recommended for you:
[2024-09-26T22:55:34.028Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:55:34.028Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:55:34.029Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (21641.888 ms) ======
[2024-09-26T22:55:34.029Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-26T22:55:34.029Z] GC before operation: completed in 274.063 ms, heap usage 1.285 GB -> 54.878 MB.
[2024-09-26T22:55:37.023Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:55:41.140Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:55:44.129Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:55:47.123Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:55:49.058Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:55:50.995Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:55:52.951Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:55:54.600Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:55:55.574Z] 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.
[2024-09-26T22:55:55.574Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:55:55.574Z] Movies recommended for you:
[2024-09-26T22:55:55.574Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:55:55.574Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:55:55.574Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (21525.817 ms) ======
[2024-09-26T22:55:55.574Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-26T22:55:55.574Z] GC before operation: completed in 237.791 ms, heap usage 1.236 GB -> 54.559 MB.
[2024-09-26T22:55:59.692Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:56:02.680Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:56:05.671Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:56:08.661Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:56:10.601Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:56:12.540Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:56:14.479Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:56:17.471Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:56:17.471Z] 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.
[2024-09-26T22:56:17.471Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:56:17.471Z] Movies recommended for you:
[2024-09-26T22:56:17.471Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:56:17.471Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:56:17.471Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (21629.185 ms) ======
[2024-09-26T22:56:17.471Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-26T22:56:17.471Z] GC before operation: completed in 240.814 ms, heap usage 1.228 GB -> 54.752 MB.
[2024-09-26T22:56:21.589Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T22:56:24.576Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T22:56:27.565Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T22:56:30.642Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T22:56:32.578Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T22:56:35.564Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T22:56:37.509Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T22:56:39.447Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T22:56:39.447Z] 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.
[2024-09-26T22:56:39.447Z] The best model improves the baseline by 14.43%.
[2024-09-26T22:56:39.447Z] Movies recommended for you:
[2024-09-26T22:56:39.447Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T22:56:39.447Z] There is no way to check that no silent failure occurred.
[2024-09-26T22:56:39.447Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (21844.795 ms) ======
[2024-09-26T22:56:42.440Z] -----------------------------------
[2024-09-26T22:56:42.440Z] renaissance-movie-lens_0_PASSED
[2024-09-26T22:56:42.440Z] -----------------------------------
[2024-09-26T22:56:42.440Z]
[2024-09-26T22:56:42.440Z] TEST TEARDOWN:
[2024-09-26T22:56:42.440Z] Nothing to be done for teardown.
[2024-09-26T22:56:42.440Z] renaissance-movie-lens_0 Finish Time: Thu Sep 26 22:56:41 2024 Epoch Time (ms): 1727391401337