renaissance-movie-lens_0
[2025-02-06T02:01:58.713Z] Running test renaissance-movie-lens_0 ...
[2025-02-06T02:01:58.713Z] ===============================================
[2025-02-06T02:01:58.713Z] renaissance-movie-lens_0 Start Time: Wed Feb 5 20:01:58 2025 Epoch Time (ms): 1738807318099
[2025-02-06T02:01:58.713Z] variation: NoOptions
[2025-02-06T02:01:58.713Z] JVM_OPTIONS:
[2025-02-06T02:01:58.713Z] { \
[2025-02-06T02:01:58.713Z] echo ""; echo "TEST SETUP:"; \
[2025-02-06T02:01:58.713Z] echo "Nothing to be done for setup."; \
[2025-02-06T02:01:58.713Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17388064545269/renaissance-movie-lens_0"; \
[2025-02-06T02:01:58.713Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17388064545269/renaissance-movie-lens_0"; \
[2025-02-06T02:01:58.713Z] echo ""; echo "TESTING:"; \
[2025-02-06T02:01:58.713Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_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_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17388064545269/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-06T02:01:58.713Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17388064545269/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-06T02:01:58.713Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-06T02:01:58.713Z] echo "Nothing to be done for teardown."; \
[2025-02-06T02:01:58.713Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17388064545269/TestTargetResult";
[2025-02-06T02:01:58.713Z]
[2025-02-06T02:01:58.713Z] TEST SETUP:
[2025-02-06T02:01:58.713Z] Nothing to be done for setup.
[2025-02-06T02:01:58.713Z]
[2025-02-06T02:01:58.713Z] TESTING:
[2025-02-06T02:02:00.906Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-06T02:02:03.115Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-02-06T02:02:06.204Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-06T02:02:06.204Z] Training: 60056, validation: 20285, test: 19854
[2025-02-06T02:02:06.204Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-06T02:02:06.204Z] GC before operation: completed in 82.586 ms, heap usage 118.007 MB -> 37.171 MB.
[2025-02-06T02:02:15.357Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:02:18.417Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:02:21.514Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:02:24.579Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:02:26.805Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:02:28.225Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:02:30.472Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:02:31.896Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:02:32.596Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:02:32.596Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:02:32.596Z] Movies recommended for you:
[2025-02-06T02:02:32.596Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:02:32.596Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:02:32.596Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26187.890 ms) ======
[2025-02-06T02:02:32.596Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-06T02:02:32.596Z] GC before operation: completed in 97.777 ms, heap usage 73.934 MB -> 48.091 MB.
[2025-02-06T02:02:35.650Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:02:38.844Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:02:41.099Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:02:44.188Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:02:45.597Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:02:47.029Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:02:49.234Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:02:50.650Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:02:50.650Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:02:50.650Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:02:50.650Z] Movies recommended for you:
[2025-02-06T02:02:50.650Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:02:50.650Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:02:50.650Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18224.834 ms) ======
[2025-02-06T02:02:50.650Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-06T02:02:50.650Z] GC before operation: completed in 104.547 ms, heap usage 264.533 MB -> 50.947 MB.
[2025-02-06T02:02:54.672Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:02:57.729Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:03:00.789Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:03:02.993Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:03:05.141Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:03:06.585Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:03:07.988Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:03:09.426Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:03:09.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:03:09.426Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:03:10.106Z] Movies recommended for you:
[2025-02-06T02:03:10.106Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:03:10.106Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:03:10.106Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18837.216 ms) ======
[2025-02-06T02:03:10.106Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-06T02:03:10.106Z] GC before operation: completed in 113.943 ms, heap usage 420.881 MB -> 51.532 MB.
[2025-02-06T02:03:12.307Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:03:15.383Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:03:17.606Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:03:19.825Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:03:21.235Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:03:22.648Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:03:24.056Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:03:25.475Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:03:26.157Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:03:26.157Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:03:26.157Z] Movies recommended for you:
[2025-02-06T02:03:26.157Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:03:26.157Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:03:26.157Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16232.368 ms) ======
[2025-02-06T02:03:26.157Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-06T02:03:26.157Z] GC before operation: completed in 134.201 ms, heap usage 391.827 MB -> 51.846 MB.
[2025-02-06T02:03:29.221Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:03:31.427Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:03:33.624Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:03:36.685Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:03:38.089Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:03:39.502Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:03:40.969Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:03:43.246Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:03:43.246Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:03:43.246Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:03:43.246Z] Movies recommended for you:
[2025-02-06T02:03:43.246Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:03:43.246Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:03:43.246Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16811.446 ms) ======
[2025-02-06T02:03:43.246Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-06T02:03:43.246Z] GC before operation: completed in 117.398 ms, heap usage 458.075 MB -> 52.011 MB.
[2025-02-06T02:03:46.336Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:03:48.529Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:03:50.734Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:03:52.978Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:03:54.429Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:03:55.851Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:03:58.077Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:03:58.757Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:03:59.448Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:03:59.448Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:03:59.448Z] Movies recommended for you:
[2025-02-06T02:03:59.448Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:03:59.448Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:03:59.448Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16183.687 ms) ======
[2025-02-06T02:03:59.448Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-06T02:03:59.448Z] GC before operation: completed in 112.701 ms, heap usage 479.487 MB -> 55.286 MB.
[2025-02-06T02:04:01.653Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:04:04.775Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:04:06.970Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:04:09.168Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:04:10.577Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:04:12.013Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:04:13.442Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:04:15.657Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:04:15.657Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:04:15.657Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:04:15.657Z] Movies recommended for you:
[2025-02-06T02:04:15.657Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:04:15.657Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:04:15.657Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16208.348 ms) ======
[2025-02-06T02:04:15.657Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-06T02:04:15.657Z] GC before operation: completed in 136.159 ms, heap usage 330.416 MB -> 52.029 MB.
[2025-02-06T02:04:18.732Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:04:20.950Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:04:24.031Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:04:26.252Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:04:27.663Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:04:29.079Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:04:30.504Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:04:31.916Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:04:32.592Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:04:32.592Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:04:32.592Z] Movies recommended for you:
[2025-02-06T02:04:32.592Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:04:32.592Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:04:32.592Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16533.552 ms) ======
[2025-02-06T02:04:32.592Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-06T02:04:32.592Z] GC before operation: completed in 1.076 ms, heap usage 87.547 MB -> 87.634 MB.
[2025-02-06T02:04:34.822Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:04:37.049Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:04:40.101Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:04:42.381Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:04:43.491Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:04:45.758Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:04:47.173Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:04:48.581Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:04:48.581Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:04:48.581Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:04:48.582Z] Movies recommended for you:
[2025-02-06T02:04:48.582Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:04:48.582Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:04:48.582Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16385.704 ms) ======
[2025-02-06T02:04:48.582Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-06T02:04:49.265Z] GC before operation: completed in 129.357 ms, heap usage 374.689 MB -> 52.145 MB.
[2025-02-06T02:04:51.474Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:04:53.691Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:04:56.753Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:04:58.960Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:05:00.371Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:05:01.787Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:05:03.206Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:05:04.614Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:05:05.317Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:05:05.317Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:05:05.317Z] Movies recommended for you:
[2025-02-06T02:05:05.317Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:05:05.317Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:05:05.317Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16323.029 ms) ======
[2025-02-06T02:05:05.317Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-06T02:05:05.317Z] GC before operation: completed in 135.174 ms, heap usage 380.766 MB -> 52.295 MB.
[2025-02-06T02:05:08.373Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:05:10.607Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:05:12.870Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:05:15.063Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:05:17.288Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:05:18.701Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:05:20.122Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:05:21.525Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:05:21.525Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:05:21.525Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:05:22.201Z] Movies recommended for you:
[2025-02-06T02:05:22.201Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:05:22.201Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:05:22.201Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16482.051 ms) ======
[2025-02-06T02:05:22.201Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-06T02:05:22.201Z] GC before operation: completed in 115.494 ms, heap usage 103.984 MB -> 53.506 MB.
[2025-02-06T02:05:24.419Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:05:27.487Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:05:29.697Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:05:31.900Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:05:33.311Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:05:35.239Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:05:36.662Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:05:38.066Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:05:38.066Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:05:38.066Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:05:38.066Z] Movies recommended for you:
[2025-02-06T02:05:38.066Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:05:38.066Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:05:38.066Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16309.245 ms) ======
[2025-02-06T02:05:38.066Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-06T02:05:38.747Z] GC before operation: completed in 141.024 ms, heap usage 417.279 MB -> 52.238 MB.
[2025-02-06T02:05:40.989Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:05:43.200Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:05:46.254Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:05:48.465Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:05:49.894Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:05:52.102Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:05:53.528Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:05:54.948Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:05:54.948Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:05:54.948Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:05:55.653Z] Movies recommended for you:
[2025-02-06T02:05:55.653Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:05:55.653Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:05:55.653Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16935.504 ms) ======
[2025-02-06T02:05:55.653Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-06T02:05:55.653Z] GC before operation: completed in 113.333 ms, heap usage 78.808 MB -> 54.270 MB.
[2025-02-06T02:05:57.871Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:06:00.079Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:06:03.201Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:06:05.406Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:06:06.834Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:06:08.257Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:06:10.456Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:06:11.139Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:06:11.815Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:06:11.815Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:06:11.815Z] Movies recommended for you:
[2025-02-06T02:06:11.815Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:06:11.815Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:06:11.815Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16401.637 ms) ======
[2025-02-06T02:06:11.815Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-06T02:06:11.815Z] GC before operation: completed in 124.853 ms, heap usage 442.704 MB -> 52.120 MB.
[2025-02-06T02:06:14.005Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:06:17.079Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:06:19.306Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:06:21.519Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:06:22.930Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:06:24.363Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:06:25.767Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:06:27.194Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:06:27.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:06:27.872Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:06:27.872Z] Movies recommended for you:
[2025-02-06T02:06:27.872Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:06:27.872Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:06:27.872Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15778.074 ms) ======
[2025-02-06T02:06:27.872Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-06T02:06:27.872Z] GC before operation: completed in 113.787 ms, heap usage 100.690 MB -> 53.944 MB.
[2025-02-06T02:06:30.210Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:06:33.273Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:06:35.484Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:06:37.682Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:06:39.108Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:06:40.525Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:06:42.786Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:06:43.485Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:06:44.164Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:06:44.164Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:06:44.164Z] Movies recommended for you:
[2025-02-06T02:06:44.164Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:06:44.164Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:06:44.164Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16205.589 ms) ======
[2025-02-06T02:06:44.164Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-06T02:06:44.164Z] GC before operation: completed in 120.211 ms, heap usage 455.110 MB -> 52.404 MB.
[2025-02-06T02:06:47.224Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:06:49.447Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:06:51.646Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:06:53.850Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:06:56.049Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:06:57.469Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:06:58.894Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:07:00.298Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:07:00.298Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:07:00.298Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:07:00.298Z] Movies recommended for you:
[2025-02-06T02:07:00.298Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:07:00.298Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:07:00.298Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16168.294 ms) ======
[2025-02-06T02:07:00.298Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-06T02:07:00.298Z] GC before operation: completed in 121.638 ms, heap usage 441.262 MB -> 52.299 MB.
[2025-02-06T02:07:03.357Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:07:05.560Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:07:07.773Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:07:10.836Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:07:12.239Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:07:13.642Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:07:15.041Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:07:16.472Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:07:16.472Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:07:16.472Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:07:16.472Z] Movies recommended for you:
[2025-02-06T02:07:16.472Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:07:16.472Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:07:16.472Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16239.577 ms) ======
[2025-02-06T02:07:16.472Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-06T02:07:17.156Z] GC before operation: completed in 108.423 ms, heap usage 325.430 MB -> 52.229 MB.
[2025-02-06T02:07:19.359Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:07:22.012Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:07:24.218Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:07:26.419Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:07:27.838Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:07:29.263Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:07:30.688Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:07:32.094Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:07:32.094Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:07:32.094Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:07:32.094Z] Movies recommended for you:
[2025-02-06T02:07:32.094Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:07:32.094Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:07:32.094Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15320.316 ms) ======
[2025-02-06T02:07:32.094Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-06T02:07:32.094Z] GC before operation: completed in 124.018 ms, heap usage 415.395 MB -> 52.456 MB.
[2025-02-06T02:07:35.174Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-06T02:07:37.523Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-06T02:07:39.736Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-06T02:07:41.950Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-06T02:07:43.365Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-06T02:07:44.779Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-06T02:07:46.198Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-06T02:07:48.435Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-06T02:07:48.435Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-06T02:07:48.435Z] The best model improves the baseline by 14.43%.
[2025-02-06T02:07:48.435Z] Movies recommended for you:
[2025-02-06T02:07:48.435Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-06T02:07:48.435Z] There is no way to check that no silent failure occurred.
[2025-02-06T02:07:48.435Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16185.395 ms) ======
[2025-02-06T02:07:49.865Z] -----------------------------------
[2025-02-06T02:07:49.865Z] renaissance-movie-lens_0_PASSED
[2025-02-06T02:07:49.865Z] -----------------------------------
[2025-02-06T02:07:49.865Z]
[2025-02-06T02:07:49.865Z] TEST TEARDOWN:
[2025-02-06T02:07:49.865Z] Nothing to be done for teardown.
[2025-02-06T02:07:49.865Z] renaissance-movie-lens_0 Finish Time: Wed Feb 5 20:07:49 2025 Epoch Time (ms): 1738807669435