renaissance-movie-lens_0
[2025-02-19T22:55:55.702Z] Running test renaissance-movie-lens_0 ...
[2025-02-19T22:55:55.702Z] ===============================================
[2025-02-19T22:55:55.702Z] renaissance-movie-lens_0 Start Time: Wed Feb 19 22:55:55 2025 Epoch Time (ms): 1740005755382
[2025-02-19T22:55:55.702Z] variation: NoOptions
[2025-02-19T22:55:55.702Z] JVM_OPTIONS:
[2025-02-19T22:55:55.702Z] { \
[2025-02-19T22:55:55.702Z] echo ""; echo "TEST SETUP:"; \
[2025-02-19T22:55:55.702Z] echo "Nothing to be done for setup."; \
[2025-02-19T22:55:55.702Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400049297763/renaissance-movie-lens_0"; \
[2025-02-19T22:55:55.702Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400049297763/renaissance-movie-lens_0"; \
[2025-02-19T22:55:55.702Z] echo ""; echo "TESTING:"; \
[2025-02-19T22:55:55.702Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400049297763/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-19T22:55:55.702Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400049297763/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-19T22:55:55.702Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-19T22:55:55.702Z] echo "Nothing to be done for teardown."; \
[2025-02-19T22:55:55.702Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400049297763/TestTargetResult";
[2025-02-19T22:55:55.702Z]
[2025-02-19T22:55:55.702Z] TEST SETUP:
[2025-02-19T22:55:55.702Z] Nothing to be done for setup.
[2025-02-19T22:55:55.702Z]
[2025-02-19T22:55:55.702Z] TESTING:
[2025-02-19T22:55:58.711Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-19T22:56:00.666Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-02-19T22:56:03.712Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-19T22:56:03.712Z] Training: 60056, validation: 20285, test: 19854
[2025-02-19T22:56:03.712Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-19T22:56:03.712Z] GC before operation: completed in 52.038 ms, heap usage 55.557 MB -> 37.375 MB.
[2025-02-19T22:56:09.258Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:56:12.451Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:56:15.465Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:56:17.417Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:56:19.379Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:56:20.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:56:22.293Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:56:23.244Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:56:24.195Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:56:24.195Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:56:24.195Z] Movies recommended for you:
[2025-02-19T22:56:24.195Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:56:24.195Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:56:24.195Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20348.528 ms) ======
[2025-02-19T22:56:24.195Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-19T22:56:24.195Z] GC before operation: completed in 79.205 ms, heap usage 316.881 MB -> 52.986 MB.
[2025-02-19T22:56:27.208Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:56:29.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:56:31.134Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:56:34.153Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:56:35.107Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:56:36.062Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:56:38.024Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:56:39.081Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:56:39.081Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:56:39.081Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:56:39.081Z] Movies recommended for you:
[2025-02-19T22:56:39.081Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:56:39.081Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:56:39.081Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15227.721 ms) ======
[2025-02-19T22:56:39.081Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-19T22:56:39.081Z] GC before operation: completed in 62.074 ms, heap usage 201.521 MB -> 49.888 MB.
[2025-02-19T22:56:42.313Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:56:43.262Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:56:46.275Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:56:47.229Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:56:49.180Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:56:50.135Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:56:51.084Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:56:53.042Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:56:53.042Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:56:53.042Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:56:53.042Z] Movies recommended for you:
[2025-02-19T22:56:53.042Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:56:53.042Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:56:53.042Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13450.994 ms) ======
[2025-02-19T22:56:53.042Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-19T22:56:53.042Z] GC before operation: completed in 56.372 ms, heap usage 267.075 MB -> 50.264 MB.
[2025-02-19T22:56:55.004Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:56:56.960Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:56:58.916Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:57:01.265Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:57:02.557Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:57:02.557Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:57:04.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:57:05.461Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:57:05.461Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:57:05.461Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:57:05.461Z] Movies recommended for you:
[2025-02-19T22:57:05.461Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:57:05.461Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:57:05.461Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (12718.815 ms) ======
[2025-02-19T22:57:05.461Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-19T22:57:05.461Z] GC before operation: completed in 58.890 ms, heap usage 81.224 MB -> 50.407 MB.
[2025-02-19T22:57:07.419Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:57:09.539Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:57:11.498Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:57:13.624Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:57:15.602Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:57:16.551Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:57:17.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:57:18.452Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:57:19.402Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:57:19.402Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:57:19.402Z] Movies recommended for you:
[2025-02-19T22:57:19.402Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:57:19.402Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:57:19.402Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13429.968 ms) ======
[2025-02-19T22:57:19.402Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-19T22:57:19.402Z] GC before operation: completed in 62.985 ms, heap usage 219.270 MB -> 50.744 MB.
[2025-02-19T22:57:21.353Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:57:23.306Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:57:25.258Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:57:27.209Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:57:28.161Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:57:29.113Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:57:31.067Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:57:32.018Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:57:32.018Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:57:32.018Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:57:32.018Z] Movies recommended for you:
[2025-02-19T22:57:32.018Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:57:32.018Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:57:32.018Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12936.368 ms) ======
[2025-02-19T22:57:32.018Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-19T22:57:32.018Z] GC before operation: completed in 64.545 ms, heap usage 216.346 MB -> 50.709 MB.
[2025-02-19T22:57:33.971Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:57:35.918Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:57:37.881Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:57:39.877Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:57:40.835Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:57:42.783Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:57:43.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:57:44.760Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:57:44.760Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:57:44.760Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:57:44.760Z] Movies recommended for you:
[2025-02-19T22:57:44.760Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:57:44.760Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:57:44.760Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12759.116 ms) ======
[2025-02-19T22:57:44.760Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-19T22:57:44.760Z] GC before operation: completed in 65.206 ms, heap usage 153.873 MB -> 50.891 MB.
[2025-02-19T22:57:46.710Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:57:48.662Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:57:50.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:57:52.623Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:57:53.572Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:57:54.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:57:56.485Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:57:57.436Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:57:57.436Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:57:57.436Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:57:57.436Z] Movies recommended for you:
[2025-02-19T22:57:57.436Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:57:57.436Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:57:57.436Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12329.119 ms) ======
[2025-02-19T22:57:57.436Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-19T22:57:57.436Z] GC before operation: completed in 59.978 ms, heap usage 76.444 MB -> 51.010 MB.
[2025-02-19T22:57:59.409Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:58:01.357Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:58:03.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:58:04.271Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:58:06.220Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:58:07.170Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:58:08.119Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:58:09.070Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:58:09.070Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:58:09.070Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:58:10.020Z] Movies recommended for you:
[2025-02-19T22:58:10.021Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:58:10.021Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:58:10.021Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12086.672 ms) ======
[2025-02-19T22:58:10.021Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-19T22:58:10.021Z] GC before operation: completed in 59.383 ms, heap usage 75.749 MB -> 50.921 MB.
[2025-02-19T22:58:10.971Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:58:12.925Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:58:14.881Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:58:16.848Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:58:17.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:58:18.749Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:58:19.698Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:58:21.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:58:21.691Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:58:21.692Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:58:21.692Z] Movies recommended for you:
[2025-02-19T22:58:21.692Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:58:21.692Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:58:21.692Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11898.391 ms) ======
[2025-02-19T22:58:21.692Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-19T22:58:21.692Z] GC before operation: completed in 60.792 ms, heap usage 77.033 MB -> 50.896 MB.
[2025-02-19T22:58:23.641Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:58:25.592Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:58:26.541Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:58:28.509Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:58:29.463Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:58:30.414Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:58:32.369Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:58:33.325Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:58:33.325Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:58:33.325Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:58:33.325Z] Movies recommended for you:
[2025-02-19T22:58:33.325Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:58:33.325Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:58:33.325Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11839.941 ms) ======
[2025-02-19T22:58:33.325Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-19T22:58:33.325Z] GC before operation: completed in 62.438 ms, heap usage 102.717 MB -> 50.764 MB.
[2025-02-19T22:58:35.771Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:58:37.066Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:58:39.038Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:58:40.986Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:58:41.935Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:58:42.885Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:58:43.838Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:58:44.789Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:58:45.746Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:58:45.746Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:58:45.746Z] Movies recommended for you:
[2025-02-19T22:58:45.746Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:58:45.746Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:58:45.746Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11999.498 ms) ======
[2025-02-19T22:58:45.746Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-19T22:58:45.747Z] GC before operation: completed in 58.389 ms, heap usage 77.607 MB -> 50.893 MB.
[2025-02-19T22:58:47.698Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:58:48.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:58:50.597Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:58:52.546Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:58:54.497Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:58:55.447Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:58:56.399Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:58:57.349Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:58:58.299Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:58:58.299Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:58:58.299Z] Movies recommended for you:
[2025-02-19T22:58:58.299Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:58:58.299Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:58:58.299Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12586.706 ms) ======
[2025-02-19T22:58:58.299Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-19T22:58:58.299Z] GC before operation: completed in 67.214 ms, heap usage 75.094 MB -> 51.006 MB.
[2025-02-19T22:59:00.253Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:59:02.208Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:59:04.157Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:59:06.107Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:59:07.057Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:59:08.007Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:59:09.997Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:59:10.947Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:59:10.947Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:59:10.947Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:59:10.947Z] Movies recommended for you:
[2025-02-19T22:59:10.947Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:59:10.947Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:59:10.947Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12786.064 ms) ======
[2025-02-19T22:59:10.947Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-19T22:59:10.947Z] GC before operation: completed in 67.515 ms, heap usage 76.215 MB -> 50.785 MB.
[2025-02-19T22:59:12.915Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:59:14.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:59:16.826Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:59:18.776Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:59:19.726Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:59:20.675Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:59:22.635Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:59:23.585Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:59:23.585Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:59:23.585Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:59:23.585Z] Movies recommended for you:
[2025-02-19T22:59:23.585Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:59:23.585Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:59:23.585Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12701.773 ms) ======
[2025-02-19T22:59:23.585Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-19T22:59:23.585Z] GC before operation: completed in 68.012 ms, heap usage 75.450 MB -> 50.966 MB.
[2025-02-19T22:59:25.536Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:59:27.529Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:59:29.487Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:59:31.438Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:59:32.388Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:59:33.338Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:59:35.295Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:59:36.248Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:59:36.248Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:59:36.248Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:59:36.248Z] Movies recommended for you:
[2025-02-19T22:59:36.248Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:59:36.248Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:59:36.248Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12646.253 ms) ======
[2025-02-19T22:59:36.248Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-19T22:59:36.248Z] GC before operation: completed in 65.112 ms, heap usage 76.805 MB -> 51.006 MB.
[2025-02-19T22:59:38.198Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:59:40.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:59:42.166Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:59:44.133Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:59:45.083Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:59:46.037Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:59:46.987Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T22:59:48.027Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T22:59:48.979Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T22:59:48.979Z] The best model improves the baseline by 14.52%.
[2025-02-19T22:59:48.979Z] Movies recommended for you:
[2025-02-19T22:59:48.979Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T22:59:48.979Z] There is no way to check that no silent failure occurred.
[2025-02-19T22:59:48.979Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12084.373 ms) ======
[2025-02-19T22:59:48.979Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-19T22:59:48.979Z] GC before operation: completed in 59.290 ms, heap usage 75.862 MB -> 50.847 MB.
[2025-02-19T22:59:49.929Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T22:59:51.881Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T22:59:53.831Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T22:59:56.995Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T22:59:58.340Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T22:59:58.340Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T22:59:59.290Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T23:00:00.241Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T23:00:00.241Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T23:00:00.241Z] The best model improves the baseline by 14.52%.
[2025-02-19T23:00:00.241Z] Movies recommended for you:
[2025-02-19T23:00:00.241Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T23:00:00.241Z] There is no way to check that no silent failure occurred.
[2025-02-19T23:00:00.241Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11744.157 ms) ======
[2025-02-19T23:00:00.241Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-19T23:00:00.241Z] GC before operation: completed in 57.876 ms, heap usage 76.568 MB -> 50.931 MB.
[2025-02-19T23:00:02.244Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T23:00:04.242Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T23:00:06.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T23:00:07.154Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T23:00:09.107Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T23:00:10.059Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T23:00:11.010Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T23:00:11.973Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T23:00:11.973Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T23:00:11.973Z] The best model improves the baseline by 14.52%.
[2025-02-19T23:00:11.973Z] Movies recommended for you:
[2025-02-19T23:00:11.973Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T23:00:11.973Z] There is no way to check that no silent failure occurred.
[2025-02-19T23:00:11.973Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11662.930 ms) ======
[2025-02-19T23:00:11.973Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-19T23:00:11.973Z] GC before operation: completed in 73.598 ms, heap usage 74.709 MB -> 51.122 MB.
[2025-02-19T23:00:13.930Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-19T23:00:15.882Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-19T23:00:17.836Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-19T23:00:18.786Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-19T23:00:20.738Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-19T23:00:21.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-19T23:00:22.638Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-19T23:00:23.588Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-19T23:00:23.588Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-02-19T23:00:23.588Z] The best model improves the baseline by 14.52%.
[2025-02-19T23:00:23.588Z] Movies recommended for you:
[2025-02-19T23:00:23.588Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-19T23:00:23.588Z] There is no way to check that no silent failure occurred.
[2025-02-19T23:00:23.588Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11694.528 ms) ======
[2025-02-19T23:00:24.541Z] -----------------------------------
[2025-02-19T23:00:24.541Z] renaissance-movie-lens_0_PASSED
[2025-02-19T23:00:24.541Z] -----------------------------------
[2025-02-19T23:00:24.541Z]
[2025-02-19T23:00:24.541Z] TEST TEARDOWN:
[2025-02-19T23:00:24.541Z] Nothing to be done for teardown.
[2025-02-19T23:00:24.541Z] renaissance-movie-lens_0 Finish Time: Wed Feb 19 23:00:23 2025 Epoch Time (ms): 1740006023860