renaissance-movie-lens_0
[2025-12-20T13:41:56.896Z] Running test renaissance-movie-lens_0 ...
[2025-12-20T13:41:56.896Z] ===============================================
[2025-12-20T13:41:56.896Z] renaissance-movie-lens_0 Start Time: Sat Dec 20 13:41:56 2025 Epoch Time (ms): 1766238116267
[2025-12-20T13:41:56.896Z] variation: NoOptions
[2025-12-20T13:41:56.896Z] JVM_OPTIONS:
[2025-12-20T13:41:56.896Z] { \
[2025-12-20T13:41:56.896Z] echo ""; echo "TEST SETUP:"; \
[2025-12-20T13:41:56.896Z] echo "Nothing to be done for setup."; \
[2025-12-20T13:41:56.896Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17662360313775/renaissance-movie-lens_0"; \
[2025-12-20T13:41:56.896Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17662360313775/renaissance-movie-lens_0"; \
[2025-12-20T13:41:56.896Z] echo ""; echo "TESTING:"; \
[2025-12-20T13:41:56.896Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_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_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17662360313775/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-20T13:41:56.896Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17662360313775/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-20T13:41:56.896Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-20T13:41:56.896Z] echo "Nothing to be done for teardown."; \
[2025-12-20T13:41:56.896Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17662360313775/TestTargetResult";
[2025-12-20T13:41:56.896Z]
[2025-12-20T13:41:56.896Z] TEST SETUP:
[2025-12-20T13:41:56.896Z] Nothing to be done for setup.
[2025-12-20T13:41:56.896Z]
[2025-12-20T13:41:56.896Z] TESTING:
[2025-12-20T13:41:57.514Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-20T13:41:57.514Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/output_17662360313775/renaissance-movie-lens_0/launcher-134156-262178032425956593/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-20T13:41:57.514Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-20T13:41:57.514Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-20T13:42:01.257Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-12-20T13:42:05.985Z] 13:42:05.888 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-20T13:42:08.031Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-20T13:42:08.648Z] Training: 60056, validation: 20285, test: 19854
[2025-12-20T13:42:08.648Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-20T13:42:09.289Z] GC before operation: completed in 218.634 ms, heap usage 264.275 MB -> 75.526 MB.
[2025-12-20T13:42:15.263Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:42:19.004Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:42:22.768Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:42:26.532Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:42:27.835Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:42:29.581Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:42:31.615Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:42:33.626Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:42:34.281Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:42:34.281Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:42:34.281Z] Top recommended movies for user id 72:
[2025-12-20T13:42:34.281Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:42:34.281Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:42:34.281Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:42:34.281Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:42:34.281Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:42:34.281Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25076.281 ms) ======
[2025-12-20T13:42:34.281Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-20T13:42:34.281Z] GC before operation: completed in 197.423 ms, heap usage 148.034 MB -> 85.629 MB.
[2025-12-20T13:42:37.105Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:42:39.921Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:42:42.755Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:42:44.825Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:42:46.927Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:42:48.212Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:42:49.503Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:42:51.540Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:42:51.540Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:42:51.540Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:42:52.157Z] Top recommended movies for user id 72:
[2025-12-20T13:42:52.157Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:42:52.157Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:42:52.157Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:42:52.157Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:42:52.157Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:42:52.157Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17463.754 ms) ======
[2025-12-20T13:42:52.157Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-20T13:42:52.157Z] GC before operation: completed in 152.227 ms, heap usage 304.635 MB -> 89.507 MB.
[2025-12-20T13:42:54.197Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:42:57.028Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:42:59.938Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:43:01.982Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:43:03.305Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:43:05.384Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:43:06.679Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:43:08.713Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:43:08.713Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:43:08.713Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:43:08.713Z] Top recommended movies for user id 72:
[2025-12-20T13:43:08.713Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:43:08.713Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:43:08.713Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:43:08.713Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:43:08.713Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:43:08.713Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16897.529 ms) ======
[2025-12-20T13:43:08.713Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-20T13:43:09.446Z] GC before operation: completed in 171.839 ms, heap usage 391.075 MB -> 88.547 MB.
[2025-12-20T13:43:11.520Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:43:14.370Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:43:17.227Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:43:20.044Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:43:21.330Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:43:22.637Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:43:24.663Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:43:25.953Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:43:26.578Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:43:26.578Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:43:26.578Z] Top recommended movies for user id 72:
[2025-12-20T13:43:26.578Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:43:26.578Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:43:26.578Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:43:26.578Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:43:26.578Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:43:26.578Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17675.523 ms) ======
[2025-12-20T13:43:26.578Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-20T13:43:27.207Z] GC before operation: completed in 141.421 ms, heap usage 443.222 MB -> 91.991 MB.
[2025-12-20T13:43:29.278Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:43:32.143Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:43:35.014Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:43:37.440Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:43:39.451Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:43:40.751Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:43:42.805Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:43:44.094Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:43:44.094Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:43:44.094Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:43:44.724Z] Top recommended movies for user id 72:
[2025-12-20T13:43:44.724Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:43:44.724Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:43:44.724Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:43:44.724Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:43:44.724Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:43:44.724Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17523.385 ms) ======
[2025-12-20T13:43:44.724Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-20T13:43:44.724Z] GC before operation: completed in 188.680 ms, heap usage 271.730 MB -> 88.478 MB.
[2025-12-20T13:43:47.594Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:43:50.452Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:43:53.272Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:43:55.291Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:43:57.336Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:43:58.676Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:44:00.714Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:44:02.012Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:44:02.012Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:44:02.012Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:44:02.012Z] Top recommended movies for user id 72:
[2025-12-20T13:44:02.012Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:44:02.012Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:44:02.012Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:44:02.012Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:44:02.012Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:44:02.012Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17661.029 ms) ======
[2025-12-20T13:44:02.012Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-20T13:44:02.635Z] GC before operation: completed in 158.885 ms, heap usage 240.443 MB -> 88.770 MB.
[2025-12-20T13:44:05.511Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:44:08.584Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:44:11.424Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:44:13.435Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:44:15.473Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:44:16.756Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:44:18.775Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:44:20.804Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:44:20.804Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:44:20.804Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:44:20.804Z] Top recommended movies for user id 72:
[2025-12-20T13:44:20.804Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:44:20.804Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:44:20.804Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:44:20.804Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:44:20.804Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:44:20.804Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18496.278 ms) ======
[2025-12-20T13:44:20.805Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-20T13:44:21.433Z] GC before operation: completed in 192.872 ms, heap usage 243.737 MB -> 88.782 MB.
[2025-12-20T13:44:24.258Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:44:26.335Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:44:29.254Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:44:31.294Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:44:33.351Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:44:34.648Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:44:36.684Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:44:37.976Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:44:38.643Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:44:38.643Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:44:38.643Z] Top recommended movies for user id 72:
[2025-12-20T13:44:38.643Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:44:38.643Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:44:38.643Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:44:38.643Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:44:38.643Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:44:38.643Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17339.564 ms) ======
[2025-12-20T13:44:38.643Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-20T13:44:38.643Z] GC before operation: completed in 169.210 ms, heap usage 108.414 MB -> 88.732 MB.
[2025-12-20T13:44:41.498Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:44:44.379Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:44:47.233Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:44:48.949Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:44:50.255Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:44:52.293Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:44:53.636Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:44:54.947Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:44:55.573Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:44:55.573Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:44:55.573Z] Top recommended movies for user id 72:
[2025-12-20T13:44:55.573Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:44:55.573Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:44:55.573Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:44:55.573Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:44:55.573Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:44:55.573Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16970.863 ms) ======
[2025-12-20T13:44:55.573Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-20T13:44:55.573Z] GC before operation: completed in 187.159 ms, heap usage 387.709 MB -> 89.161 MB.
[2025-12-20T13:44:58.389Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:45:00.511Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:45:03.357Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:45:05.415Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:45:06.725Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:45:08.773Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:45:10.095Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:45:12.109Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:45:12.109Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:45:12.109Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:45:12.109Z] Top recommended movies for user id 72:
[2025-12-20T13:45:12.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:45:12.110Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:45:12.110Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:45:12.110Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:45:12.110Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:45:12.110Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16457.635 ms) ======
[2025-12-20T13:45:12.110Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-20T13:45:12.742Z] GC before operation: completed in 183.129 ms, heap usage 141.059 MB -> 88.946 MB.
[2025-12-20T13:45:14.783Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:45:17.670Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:45:20.549Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:45:23.536Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:45:24.894Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:45:26.970Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:45:29.022Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:45:30.334Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:45:30.334Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:45:30.334Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:45:30.952Z] Top recommended movies for user id 72:
[2025-12-20T13:45:30.952Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:45:30.952Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:45:30.952Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:45:30.952Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:45:30.952Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:45:30.952Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18241.360 ms) ======
[2025-12-20T13:45:30.952Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-20T13:45:30.952Z] GC before operation: completed in 187.133 ms, heap usage 441.599 MB -> 92.331 MB.
[2025-12-20T13:45:33.782Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:45:35.837Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:45:38.679Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:45:41.493Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:45:42.783Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:45:44.813Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:45:46.940Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:45:47.563Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:45:48.199Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:45:48.199Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:45:48.199Z] Top recommended movies for user id 72:
[2025-12-20T13:45:48.199Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:45:48.199Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:45:48.199Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:45:48.199Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:45:48.199Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:45:48.199Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17366.850 ms) ======
[2025-12-20T13:45:48.199Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-20T13:45:48.199Z] GC before operation: completed in 174.636 ms, heap usage 443.515 MB -> 92.515 MB.
[2025-12-20T13:45:51.028Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:45:53.874Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:45:56.768Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:45:59.131Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:46:00.464Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:46:02.524Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:46:03.805Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:46:05.872Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:46:05.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:46:05.872Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:46:06.516Z] Top recommended movies for user id 72:
[2025-12-20T13:46:06.516Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:46:06.516Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:46:06.516Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:46:06.516Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:46:06.516Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:46:06.516Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17782.501 ms) ======
[2025-12-20T13:46:06.516Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-20T13:46:06.516Z] GC before operation: completed in 148.477 ms, heap usage 160.357 MB -> 88.964 MB.
[2025-12-20T13:46:08.569Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:46:11.420Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:46:13.451Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:46:15.461Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:46:16.758Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:46:18.044Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:46:20.062Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:46:21.345Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:46:21.345Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:46:21.345Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:46:21.345Z] Top recommended movies for user id 72:
[2025-12-20T13:46:21.345Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:46:21.345Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:46:21.345Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:46:21.345Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:46:21.345Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:46:21.345Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15166.910 ms) ======
[2025-12-20T13:46:21.345Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-20T13:46:21.980Z] GC before operation: completed in 150.426 ms, heap usage 353.579 MB -> 89.230 MB.
[2025-12-20T13:46:24.016Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:46:26.059Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:46:28.903Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:46:30.217Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:46:31.505Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:46:33.520Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:46:34.809Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:46:35.891Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:46:36.524Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:46:36.524Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:46:36.524Z] Top recommended movies for user id 72:
[2025-12-20T13:46:36.524Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:46:36.524Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:46:36.524Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:46:36.524Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:46:36.524Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:46:36.524Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14695.983 ms) ======
[2025-12-20T13:46:36.524Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-20T13:46:36.524Z] GC before operation: completed in 202.465 ms, heap usage 141.414 MB -> 88.990 MB.
[2025-12-20T13:46:39.335Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:46:41.344Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:46:43.354Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:46:45.368Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:46:46.664Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:46:47.967Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:46:50.015Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:46:50.641Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:46:51.258Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:46:51.258Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:46:51.258Z] Top recommended movies for user id 72:
[2025-12-20T13:46:51.258Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:46:51.258Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:46:51.258Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:46:51.258Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:46:51.258Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:46:51.258Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14559.344 ms) ======
[2025-12-20T13:46:51.258Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-20T13:46:51.258Z] GC before operation: completed in 161.328 ms, heap usage 222.263 MB -> 89.088 MB.
[2025-12-20T13:46:53.306Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:46:56.136Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:46:58.167Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:47:00.214Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:47:01.513Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:47:02.810Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:47:04.100Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:47:05.432Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:47:05.432Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:47:05.432Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:47:05.432Z] Top recommended movies for user id 72:
[2025-12-20T13:47:05.432Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:47:05.432Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:47:05.432Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:47:05.432Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:47:05.432Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:47:05.432Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14241.108 ms) ======
[2025-12-20T13:47:05.432Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-20T13:47:05.432Z] GC before operation: completed in 193.488 ms, heap usage 230.336 MB -> 89.176 MB.
[2025-12-20T13:47:08.280Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:47:10.315Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:47:13.134Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:47:15.261Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:47:16.594Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:47:17.214Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:47:19.258Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:47:19.890Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:47:20.506Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:47:20.506Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:47:20.506Z] Top recommended movies for user id 72:
[2025-12-20T13:47:20.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:47:20.506Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:47:20.506Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:47:20.506Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:47:20.506Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:47:20.506Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14775.096 ms) ======
[2025-12-20T13:47:20.506Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-20T13:47:20.506Z] GC before operation: completed in 143.014 ms, heap usage 211.966 MB -> 88.938 MB.
[2025-12-20T13:47:22.511Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:47:24.532Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:47:27.352Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:47:29.389Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:47:30.684Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:47:31.972Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:47:33.275Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:47:34.571Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:47:34.571Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:47:34.571Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:47:35.190Z] Top recommended movies for user id 72:
[2025-12-20T13:47:35.190Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:47:35.190Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:47:35.190Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:47:35.190Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:47:35.190Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:47:35.190Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14351.168 ms) ======
[2025-12-20T13:47:35.190Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-20T13:47:35.190Z] GC before operation: completed in 180.329 ms, heap usage 227.970 MB -> 89.131 MB.
[2025-12-20T13:47:37.212Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T13:47:39.268Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T13:47:42.100Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T13:47:44.201Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T13:47:45.500Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T13:47:46.788Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T13:47:48.460Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T13:47:49.751Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T13:47:49.751Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-20T13:47:49.751Z] The best model improves the baseline by 14.34%.
[2025-12-20T13:47:49.751Z] Top recommended movies for user id 72:
[2025-12-20T13:47:49.751Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T13:47:49.751Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T13:47:49.751Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T13:47:49.751Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T13:47:49.751Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T13:47:49.751Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14804.677 ms) ======
[2025-12-20T13:47:50.380Z] -----------------------------------
[2025-12-20T13:47:50.380Z] renaissance-movie-lens_0_PASSED
[2025-12-20T13:47:50.380Z] -----------------------------------
[2025-12-20T13:47:50.380Z]
[2025-12-20T13:47:50.380Z] TEST TEARDOWN:
[2025-12-20T13:47:50.380Z] Nothing to be done for teardown.
[2025-12-20T13:47:50.380Z] renaissance-movie-lens_0 Finish Time: Sat Dec 20 13:47:49 2025 Epoch Time (ms): 1766238469939