renaissance-movie-lens_0
[2025-10-01T23:01:09.846Z] Running test renaissance-movie-lens_0 ...
[2025-10-01T23:01:09.846Z] ===============================================
[2025-10-01T23:01:09.846Z] renaissance-movie-lens_0 Start Time: Wed Oct 1 23:01:09 2025 Epoch Time (ms): 1759359669707
[2025-10-01T23:01:09.846Z] variation: NoOptions
[2025-10-01T23:01:09.846Z] JVM_OPTIONS:
[2025-10-01T23:01:09.846Z] { \
[2025-10-01T23:01:09.846Z] echo ""; echo "TEST SETUP:"; \
[2025-10-01T23:01:09.846Z] echo "Nothing to be done for setup."; \
[2025-10-01T23:01:09.846Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17593596692299/renaissance-movie-lens_0"; \
[2025-10-01T23:01:09.846Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17593596692299/renaissance-movie-lens_0"; \
[2025-10-01T23:01:09.846Z] echo ""; echo "TESTING:"; \
[2025-10-01T23:01:09.846Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/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_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17593596692299/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-10-01T23:01:09.846Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17593596692299/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-10-01T23:01:09.846Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-10-01T23:01:09.846Z] echo "Nothing to be done for teardown."; \
[2025-10-01T23:01:09.846Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17593596692299/TestTargetResult";
[2025-10-01T23:01:09.846Z]
[2025-10-01T23:01:09.846Z] TEST SETUP:
[2025-10-01T23:01:09.846Z] Nothing to be done for setup.
[2025-10-01T23:01:09.846Z]
[2025-10-01T23:01:09.846Z] TESTING:
[2025-10-01T23:01:18.682Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-10-01T23:01:27.308Z] 23:01:26.580 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-10-01T23:01:31.029Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-10-01T23:01:31.657Z] Training: 60056, validation: 20285, test: 19854
[2025-10-01T23:01:31.657Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-10-01T23:01:32.323Z] GC before operation: completed in 396.072 ms, heap usage 266.602 MB -> 75.770 MB.
[2025-10-01T23:01:42.870Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:01:50.124Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:01:56.685Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:02:01.725Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:02:05.816Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:02:09.682Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:02:12.549Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:02:16.316Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:02:16.316Z] 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.
[2025-10-01T23:02:16.316Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:02:16.962Z] Top recommended movies for user id 72:
[2025-10-01T23:02:16.962Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:02:16.962Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:02:16.962Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:02:16.962Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:02:16.962Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:02:16.962Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (44801.509 ms) ======
[2025-10-01T23:02:16.962Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-10-01T23:02:16.962Z] GC before operation: completed in 223.630 ms, heap usage 189.746 MB -> 94.084 MB.
[2025-10-01T23:02:21.768Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:02:26.903Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:02:32.839Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:02:37.798Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:02:41.649Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:02:44.655Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:02:48.454Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:02:50.510Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:02:51.185Z] 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.
[2025-10-01T23:02:51.185Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:02:51.907Z] Top recommended movies for user id 72:
[2025-10-01T23:02:51.907Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:02:51.907Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:02:51.907Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:02:51.907Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:02:51.907Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:02:51.907Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (34736.203 ms) ======
[2025-10-01T23:02:51.907Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-10-01T23:02:51.907Z] GC before operation: completed in 301.783 ms, heap usage 225.501 MB -> 87.889 MB.
[2025-10-01T23:02:56.748Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:03:01.587Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:03:06.437Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:03:11.579Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:03:15.397Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:03:17.806Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:03:21.797Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:03:24.781Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:03:25.456Z] 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.
[2025-10-01T23:03:25.456Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:03:25.456Z] Top recommended movies for user id 72:
[2025-10-01T23:03:25.456Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:03:25.456Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:03:25.456Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:03:25.456Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:03:25.456Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:03:25.456Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (33338.123 ms) ======
[2025-10-01T23:03:25.456Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-10-01T23:03:26.130Z] GC before operation: completed in 326.725 ms, heap usage 205.678 MB -> 88.513 MB.
[2025-10-01T23:03:30.949Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:03:37.068Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:03:41.810Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:03:46.761Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:03:50.686Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:03:53.661Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:03:57.705Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:04:01.780Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:04:01.780Z] 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.
[2025-10-01T23:04:01.780Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:04:02.440Z] Top recommended movies for user id 72:
[2025-10-01T23:04:02.440Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:04:02.440Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:04:02.440Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:04:02.440Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:04:02.440Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:04:02.440Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (36440.648 ms) ======
[2025-10-01T23:04:02.440Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-10-01T23:04:02.440Z] GC before operation: completed in 497.950 ms, heap usage 153.561 MB -> 88.824 MB.
[2025-10-01T23:04:07.325Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:04:13.303Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:04:19.368Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:04:24.326Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:04:29.324Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:04:32.297Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:04:36.158Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:04:39.059Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:04:39.059Z] 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.
[2025-10-01T23:04:39.718Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:04:39.718Z] Top recommended movies for user id 72:
[2025-10-01T23:04:39.718Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:04:39.718Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:04:39.718Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:04:39.718Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:04:39.718Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:04:39.718Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (36985.573 ms) ======
[2025-10-01T23:04:39.718Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-10-01T23:04:39.718Z] GC before operation: completed in 219.440 ms, heap usage 320.037 MB -> 89.012 MB.
[2025-10-01T23:04:44.734Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:04:50.905Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:04:54.840Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:05:00.788Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:05:02.902Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:05:05.129Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:05:09.351Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:05:12.267Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:05:12.267Z] 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.
[2025-10-01T23:05:12.267Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:05:12.913Z] Top recommended movies for user id 72:
[2025-10-01T23:05:12.914Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:05:12.914Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:05:12.914Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:05:12.914Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:05:12.914Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:05:12.914Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (33054.368 ms) ======
[2025-10-01T23:05:12.914Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-10-01T23:05:12.914Z] GC before operation: completed in 201.978 ms, heap usage 216.850 MB -> 89.163 MB.
[2025-10-01T23:05:20.785Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:05:24.675Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:05:30.810Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:05:35.691Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:05:38.756Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:05:41.695Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:05:45.656Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:05:48.718Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:05:49.358Z] 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.
[2025-10-01T23:05:49.358Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:05:49.358Z] Top recommended movies for user id 72:
[2025-10-01T23:05:49.358Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:05:49.358Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:05:49.358Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:05:49.358Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:05:49.358Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:05:49.358Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (36437.259 ms) ======
[2025-10-01T23:05:49.358Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-10-01T23:05:50.004Z] GC before operation: completed in 317.711 ms, heap usage 141.129 MB -> 89.042 MB.
[2025-10-01T23:05:56.136Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:05:59.955Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:06:05.989Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:06:11.285Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:06:14.647Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:06:17.660Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:06:21.525Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:06:24.595Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:06:25.219Z] 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.
[2025-10-01T23:06:25.219Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:06:25.823Z] Top recommended movies for user id 72:
[2025-10-01T23:06:25.823Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:06:25.823Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:06:25.823Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:06:25.823Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:06:25.823Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:06:25.823Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (35794.246 ms) ======
[2025-10-01T23:06:25.823Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-10-01T23:06:25.823Z] GC before operation: completed in 290.472 ms, heap usage 199.378 MB -> 89.242 MB.
[2025-10-01T23:06:31.985Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:06:36.789Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:06:41.696Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:06:45.611Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:06:48.687Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:06:51.764Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:06:55.651Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:06:58.802Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:06:59.599Z] 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.
[2025-10-01T23:06:59.599Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:06:59.599Z] Top recommended movies for user id 72:
[2025-10-01T23:06:59.599Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:06:59.599Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:06:59.599Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:06:59.599Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:06:59.599Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:06:59.599Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (33626.076 ms) ======
[2025-10-01T23:06:59.599Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-10-01T23:07:00.240Z] GC before operation: completed in 370.275 ms, heap usage 489.867 MB -> 92.739 MB.
[2025-10-01T23:07:06.375Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:07:12.781Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:07:18.364Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:07:23.227Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:07:26.308Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:07:29.323Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:07:32.208Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:07:35.100Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:07:35.787Z] 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.
[2025-10-01T23:07:35.787Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:07:35.787Z] Top recommended movies for user id 72:
[2025-10-01T23:07:35.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:07:35.787Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:07:35.787Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:07:35.787Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:07:35.787Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:07:35.787Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (35879.146 ms) ======
[2025-10-01T23:07:35.787Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-10-01T23:07:36.469Z] GC before operation: completed in 273.919 ms, heap usage 357.735 MB -> 89.670 MB.
[2025-10-01T23:07:41.243Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:07:46.101Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:07:52.179Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:07:57.289Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:08:00.356Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:08:03.430Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:08:07.314Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:08:09.425Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:08:10.124Z] 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.
[2025-10-01T23:08:10.124Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:08:10.778Z] Top recommended movies for user id 72:
[2025-10-01T23:08:10.778Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:08:10.778Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:08:10.778Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:08:10.778Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:08:10.778Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:08:10.778Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (34525.265 ms) ======
[2025-10-01T23:08:10.778Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-10-01T23:08:10.778Z] GC before operation: completed in 190.723 ms, heap usage 108.471 MB -> 89.267 MB.
[2025-10-01T23:08:15.800Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:08:21.984Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:08:28.126Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:08:33.105Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:08:36.918Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:08:39.849Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:08:43.665Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:08:46.678Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:08:46.678Z] 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.
[2025-10-01T23:08:47.350Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:08:47.350Z] Top recommended movies for user id 72:
[2025-10-01T23:08:47.350Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:08:47.350Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:08:47.350Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:08:47.350Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:08:47.350Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:08:47.350Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (36325.174 ms) ======
[2025-10-01T23:08:47.351Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-10-01T23:08:47.351Z] GC before operation: completed in 276.830 ms, heap usage 113.592 MB -> 89.163 MB.
[2025-10-01T23:08:52.708Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:08:57.600Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:09:03.313Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:09:07.184Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:09:10.130Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:09:13.175Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:09:15.328Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:09:19.175Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:09:19.175Z] 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.
[2025-10-01T23:09:19.175Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:09:19.175Z] Top recommended movies for user id 72:
[2025-10-01T23:09:19.175Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:09:19.175Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:09:19.175Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:09:19.175Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:09:19.175Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:09:19.175Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (31844.345 ms) ======
[2025-10-01T23:09:19.175Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-10-01T23:09:19.825Z] GC before operation: completed in 202.104 ms, heap usage 305.320 MB -> 89.651 MB.
[2025-10-01T23:09:23.745Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:09:28.822Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:09:34.771Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:09:38.487Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:09:40.548Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:09:44.485Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:09:47.196Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:09:50.591Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:09:50.591Z] 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.
[2025-10-01T23:09:51.355Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:09:51.355Z] Top recommended movies for user id 72:
[2025-10-01T23:09:51.355Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:09:51.355Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:09:51.355Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:09:51.355Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:09:51.355Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:09:51.355Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (31635.296 ms) ======
[2025-10-01T23:09:51.355Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-10-01T23:09:51.355Z] GC before operation: completed in 236.670 ms, heap usage 177.552 MB -> 89.296 MB.
[2025-10-01T23:09:56.466Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:10:01.716Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:10:06.809Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:10:11.831Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:10:14.846Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:10:17.214Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:10:21.139Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:10:23.366Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:10:24.028Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-10-01T23:10:24.028Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:10:24.028Z] Top recommended movies for user id 72:
[2025-10-01T23:10:24.028Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:10:24.028Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:10:24.028Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:10:24.028Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:10:24.028Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:10:24.028Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (32618.967 ms) ======
[2025-10-01T23:10:24.028Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-10-01T23:10:24.028Z] GC before operation: completed in 242.584 ms, heap usage 121.877 MB -> 89.355 MB.
[2025-10-01T23:10:28.865Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:10:32.759Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:10:37.761Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:10:42.555Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:10:45.445Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:10:47.496Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:10:49.565Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:10:52.597Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:10:53.265Z] 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.
[2025-10-01T23:10:53.265Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:10:53.265Z] Top recommended movies for user id 72:
[2025-10-01T23:10:53.265Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:10:53.265Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:10:53.265Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:10:53.265Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:10:53.265Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:10:53.265Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (28959.641 ms) ======
[2025-10-01T23:10:53.265Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-10-01T23:10:53.265Z] GC before operation: completed in 245.895 ms, heap usage 218.835 MB -> 89.398 MB.
[2025-10-01T23:10:58.285Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:11:01.620Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:11:06.669Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:11:09.764Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:11:12.790Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:11:15.617Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:11:19.535Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:11:21.615Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:11:22.253Z] 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.
[2025-10-01T23:11:22.253Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:11:22.253Z] Top recommended movies for user id 72:
[2025-10-01T23:11:22.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:11:22.253Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:11:22.253Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:11:22.253Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:11:22.253Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:11:22.253Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (29044.077 ms) ======
[2025-10-01T23:11:22.253Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-10-01T23:11:22.897Z] GC before operation: completed in 252.360 ms, heap usage 169.187 MB -> 89.461 MB.
[2025-10-01T23:11:27.996Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:11:33.009Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:11:37.928Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:11:41.716Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:11:44.649Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:11:47.439Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:11:50.348Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:11:52.415Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:11:53.070Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-10-01T23:11:53.070Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:11:53.070Z] Top recommended movies for user id 72:
[2025-10-01T23:11:53.070Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:11:53.070Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:11:53.070Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:11:53.070Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:11:53.070Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:11:53.070Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (30453.846 ms) ======
[2025-10-01T23:11:53.070Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-10-01T23:11:53.697Z] GC before operation: completed in 261.197 ms, heap usage 108.754 MB -> 89.426 MB.
[2025-10-01T23:11:58.466Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:12:03.281Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:12:07.134Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:12:11.381Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:12:13.435Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:12:15.466Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:12:18.352Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:12:20.408Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:12:21.067Z] 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.
[2025-10-01T23:12:21.067Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:12:21.067Z] Top recommended movies for user id 72:
[2025-10-01T23:12:21.067Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:12:21.067Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:12:21.067Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:12:21.067Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:12:21.067Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:12:21.067Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27594.707 ms) ======
[2025-10-01T23:12:21.067Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-10-01T23:12:21.067Z] GC before operation: completed in 266.101 ms, heap usage 392.585 MB -> 89.769 MB.
[2025-10-01T23:12:25.847Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-01T23:12:29.758Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-01T23:12:34.641Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-01T23:12:38.501Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-01T23:12:41.405Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-01T23:12:43.580Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-01T23:12:45.697Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-01T23:12:47.791Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-01T23:12:48.428Z] 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.
[2025-10-01T23:12:48.428Z] The best model improves the baseline by 14.34%.
[2025-10-01T23:12:48.428Z] Top recommended movies for user id 72:
[2025-10-01T23:12:48.428Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-10-01T23:12:48.428Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-10-01T23:12:48.428Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-10-01T23:12:48.428Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-10-01T23:12:48.428Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-10-01T23:12:48.428Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27223.880 ms) ======
[2025-10-01T23:12:49.058Z] -----------------------------------
[2025-10-01T23:12:49.058Z] renaissance-movie-lens_0_PASSED
[2025-10-01T23:12:49.058Z] -----------------------------------
[2025-10-01T23:12:49.058Z]
[2025-10-01T23:12:49.058Z] TEST TEARDOWN:
[2025-10-01T23:12:49.058Z] Nothing to be done for teardown.
[2025-10-01T23:12:49.058Z] renaissance-movie-lens_0 Finish Time: Wed Oct 1 23:12:48 2025 Epoch Time (ms): 1759360368760