renaissance-movie-lens_0
[2025-12-20T14:16:39.363Z] Running test renaissance-movie-lens_0 ...
[2025-12-20T14:16:39.363Z] ===============================================
[2025-12-20T14:16:39.363Z] renaissance-movie-lens_0 Start Time: Sat Dec 20 14:16:39 2025 Epoch Time (ms): 1766240199231
[2025-12-20T14:16:39.363Z] variation: NoOptions
[2025-12-20T14:16:39.363Z] JVM_OPTIONS:
[2025-12-20T14:16:39.363Z] { \
[2025-12-20T14:16:39.363Z] echo ""; echo "TEST SETUP:"; \
[2025-12-20T14:16:39.363Z] echo "Nothing to be done for setup."; \
[2025-12-20T14:16:39.363Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1766238330110/renaissance-movie-lens_0"; \
[2025-12-20T14:16:39.363Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1766238330110/renaissance-movie-lens_0"; \
[2025-12-20T14:16:39.363Z] echo ""; echo "TESTING:"; \
[2025-12-20T14:16:39.363Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1766238330110/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-20T14:16:39.364Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1766238330110/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-20T14:16:39.364Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-20T14:16:39.364Z] echo "Nothing to be done for teardown."; \
[2025-12-20T14:16:39.364Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_1766238330110/TestTargetResult";
[2025-12-20T14:16:39.364Z]
[2025-12-20T14:16:39.364Z] TEST SETUP:
[2025-12-20T14:16:39.364Z] Nothing to be done for setup.
[2025-12-20T14:16:39.364Z]
[2025-12-20T14:16:39.364Z] TESTING:
[2025-12-20T14:16:39.693Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-20T14:16:39.693Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_1766238330110/renaissance-movie-lens_0/launcher-141639-5056925600314447322/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-20T14:16:39.693Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-20T14:16:39.693Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-20T14:16:46.934Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-12-20T14:16:54.193Z] 14:16:53.104 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.
[2025-12-20T14:16:56.445Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-20T14:16:57.157Z] Training: 60056, validation: 20285, test: 19854
[2025-12-20T14:16:57.157Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-20T14:16:57.490Z] GC before operation: completed in 183.419 ms, heap usage 291.970 MB -> 75.623 MB.
[2025-12-20T14:17:06.465Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:17:11.213Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:17:14.990Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:17:18.769Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:17:21.723Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:17:23.391Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:17:25.711Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:17:27.370Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:17:27.702Z] 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.
[2025-12-20T14:17:27.702Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:17:28.033Z] Top recommended movies for user id 72:
[2025-12-20T14:17:28.033Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:17:28.033Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:17:28.033Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:17:28.033Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:17:28.033Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:17:28.033Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (30692.482 ms) ======
[2025-12-20T14:17:28.033Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-20T14:17:28.424Z] GC before operation: completed in 183.099 ms, heap usage 242.328 MB -> 85.879 MB.
[2025-12-20T14:17:31.374Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:17:34.322Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:17:37.265Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:17:39.501Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:17:40.636Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:17:42.282Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:17:43.935Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:17:45.579Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:17:45.907Z] 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.
[2025-12-20T14:17:45.907Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:17:45.907Z] Top recommended movies for user id 72:
[2025-12-20T14:17:45.907Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:17:45.907Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:17:45.907Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:17:45.907Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:17:45.907Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:17:45.907Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17681.269 ms) ======
[2025-12-20T14:17:45.907Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-20T14:17:46.239Z] GC before operation: completed in 162.907 ms, heap usage 145.096 MB -> 87.518 MB.
[2025-12-20T14:17:50.027Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:17:52.379Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:17:55.350Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:17:58.328Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:17:59.980Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:18:01.763Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:18:04.046Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:18:05.705Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:18:06.033Z] 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.
[2025-12-20T14:18:06.033Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:18:06.365Z] Top recommended movies for user id 72:
[2025-12-20T14:18:06.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:18:06.365Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:18:06.365Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:18:06.365Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:18:06.365Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:18:06.365Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20062.623 ms) ======
[2025-12-20T14:18:06.365Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-20T14:18:06.365Z] GC before operation: completed in 156.899 ms, heap usage 131.506 MB -> 88.047 MB.
[2025-12-20T14:18:10.138Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:18:13.121Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:18:16.119Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:18:19.074Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:18:20.212Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:18:21.886Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:18:24.128Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:18:25.270Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:18:25.977Z] 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.
[2025-12-20T14:18:25.977Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:18:25.977Z] Top recommended movies for user id 72:
[2025-12-20T14:18:25.977Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:18:25.977Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:18:25.977Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:18:25.977Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:18:25.977Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:18:25.977Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19554.534 ms) ======
[2025-12-20T14:18:25.977Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-20T14:18:25.977Z] GC before operation: completed in 160.702 ms, heap usage 359.440 MB -> 88.771 MB.
[2025-12-20T14:18:28.918Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:18:31.162Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:18:34.101Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:18:36.449Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:18:37.637Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:18:39.288Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:18:40.996Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:18:42.643Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:18:42.969Z] 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.
[2025-12-20T14:18:42.969Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:18:43.294Z] Top recommended movies for user id 72:
[2025-12-20T14:18:43.294Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:18:43.294Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:18:43.294Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:18:43.294Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:18:43.294Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:18:43.294Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17069.123 ms) ======
[2025-12-20T14:18:43.294Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-20T14:18:43.294Z] GC before operation: completed in 168.163 ms, heap usage 288.275 MB -> 88.530 MB.
[2025-12-20T14:18:46.272Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:18:49.290Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:18:52.232Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:18:54.478Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:18:56.155Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:18:57.853Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:18:59.201Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:19:00.948Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:19:01.280Z] 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.
[2025-12-20T14:19:01.280Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:19:01.280Z] Top recommended movies for user id 72:
[2025-12-20T14:19:01.280Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:19:01.280Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:19:01.280Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:19:01.280Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:19:01.280Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:19:01.280Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17999.290 ms) ======
[2025-12-20T14:19:01.280Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-20T14:19:01.618Z] GC before operation: completed in 165.772 ms, heap usage 135.265 MB -> 88.600 MB.
[2025-12-20T14:19:04.627Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:19:06.906Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:19:09.891Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:19:12.192Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:19:14.492Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:19:16.170Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:19:17.827Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:19:19.474Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:19:19.801Z] 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.
[2025-12-20T14:19:19.801Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:19:19.801Z] Top recommended movies for user id 72:
[2025-12-20T14:19:19.801Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:19:19.801Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:19:19.801Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:19:19.801Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:19:19.801Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:19:19.801Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18283.138 ms) ======
[2025-12-20T14:19:19.801Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-20T14:19:20.132Z] GC before operation: completed in 172.240 ms, heap usage 290.553 MB -> 88.838 MB.
[2025-12-20T14:19:22.374Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:19:24.612Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:19:26.864Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:19:29.125Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:19:30.772Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:19:31.962Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:19:33.621Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:19:34.788Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:19:35.186Z] 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.
[2025-12-20T14:19:35.186Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:19:35.513Z] Top recommended movies for user id 72:
[2025-12-20T14:19:35.513Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:19:35.513Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:19:35.513Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:19:35.513Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:19:35.513Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:19:35.513Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15393.744 ms) ======
[2025-12-20T14:19:35.513Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-20T14:19:35.513Z] GC before operation: completed in 165.388 ms, heap usage 149.608 MB -> 88.920 MB.
[2025-12-20T14:19:38.454Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:19:40.698Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:19:43.019Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:19:45.281Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:19:46.421Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:19:48.077Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:19:49.237Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:19:50.892Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:19:50.893Z] 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.
[2025-12-20T14:19:50.893Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:19:51.226Z] Top recommended movies for user id 72:
[2025-12-20T14:19:51.226Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:19:51.226Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:19:51.226Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:19:51.226Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:19:51.226Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:19:51.226Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15613.027 ms) ======
[2025-12-20T14:19:51.226Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-20T14:19:51.226Z] GC before operation: completed in 169.299 ms, heap usage 415.662 MB -> 89.172 MB.
[2025-12-20T14:19:54.188Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:19:56.432Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:19:59.379Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:20:01.621Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:20:03.275Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:20:04.488Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:20:06.730Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:20:07.879Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:20:08.205Z] 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.
[2025-12-20T14:20:08.205Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:20:08.531Z] Top recommended movies for user id 72:
[2025-12-20T14:20:08.531Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:20:08.531Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:20:08.531Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:20:08.531Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:20:08.531Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:20:08.531Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17208.953 ms) ======
[2025-12-20T14:20:08.531Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-20T14:20:08.531Z] GC before operation: completed in 160.257 ms, heap usage 247.089 MB -> 89.096 MB.
[2025-12-20T14:20:11.474Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:20:13.779Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:20:16.042Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:20:18.338Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:20:19.485Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:20:21.143Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:20:22.791Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:20:23.995Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:20:23.995Z] 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.
[2025-12-20T14:20:23.995Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:20:24.336Z] Top recommended movies for user id 72:
[2025-12-20T14:20:24.336Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:20:24.336Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:20:24.336Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:20:24.336Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:20:24.336Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:20:24.336Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15492.082 ms) ======
[2025-12-20T14:20:24.336Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-20T14:20:24.336Z] GC before operation: completed in 177.034 ms, heap usage 656.424 MB -> 92.924 MB.
[2025-12-20T14:20:27.272Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:20:29.514Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:20:31.767Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:20:34.002Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:20:35.197Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:20:36.849Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:20:37.993Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:20:39.640Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:20:39.640Z] 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.
[2025-12-20T14:20:39.640Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:20:39.990Z] Top recommended movies for user id 72:
[2025-12-20T14:20:39.990Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:20:39.990Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:20:39.990Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:20:39.990Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:20:39.990Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:20:39.990Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15495.123 ms) ======
[2025-12-20T14:20:39.990Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-20T14:20:39.990Z] GC before operation: completed in 162.403 ms, heap usage 436.507 MB -> 89.429 MB.
[2025-12-20T14:20:42.238Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:20:44.479Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:20:46.814Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:20:49.054Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:20:50.208Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:20:51.851Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:20:53.494Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:20:54.638Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:20:54.963Z] 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.
[2025-12-20T14:20:54.963Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:20:54.963Z] Top recommended movies for user id 72:
[2025-12-20T14:20:54.963Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:20:54.963Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:20:54.963Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:20:54.963Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:20:54.963Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:20:54.963Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14958.939 ms) ======
[2025-12-20T14:20:54.963Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-20T14:20:55.288Z] GC before operation: completed in 167.064 ms, heap usage 308.373 MB -> 89.308 MB.
[2025-12-20T14:20:57.533Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:20:59.782Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:21:02.737Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:21:04.436Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:21:06.101Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:21:07.327Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:21:09.043Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:21:10.184Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:21:10.512Z] 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.
[2025-12-20T14:21:10.512Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:21:10.903Z] Top recommended movies for user id 72:
[2025-12-20T14:21:10.903Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:21:10.903Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:21:10.903Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:21:10.903Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:21:10.903Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:21:10.903Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15566.979 ms) ======
[2025-12-20T14:21:10.903Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-20T14:21:10.903Z] GC before operation: completed in 158.438 ms, heap usage 204.941 MB -> 88.923 MB.
[2025-12-20T14:21:13.142Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:21:15.393Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:21:17.646Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:21:19.902Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:21:21.057Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:21:22.208Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:21:23.917Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:21:25.055Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:21:25.055Z] 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.
[2025-12-20T14:21:25.055Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:21:25.380Z] Top recommended movies for user id 72:
[2025-12-20T14:21:25.380Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:21:25.380Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:21:25.380Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:21:25.380Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:21:25.380Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:21:25.380Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14455.533 ms) ======
[2025-12-20T14:21:25.380Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-20T14:21:25.380Z] GC before operation: completed in 169.725 ms, heap usage 213.997 MB -> 89.196 MB.
[2025-12-20T14:21:27.707Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:21:29.949Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:21:32.195Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:21:34.431Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:21:35.572Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:21:37.215Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:21:38.859Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:21:40.000Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:21:40.000Z] 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.
[2025-12-20T14:21:40.000Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:21:40.331Z] Top recommended movies for user id 72:
[2025-12-20T14:21:40.331Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:21:40.331Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:21:40.331Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:21:40.331Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:21:40.331Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:21:40.331Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14699.133 ms) ======
[2025-12-20T14:21:40.331Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-20T14:21:40.331Z] GC before operation: completed in 167.320 ms, heap usage 310.021 MB -> 89.204 MB.
[2025-12-20T14:21:42.583Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:21:44.821Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:21:47.060Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:21:49.298Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:21:50.486Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:21:52.131Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:21:53.269Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:21:54.915Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:21:54.915Z] 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.
[2025-12-20T14:21:54.915Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:21:54.915Z] Top recommended movies for user id 72:
[2025-12-20T14:21:54.915Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:21:54.915Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:21:54.915Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:21:54.915Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:21:54.915Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:21:54.915Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14695.129 ms) ======
[2025-12-20T14:21:54.915Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-20T14:21:55.243Z] GC before operation: completed in 161.179 ms, heap usage 309.378 MB -> 89.416 MB.
[2025-12-20T14:21:57.485Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:21:59.766Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:22:02.026Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:22:04.336Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:22:05.501Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:22:06.649Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:22:08.303Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:22:09.445Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:22:09.445Z] 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.
[2025-12-20T14:22:09.445Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:22:09.803Z] Top recommended movies for user id 72:
[2025-12-20T14:22:09.803Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:22:09.803Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:22:09.803Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:22:09.803Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:22:09.803Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:22:09.803Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14474.125 ms) ======
[2025-12-20T14:22:09.803Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-20T14:22:09.803Z] GC before operation: completed in 159.256 ms, heap usage 206.281 MB -> 88.999 MB.
[2025-12-20T14:22:12.087Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:22:14.363Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:22:17.313Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:22:18.970Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:22:20.162Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:22:21.325Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:22:22.991Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:22:24.146Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:22:24.476Z] 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.
[2025-12-20T14:22:24.476Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:22:24.808Z] Top recommended movies for user id 72:
[2025-12-20T14:22:24.808Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:22:24.808Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:22:24.808Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:22:24.808Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:22:24.808Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:22:24.808Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14798.373 ms) ======
[2025-12-20T14:22:24.808Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-20T14:22:24.808Z] GC before operation: completed in 174.141 ms, heap usage 715.559 MB -> 93.563 MB.
[2025-12-20T14:22:27.054Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-20T14:22:29.316Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-20T14:22:31.652Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-20T14:22:33.896Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-20T14:22:35.032Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-20T14:22:36.169Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-20T14:22:37.813Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-20T14:22:38.952Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-20T14:22:38.952Z] 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.
[2025-12-20T14:22:38.952Z] The best model improves the baseline by 14.34%.
[2025-12-20T14:22:39.285Z] Top recommended movies for user id 72:
[2025-12-20T14:22:39.285Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-20T14:22:39.285Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-20T14:22:39.285Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-20T14:22:39.285Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-20T14:22:39.285Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-20T14:22:39.285Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14313.647 ms) ======
[2025-12-20T14:22:39.612Z] -----------------------------------
[2025-12-20T14:22:39.612Z] renaissance-movie-lens_0_PASSED
[2025-12-20T14:22:39.612Z] -----------------------------------
[2025-12-20T14:22:39.612Z]
[2025-12-20T14:22:39.612Z] TEST TEARDOWN:
[2025-12-20T14:22:39.612Z] Nothing to be done for teardown.
[2025-12-20T14:22:39.612Z] renaissance-movie-lens_0 Finish Time: Sat Dec 20 14:22:39 2025 Epoch Time (ms): 1766240559341