renaissance-movie-lens_0
[2025-06-12T22:58:50.107Z] Running test renaissance-movie-lens_0 ...
[2025-06-12T22:58:50.107Z] ===============================================
[2025-06-12T22:58:50.107Z] renaissance-movie-lens_0 Start Time: Thu Jun 12 22:58:49 2025 Epoch Time (ms): 1749769129726
[2025-06-12T22:58:50.107Z] variation: NoOptions
[2025-06-12T22:58:50.107Z] JVM_OPTIONS:
[2025-06-12T22:58:50.107Z] { \
[2025-06-12T22:58:50.107Z] echo ""; echo "TEST SETUP:"; \
[2025-06-12T22:58:50.107Z] echo "Nothing to be done for setup."; \
[2025-06-12T22:58:50.107Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17497671083486/renaissance-movie-lens_0"; \
[2025-06-12T22:58:50.107Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17497671083486/renaissance-movie-lens_0"; \
[2025-06-12T22:58:50.107Z] echo ""; echo "TESTING:"; \
[2025-06-12T22:58:50.107Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-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_aarch64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17497671083486/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-06-12T22:58:50.107Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17497671083486/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-06-12T22:58:50.107Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-06-12T22:58:50.107Z] echo "Nothing to be done for teardown."; \
[2025-06-12T22:58:50.107Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17497671083486/TestTargetResult";
[2025-06-12T22:58:50.107Z]
[2025-06-12T22:58:50.107Z] TEST SETUP:
[2025-06-12T22:58:50.107Z] Nothing to be done for setup.
[2025-06-12T22:58:50.107Z]
[2025-06-12T22:58:50.107Z] TESTING:
[2025-06-12T22:58:50.875Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-06-12T22:58:50.875Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/output_17497671083486/renaissance-movie-lens_0/launcher-225849-12761231719634751050/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-06-12T22:58:50.875Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-06-12T22:58:50.875Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-06-12T22:59:00.746Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-06-12T22:59:17.490Z] 22:59:15.340 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.
[2025-06-12T22:59:22.089Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-06-12T22:59:23.688Z] Training: 60056, validation: 20285, test: 19854
[2025-06-12T22:59:23.688Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-06-12T22:59:23.688Z] GC before operation: completed in 314.380 ms, heap usage 264.800 MB -> 75.599 MB.
[2025-06-12T22:59:37.645Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T22:59:47.710Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T22:59:53.419Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T22:59:58.148Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:00:00.621Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:00:04.118Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:00:06.597Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:00:10.007Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:00:10.007Z] 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.
[2025-06-12T23:00:10.007Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:00:10.819Z] Top recommended movies for user id 72:
[2025-06-12T23:00:10.819Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:00:10.820Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:00:10.820Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:00:10.820Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:00:10.820Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:00:10.820Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (46834.094 ms) ======
[2025-06-12T23:00:10.820Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-06-12T23:00:10.820Z] GC before operation: completed in 379.441 ms, heap usage 313.934 MB -> 95.639 MB.
[2025-06-12T23:00:15.432Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:00:19.874Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:00:23.333Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:00:27.808Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:00:29.390Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:00:32.799Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:00:34.382Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:00:36.474Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:00:37.239Z] 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.
[2025-06-12T23:00:37.239Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:00:37.239Z] Top recommended movies for user id 72:
[2025-06-12T23:00:37.239Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:00:37.239Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:00:37.239Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:00:37.239Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:00:37.239Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:00:37.239Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (26400.558 ms) ======
[2025-06-12T23:00:37.239Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-06-12T23:00:38.034Z] GC before operation: completed in 320.391 ms, heap usage 414.994 MB -> 87.975 MB.
[2025-06-12T23:00:42.542Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:00:45.048Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:00:50.146Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:00:52.607Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:00:54.209Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:00:56.669Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:00:58.255Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:01:00.717Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:01:00.717Z] 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.
[2025-06-12T23:01:00.717Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:01:01.489Z] Top recommended movies for user id 72:
[2025-06-12T23:01:01.489Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:01:01.489Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:01:01.489Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:01:01.489Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:01:01.489Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:01:01.489Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23529.748 ms) ======
[2025-06-12T23:01:01.489Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-06-12T23:01:01.489Z] GC before operation: completed in 286.332 ms, heap usage 222.418 MB -> 88.270 MB.
[2025-06-12T23:01:04.902Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:01:08.312Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:01:12.761Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:01:15.223Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:01:16.808Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:01:19.271Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:01:21.263Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:01:22.852Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:01:23.621Z] 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.
[2025-06-12T23:01:23.621Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:01:23.621Z] Top recommended movies for user id 72:
[2025-06-12T23:01:23.621Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:01:23.621Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:01:23.621Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:01:23.621Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:01:23.621Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:01:23.621Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22140.544 ms) ======
[2025-06-12T23:01:23.621Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-06-12T23:01:23.621Z] GC before operation: completed in 284.716 ms, heap usage 384.590 MB -> 88.877 MB.
[2025-06-12T23:01:28.156Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:01:30.646Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:01:34.056Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:01:37.474Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:01:39.059Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:01:41.523Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:01:43.982Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:01:45.569Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:01:46.341Z] 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.
[2025-06-12T23:01:46.341Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:01:46.341Z] Top recommended movies for user id 72:
[2025-06-12T23:01:46.341Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:01:46.341Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:01:46.341Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:01:46.341Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:01:46.341Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:01:46.341Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22347.873 ms) ======
[2025-06-12T23:01:46.341Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-06-12T23:01:46.341Z] GC before operation: completed in 302.437 ms, heap usage 347.728 MB -> 88.738 MB.
[2025-06-12T23:01:49.767Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:01:53.177Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:01:56.582Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:01:59.246Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:02:01.736Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:02:03.317Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:02:04.936Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:02:06.631Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:02:07.398Z] 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.
[2025-06-12T23:02:07.398Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:02:07.398Z] Top recommended movies for user id 72:
[2025-06-12T23:02:07.398Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:02:07.398Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:02:07.398Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:02:07.398Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:02:07.398Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:02:07.398Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20981.199 ms) ======
[2025-06-12T23:02:07.398Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-06-12T23:02:08.168Z] GC before operation: completed in 290.566 ms, heap usage 153.004 MB -> 88.735 MB.
[2025-06-12T23:02:11.585Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:02:14.047Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:02:17.456Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:02:19.940Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:02:22.499Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:02:24.086Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:02:25.668Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:02:27.250Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:02:28.018Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-12T23:02:28.018Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:02:28.018Z] Top recommended movies for user id 72:
[2025-06-12T23:02:28.018Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:02:28.018Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:02:28.018Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:02:28.018Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:02:28.018Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:02:28.018Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20049.755 ms) ======
[2025-06-12T23:02:28.018Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-06-12T23:02:28.018Z] GC before operation: completed in 282.203 ms, heap usage 497.784 MB -> 92.466 MB.
[2025-06-12T23:02:31.431Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:02:34.842Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:02:37.954Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:02:40.423Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:02:42.010Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:02:43.605Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:02:46.111Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:02:47.694Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:02:48.460Z] 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.
[2025-06-12T23:02:48.460Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:02:48.460Z] Top recommended movies for user id 72:
[2025-06-12T23:02:48.460Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:02:48.460Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:02:48.460Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:02:48.460Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:02:48.460Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:02:48.460Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20309.068 ms) ======
[2025-06-12T23:02:48.460Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-06-12T23:02:48.460Z] GC before operation: completed in 309.712 ms, heap usage 160.339 MB -> 88.983 MB.
[2025-06-12T23:02:51.874Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:02:55.287Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:02:58.709Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:03:01.166Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:03:02.750Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:03:05.237Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:03:06.821Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:03:08.405Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:03:08.405Z] 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.
[2025-06-12T23:03:08.405Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:03:09.171Z] Top recommended movies for user id 72:
[2025-06-12T23:03:09.171Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:03:09.171Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:03:09.171Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:03:09.171Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:03:09.171Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:03:09.171Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20111.883 ms) ======
[2025-06-12T23:03:09.171Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-06-12T23:03:09.171Z] GC before operation: completed in 243.007 ms, heap usage 171.796 MB -> 88.862 MB.
[2025-06-12T23:03:12.579Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:03:15.037Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:03:17.498Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:03:20.467Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:03:22.049Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:03:23.633Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:03:26.115Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:03:27.694Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:03:27.694Z] 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.
[2025-06-12T23:03:27.694Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:03:27.694Z] Top recommended movies for user id 72:
[2025-06-12T23:03:27.694Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:03:27.694Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:03:27.694Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:03:27.694Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:03:27.694Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:03:27.694Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18713.843 ms) ======
[2025-06-12T23:03:27.694Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-06-12T23:03:27.694Z] GC before operation: completed in 224.552 ms, heap usage 165.373 MB -> 89.002 MB.
[2025-06-12T23:03:31.103Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:03:33.571Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:03:37.001Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:03:39.489Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:03:41.089Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:03:42.689Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:03:45.169Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:03:46.754Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:03:47.549Z] 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.
[2025-06-12T23:03:47.549Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:03:47.549Z] Top recommended movies for user id 72:
[2025-06-12T23:03:47.549Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:03:47.549Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:03:47.549Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:03:47.549Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:03:47.549Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:03:47.549Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19288.719 ms) ======
[2025-06-12T23:03:47.549Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-06-12T23:03:47.549Z] GC before operation: completed in 220.103 ms, heap usage 638.638 MB -> 92.940 MB.
[2025-06-12T23:03:50.969Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:03:53.448Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:03:57.362Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:03:58.943Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:04:01.423Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:04:03.005Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:04:04.587Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:04:06.189Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:04:06.189Z] 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.
[2025-06-12T23:04:06.189Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:04:06.958Z] Top recommended movies for user id 72:
[2025-06-12T23:04:06.958Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:04:06.958Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:04:06.958Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:04:06.958Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:04:06.958Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:04:06.958Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19110.862 ms) ======
[2025-06-12T23:04:06.958Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-06-12T23:04:06.958Z] GC before operation: completed in 225.707 ms, heap usage 219.064 MB -> 89.006 MB.
[2025-06-12T23:04:10.367Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:04:12.848Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:04:15.315Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:04:18.725Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:04:20.308Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:04:22.011Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:04:23.594Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:04:25.176Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:04:25.176Z] 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.
[2025-06-12T23:04:25.176Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:04:25.947Z] Top recommended movies for user id 72:
[2025-06-12T23:04:25.947Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:04:25.947Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:04:25.947Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:04:25.947Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:04:25.947Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:04:25.947Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18724.714 ms) ======
[2025-06-12T23:04:25.947Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-06-12T23:04:25.947Z] GC before operation: completed in 242.746 ms, heap usage 430.185 MB -> 89.529 MB.
[2025-06-12T23:04:29.447Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:04:31.926Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:04:35.331Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:04:37.425Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:04:39.896Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:04:41.478Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:04:43.951Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:04:45.541Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:04:45.541Z] 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.
[2025-06-12T23:04:45.541Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:04:45.541Z] Top recommended movies for user id 72:
[2025-06-12T23:04:45.541Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:04:45.541Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:04:45.541Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:04:45.541Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:04:45.541Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:04:45.541Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19800.309 ms) ======
[2025-06-12T23:04:45.541Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-06-12T23:04:45.541Z] GC before operation: completed in 217.251 ms, heap usage 302.548 MB -> 89.129 MB.
[2025-06-12T23:04:48.974Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:04:51.506Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:04:53.966Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:04:57.378Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:04:58.960Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:05:00.544Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:05:02.135Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:05:03.725Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:05:03.725Z] 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.
[2025-06-12T23:05:03.725Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:05:03.725Z] Top recommended movies for user id 72:
[2025-06-12T23:05:03.725Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:05:03.725Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:05:03.725Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:05:03.725Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:05:03.725Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:05:03.725Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18100.276 ms) ======
[2025-06-12T23:05:03.725Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-06-12T23:05:04.490Z] GC before operation: completed in 216.532 ms, heap usage 352.806 MB -> 89.444 MB.
[2025-06-12T23:05:06.948Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:05:10.370Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:05:12.840Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:05:15.435Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:05:17.022Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:05:18.874Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:05:20.459Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:05:22.101Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:05:22.891Z] 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.
[2025-06-12T23:05:22.891Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:05:22.891Z] Top recommended movies for user id 72:
[2025-06-12T23:05:22.891Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:05:22.891Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:05:22.891Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:05:22.891Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:05:22.891Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:05:22.891Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18610.902 ms) ======
[2025-06-12T23:05:22.891Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-06-12T23:05:22.891Z] GC before operation: completed in 227.442 ms, heap usage 435.258 MB -> 92.579 MB.
[2025-06-12T23:05:26.305Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:05:28.769Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:05:32.208Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:05:34.668Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:05:36.254Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:05:37.839Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:05:39.437Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:05:41.020Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:05:41.020Z] 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.
[2025-06-12T23:05:41.020Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:05:41.020Z] Top recommended movies for user id 72:
[2025-06-12T23:05:41.020Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:05:41.020Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:05:41.020Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:05:41.020Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:05:41.020Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:05:41.020Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18241.467 ms) ======
[2025-06-12T23:05:41.020Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-06-12T23:05:41.787Z] GC before operation: completed in 212.666 ms, heap usage 148.108 MB -> 89.033 MB.
[2025-06-12T23:05:44.244Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:05:47.649Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:05:50.109Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:05:52.578Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:05:54.161Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:05:56.257Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:05:57.842Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:05:59.433Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:05:59.433Z] 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.
[2025-06-12T23:05:59.433Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:06:00.227Z] Top recommended movies for user id 72:
[2025-06-12T23:06:00.227Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:06:00.227Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:06:00.227Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:06:00.227Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:06:00.227Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:06:00.227Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18482.726 ms) ======
[2025-06-12T23:06:00.227Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-06-12T23:06:00.227Z] GC before operation: completed in 205.609 ms, heap usage 248.214 MB -> 89.105 MB.
[2025-06-12T23:06:03.641Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:06:06.103Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:06:08.570Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:06:11.029Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:06:13.521Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:06:15.102Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:06:16.685Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:06:18.272Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:06:18.272Z] 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.
[2025-06-12T23:06:18.272Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:06:18.272Z] Top recommended movies for user id 72:
[2025-06-12T23:06:18.272Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:06:18.272Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:06:18.272Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:06:18.272Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:06:18.272Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:06:18.272Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18300.456 ms) ======
[2025-06-12T23:06:18.272Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-06-12T23:06:19.040Z] GC before operation: completed in 214.598 ms, heap usage 405.661 MB -> 89.477 MB.
[2025-06-12T23:06:21.555Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T23:06:24.017Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T23:06:27.426Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T23:06:29.888Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T23:06:31.470Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T23:06:33.052Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T23:06:35.147Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T23:06:36.730Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T23:06:36.730Z] 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.
[2025-06-12T23:06:36.730Z] The best model improves the baseline by 14.34%.
[2025-06-12T23:06:36.730Z] Top recommended movies for user id 72:
[2025-06-12T23:06:36.730Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-12T23:06:36.730Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-12T23:06:36.730Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-12T23:06:36.730Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-12T23:06:36.730Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-12T23:06:36.730Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18193.813 ms) ======
[2025-06-12T23:06:38.348Z] -----------------------------------
[2025-06-12T23:06:38.348Z] renaissance-movie-lens_0_PASSED
[2025-06-12T23:06:38.348Z] -----------------------------------
[2025-06-12T23:06:38.348Z]
[2025-06-12T23:06:38.348Z] TEST TEARDOWN:
[2025-06-12T23:06:38.348Z] Nothing to be done for teardown.
[2025-06-12T23:06:38.348Z] renaissance-movie-lens_0 Finish Time: Thu Jun 12 23:06:37 2025 Epoch Time (ms): 1749769597705