renaissance-movie-lens_0
[2025-11-27T17:55:14.443Z] Running test renaissance-movie-lens_0 ...
[2025-11-27T17:55:14.443Z] ===============================================
[2025-11-27T17:55:14.443Z] renaissance-movie-lens_0 Start Time: Thu Nov 27 17:55:14 2025 Epoch Time (ms): 1764266114239
[2025-11-27T17:55:14.443Z] variation: NoOptions
[2025-11-27T17:55:14.443Z] JVM_OPTIONS:
[2025-11-27T17:55:14.443Z] { \
[2025-11-27T17:55:14.443Z] echo ""; echo "TEST SETUP:"; \
[2025-11-27T17:55:14.443Z] echo "Nothing to be done for setup."; \
[2025-11-27T17:55:14.443Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17642606825143/renaissance-movie-lens_0"; \
[2025-11-27T17:55:14.443Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17642606825143/renaissance-movie-lens_0"; \
[2025-11-27T17:55:14.443Z] echo ""; echo "TESTING:"; \
[2025-11-27T17:55:14.443Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17642606825143/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-27T17:55:14.443Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17642606825143/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-27T17:55:14.443Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-27T17:55:14.443Z] echo "Nothing to be done for teardown."; \
[2025-11-27T17:55:14.443Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17642606825143/TestTargetResult";
[2025-11-27T17:55:14.443Z]
[2025-11-27T17:55:14.443Z] TEST SETUP:
[2025-11-27T17:55:14.443Z] Nothing to be done for setup.
[2025-11-27T17:55:14.443Z]
[2025-11-27T17:55:14.443Z] TESTING:
[2025-11-27T17:55:37.549Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-27T17:56:10.839Z] 17:56:09.898 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-27T17:56:21.616Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-27T17:56:23.854Z] Training: 60056, validation: 20285, test: 19854
[2025-11-27T17:56:23.854Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-27T17:56:24.182Z] GC before operation: completed in 566.699 ms, heap usage 776.366 MB -> 77.218 MB.
[2025-11-27T17:56:57.537Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T17:57:10.660Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T17:57:25.201Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T17:57:36.266Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T17:57:44.808Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T17:57:50.407Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T17:57:57.344Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T17:58:03.303Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T17:58:04.957Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T17:58:04.957Z] The best model improves the baseline by 14.52%.
[2025-11-27T17:58:06.182Z] Top recommended movies for user id 72:
[2025-11-27T17:58:06.182Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T17:58:06.182Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T17:58:06.182Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T17:58:06.182Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T17:58:06.182Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T17:58:06.182Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (101858.872 ms) ======
[2025-11-27T17:58:06.182Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-27T17:58:06.910Z] GC before operation: completed in 880.637 ms, heap usage 498.085 MB -> 89.733 MB.
[2025-11-27T17:58:20.021Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T17:58:30.856Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T17:58:41.717Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T17:58:50.590Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T17:58:57.840Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T17:59:03.754Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T17:59:09.751Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T17:59:15.639Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T17:59:15.966Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T17:59:16.292Z] The best model improves the baseline by 14.52%.
[2025-11-27T17:59:17.011Z] Top recommended movies for user id 72:
[2025-11-27T17:59:17.011Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T17:59:17.011Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T17:59:17.011Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T17:59:17.011Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T17:59:17.011Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T17:59:17.011Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (70068.678 ms) ======
[2025-11-27T17:59:17.011Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-27T17:59:18.209Z] GC before operation: completed in 917.737 ms, heap usage 479.198 MB -> 90.020 MB.
[2025-11-27T17:59:28.993Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T17:59:37.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T17:59:48.657Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T17:59:57.599Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:00:02.423Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:00:08.728Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:00:13.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:00:19.742Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:00:20.922Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:00:20.922Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:00:21.619Z] Top recommended movies for user id 72:
[2025-11-27T18:00:21.619Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:00:21.619Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:00:21.619Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:00:21.619Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:00:21.619Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:00:21.619Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63568.155 ms) ======
[2025-11-27T18:00:21.619Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-27T18:00:22.774Z] GC before operation: completed in 959.441 ms, heap usage 293.475 MB -> 90.669 MB.
[2025-11-27T18:00:33.550Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:00:42.438Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:00:51.262Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:01:00.086Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:01:04.805Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:01:10.664Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:01:16.538Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:01:21.269Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:01:21.970Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:01:22.294Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:01:23.067Z] Top recommended movies for user id 72:
[2025-11-27T18:01:23.067Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:01:23.067Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:01:23.067Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:01:23.067Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:01:23.067Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:01:23.067Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60321.203 ms) ======
[2025-11-27T18:01:23.067Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-27T18:01:23.797Z] GC before operation: completed in 964.857 ms, heap usage 692.595 MB -> 94.568 MB.
[2025-11-27T18:01:34.565Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:01:45.351Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:01:56.137Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:02:06.914Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:02:12.783Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:02:18.693Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:02:24.791Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:02:30.650Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:02:31.348Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:02:31.348Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:02:32.052Z] Top recommended movies for user id 72:
[2025-11-27T18:02:32.052Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:02:32.052Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:02:32.052Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:02:32.052Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:02:32.052Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:02:32.052Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (68339.208 ms) ======
[2025-11-27T18:02:32.052Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-27T18:02:33.232Z] GC before operation: completed in 943.698 ms, heap usage 229.706 MB -> 94.232 MB.
[2025-11-27T18:02:44.011Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:02:51.238Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:03:00.081Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:03:08.931Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:03:13.659Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:03:18.380Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:03:24.248Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:03:28.981Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:03:30.131Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:03:30.131Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:03:30.833Z] Top recommended movies for user id 72:
[2025-11-27T18:03:30.833Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:03:30.833Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:03:30.833Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:03:30.833Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:03:30.833Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:03:30.833Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57768.575 ms) ======
[2025-11-27T18:03:30.833Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-27T18:03:31.988Z] GC before operation: completed in 960.252 ms, heap usage 442.434 MB -> 91.333 MB.
[2025-11-27T18:03:40.849Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:03:49.709Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:03:56.943Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:04:05.792Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:04:09.539Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:04:15.409Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:04:20.132Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:04:24.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:04:26.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:04:26.008Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:04:26.706Z] Top recommended movies for user id 72:
[2025-11-27T18:04:26.706Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:04:26.706Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:04:26.706Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:04:26.706Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:04:26.706Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:04:26.706Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (54861.495 ms) ======
[2025-11-27T18:04:26.706Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-27T18:04:27.870Z] GC before operation: completed in 966.406 ms, heap usage 367.870 MB -> 91.164 MB.
[2025-11-27T18:04:37.122Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:04:45.976Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:04:54.804Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:05:02.094Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:05:06.832Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:05:11.560Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:05:16.283Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:05:21.006Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:05:22.141Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:05:22.141Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:05:22.840Z] Top recommended movies for user id 72:
[2025-11-27T18:05:22.840Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:05:22.840Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:05:22.840Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:05:22.840Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:05:22.840Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:05:22.840Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55106.591 ms) ======
[2025-11-27T18:05:22.840Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-27T18:05:23.993Z] GC before operation: completed in 979.887 ms, heap usage 959.480 MB -> 95.969 MB.
[2025-11-27T18:05:32.847Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:05:41.689Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:05:48.944Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:05:56.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:06:02.051Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:06:07.911Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:06:12.632Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:06:18.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:06:18.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:06:19.170Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:06:19.886Z] Top recommended movies for user id 72:
[2025-11-27T18:06:19.886Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:06:19.886Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:06:19.886Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:06:19.886Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:06:19.886Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:06:19.886Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (56017.429 ms) ======
[2025-11-27T18:06:19.886Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-27T18:06:20.624Z] GC before operation: completed in 948.049 ms, heap usage 118.039 MB -> 95.183 MB.
[2025-11-27T18:06:31.427Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:06:42.306Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:06:49.907Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:06:57.141Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:07:03.013Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:07:07.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:07:13.587Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:07:18.297Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:07:18.995Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:07:18.995Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:07:20.133Z] Top recommended movies for user id 72:
[2025-11-27T18:07:20.133Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:07:20.133Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:07:20.133Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:07:20.133Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:07:20.133Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:07:20.133Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (59211.132 ms) ======
[2025-11-27T18:07:20.133Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-27T18:07:20.847Z] GC before operation: completed in 978.991 ms, heap usage 219.344 MB -> 93.541 MB.
[2025-11-27T18:07:29.679Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:07:38.526Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:07:45.747Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:07:52.996Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:07:58.852Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:08:03.570Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:08:08.293Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:08:13.009Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:08:13.709Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:08:14.033Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:08:14.745Z] Top recommended movies for user id 72:
[2025-11-27T18:08:14.745Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:08:14.745Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:08:14.745Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:08:14.745Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:08:14.745Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:08:14.745Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (53666.242 ms) ======
[2025-11-27T18:08:14.745Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-27T18:08:15.470Z] GC before operation: completed in 980.089 ms, heap usage 550.985 MB -> 94.763 MB.
[2025-11-27T18:08:26.242Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:08:35.081Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:08:43.925Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:08:52.805Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:08:57.747Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:09:03.626Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:09:08.373Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:09:13.097Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:09:14.232Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:09:14.232Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:09:14.931Z] Top recommended movies for user id 72:
[2025-11-27T18:09:14.931Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:09:14.931Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:09:14.931Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:09:14.931Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:09:14.931Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:09:14.931Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (59492.079 ms) ======
[2025-11-27T18:09:14.931Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-27T18:09:16.107Z] GC before operation: completed in 961.886 ms, heap usage 396.130 MB -> 93.838 MB.
[2025-11-27T18:09:26.906Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:09:37.995Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:09:46.846Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:09:54.159Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:10:00.040Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:10:05.946Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:10:10.670Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:10:15.376Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:10:16.070Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:10:16.070Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:10:16.764Z] Top recommended movies for user id 72:
[2025-11-27T18:10:16.764Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:10:16.764Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:10:16.764Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:10:16.764Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:10:16.764Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:10:16.764Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (60741.001 ms) ======
[2025-11-27T18:10:16.764Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-27T18:10:17.931Z] GC before operation: completed in 995.094 ms, heap usage 767.997 MB -> 98.807 MB.
[2025-11-27T18:10:26.905Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:10:35.730Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:10:42.956Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:10:50.421Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:10:56.295Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:11:01.002Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:11:05.727Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:11:10.513Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:11:11.214Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:11:11.539Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:11:12.265Z] Top recommended movies for user id 72:
[2025-11-27T18:11:12.265Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:11:12.265Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:11:12.265Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:11:12.265Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:11:12.265Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:11:12.265Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (54310.524 ms) ======
[2025-11-27T18:11:12.265Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-27T18:11:12.993Z] GC before operation: completed in 962.647 ms, heap usage 559.063 MB -> 94.850 MB.
[2025-11-27T18:11:21.863Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:11:30.721Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:11:37.950Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:11:46.805Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:11:50.562Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:11:55.400Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:12:01.269Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:12:05.974Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:12:06.301Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:12:06.301Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:12:06.998Z] Top recommended movies for user id 72:
[2025-11-27T18:12:06.998Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:12:06.998Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:12:06.998Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:12:06.998Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:12:06.998Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:12:06.998Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53984.333 ms) ======
[2025-11-27T18:12:06.998Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-27T18:12:08.182Z] GC before operation: completed in 956.241 ms, heap usage 271.044 MB -> 91.487 MB.
[2025-11-27T18:12:17.011Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:12:24.239Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:12:33.091Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:12:40.425Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:12:45.176Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:12:49.935Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:12:55.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:13:00.622Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:13:01.321Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:13:01.646Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:13:02.004Z] Top recommended movies for user id 72:
[2025-11-27T18:13:02.004Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:13:02.004Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:13:02.004Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:13:02.004Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:13:02.004Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:13:02.004Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54126.776 ms) ======
[2025-11-27T18:13:02.004Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-27T18:13:03.171Z] GC before operation: completed in 940.425 ms, heap usage 483.644 MB -> 91.664 MB.
[2025-11-27T18:13:12.016Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:13:19.331Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:13:28.243Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:13:35.513Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:13:39.280Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:13:45.136Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:13:49.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:13:54.653Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:13:55.354Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:13:55.354Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:13:56.089Z] Top recommended movies for user id 72:
[2025-11-27T18:13:56.089Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:13:56.089Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:13:56.089Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:13:56.089Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:13:56.089Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:13:56.089Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (53012.795 ms) ======
[2025-11-27T18:13:56.089Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-27T18:13:57.252Z] GC before operation: completed in 952.177 ms, heap usage 178.937 MB -> 94.707 MB.
[2025-11-27T18:14:08.184Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:14:18.975Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:14:27.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:14:36.789Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:14:41.513Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:14:46.273Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:14:53.388Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:14:56.315Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:14:57.468Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:14:57.468Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:14:58.178Z] Top recommended movies for user id 72:
[2025-11-27T18:14:58.178Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:14:58.178Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:14:58.178Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:14:58.178Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:14:58.178Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:14:58.178Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (61303.154 ms) ======
[2025-11-27T18:14:58.178Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-27T18:14:59.361Z] GC before operation: completed in 1023.454 ms, heap usage 883.666 MB -> 98.946 MB.
[2025-11-27T18:15:08.222Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:15:15.483Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:15:24.418Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:15:31.637Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:15:36.383Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:15:41.095Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:15:46.963Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:15:51.671Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:15:51.995Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:15:52.319Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:15:53.023Z] Top recommended movies for user id 72:
[2025-11-27T18:15:53.023Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:15:53.024Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:15:53.024Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:15:53.024Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:15:53.024Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:15:53.024Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53538.706 ms) ======
[2025-11-27T18:15:53.024Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-27T18:15:53.758Z] GC before operation: completed in 970.654 ms, heap usage 751.212 MB -> 97.632 MB.
[2025-11-27T18:16:02.610Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T18:16:09.840Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T18:16:19.029Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T18:16:26.269Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T18:16:30.992Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T18:16:35.719Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T18:16:40.453Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T18:16:46.332Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T18:16:46.658Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T18:16:46.658Z] The best model improves the baseline by 14.52%.
[2025-11-27T18:16:47.802Z] Top recommended movies for user id 72:
[2025-11-27T18:16:47.802Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T18:16:47.802Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T18:16:47.802Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T18:16:47.802Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T18:16:47.802Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T18:16:47.802Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53751.582 ms) ======
[2025-11-27T18:16:51.551Z] -----------------------------------
[2025-11-27T18:16:51.551Z] renaissance-movie-lens_0_PASSED
[2025-11-27T18:16:51.551Z] -----------------------------------
[2025-11-27T18:16:51.551Z]
[2025-11-27T18:16:51.551Z] TEST TEARDOWN:
[2025-11-27T18:16:51.551Z] Nothing to be done for teardown.
[2025-11-27T18:16:51.551Z] renaissance-movie-lens_0 Finish Time: Thu Nov 27 18:16:50 2025 Epoch Time (ms): 1764267410886