renaissance-movie-lens_0
[2026-01-21T10:24:42.919Z] Running test renaissance-movie-lens_0 ...
[2026-01-21T10:24:42.919Z] ===============================================
[2026-01-21T10:24:42.919Z] renaissance-movie-lens_0 Start Time: Wed Jan 21 10:24:42 2026 Epoch Time (ms): 1768991082027
[2026-01-21T10:24:42.919Z] variation: NoOptions
[2026-01-21T10:24:42.919Z] JVM_OPTIONS:
[2026-01-21T10:24:42.919Z] { \
[2026-01-21T10:24:42.919Z] echo ""; echo "TEST SETUP:"; \
[2026-01-21T10:24:42.919Z] echo "Nothing to be done for setup."; \
[2026-01-21T10:24:42.919Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17689880455839/renaissance-movie-lens_0"; \
[2026-01-21T10:24:42.919Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17689880455839/renaissance-movie-lens_0"; \
[2026-01-21T10:24:42.919Z] echo ""; echo "TESTING:"; \
[2026-01-21T10:24:42.919Z] "/home/jenkins/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17689880455839/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2026-01-21T10:24:42.919Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17689880455839/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2026-01-21T10:24:42.919Z] echo ""; echo "TEST TEARDOWN:"; \
[2026-01-21T10:24:42.919Z] echo "Nothing to be done for teardown."; \
[2026-01-21T10:24:42.919Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17689880455839/TestTargetResult";
[2026-01-21T10:24:42.919Z]
[2026-01-21T10:24:42.919Z] TEST SETUP:
[2026-01-21T10:24:42.919Z] Nothing to be done for setup.
[2026-01-21T10:24:42.919Z]
[2026-01-21T10:24:42.919Z] TESTING:
[2026-01-21T10:25:05.992Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2026-01-21T10:25:39.377Z] 10:25:36.485 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2026-01-21T10:25:48.287Z] Got 100004 ratings from 671 users on 9066 movies.
[2026-01-21T10:25:49.443Z] Training: 60056, validation: 20285, test: 19854
[2026-01-21T10:25:49.443Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2026-01-21T10:25:50.203Z] GC before operation: completed in 673.193 ms, heap usage 278.002 MB -> 76.101 MB.
[2026-01-21T10:26:18.117Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:26:34.079Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:26:47.220Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:27:00.377Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:27:07.774Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:27:15.287Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:27:24.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:27:30.118Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:27:31.791Z] 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.
[2026-01-21T10:27:31.791Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:27:32.961Z] Top recommended movies for user id 72:
[2026-01-21T10:27:32.961Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:27:32.961Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:27:32.961Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:27:32.961Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:27:32.961Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:27:32.961Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (102843.642 ms) ======
[2026-01-21T10:27:32.961Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2026-01-21T10:27:34.146Z] GC before operation: completed in 855.428 ms, heap usage 98.223 MB -> 88.097 MB.
[2026-01-21T10:27:47.298Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:27:58.263Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:28:09.107Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:28:19.945Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:28:25.874Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:28:31.881Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:28:39.164Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:28:45.081Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:28:46.361Z] 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.
[2026-01-21T10:28:46.693Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:28:47.404Z] Top recommended movies for user id 72:
[2026-01-21T10:28:47.404Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:28:47.404Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:28:47.404Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:28:47.404Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:28:47.404Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:28:47.404Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (73411.313 ms) ======
[2026-01-21T10:28:47.404Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2026-01-21T10:28:48.120Z] GC before operation: completed in 897.473 ms, heap usage 517.191 MB -> 89.327 MB.
[2026-01-21T10:28:59.022Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:29:09.872Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:29:20.742Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:29:29.654Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:29:35.629Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:29:41.591Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:29:48.868Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:29:53.631Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:29:54.794Z] 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.
[2026-01-21T10:29:54.794Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:29:55.501Z] Top recommended movies for user id 72:
[2026-01-21T10:29:55.501Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:29:55.501Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:29:55.837Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:29:55.837Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:29:55.837Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:29:55.837Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (67479.370 ms) ======
[2026-01-21T10:29:55.837Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2026-01-21T10:29:56.558Z] GC before operation: completed in 925.667 ms, heap usage 371.405 MB -> 89.724 MB.
[2026-01-21T10:30:07.473Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:30:16.366Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:30:25.272Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:30:34.378Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:30:41.663Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:30:47.576Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:30:53.481Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:30:59.402Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:31:00.114Z] 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.
[2026-01-21T10:31:00.114Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:31:01.276Z] Top recommended movies for user id 72:
[2026-01-21T10:31:01.276Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:31:01.276Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:31:01.276Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:31:01.276Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:31:01.276Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:31:01.276Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (64424.536 ms) ======
[2026-01-21T10:31:01.276Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2026-01-21T10:31:02.008Z] GC before operation: completed in 899.146 ms, heap usage 265.517 MB -> 89.964 MB.
[2026-01-21T10:31:13.010Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:31:20.290Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:31:31.125Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:31:38.431Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:31:44.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:31:50.288Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:31:55.053Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:32:01.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:32:01.383Z] 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.
[2026-01-21T10:32:01.383Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:32:02.106Z] Top recommended movies for user id 72:
[2026-01-21T10:32:02.106Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:32:02.106Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:32:02.106Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:32:02.106Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:32:02.106Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:32:02.106Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60059.038 ms) ======
[2026-01-21T10:32:02.106Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2026-01-21T10:32:02.851Z] GC before operation: completed in 986.745 ms, heap usage 364.638 MB -> 90.032 MB.
[2026-01-21T10:32:13.714Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:32:21.013Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:32:29.928Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:32:37.245Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:32:43.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:32:47.978Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:32:52.838Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:32:58.763Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:32:58.763Z] 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.
[2026-01-21T10:32:59.095Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:32:59.823Z] Top recommended movies for user id 72:
[2026-01-21T10:32:59.823Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:32:59.823Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:32:59.823Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:32:59.823Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:32:59.823Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:32:59.823Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (56681.484 ms) ======
[2026-01-21T10:32:59.823Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2026-01-21T10:33:00.556Z] GC before operation: completed in 960.171 ms, heap usage 542.402 MB -> 93.827 MB.
[2026-01-21T10:33:09.467Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:33:18.366Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:33:27.286Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:33:34.838Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:33:39.608Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:33:44.381Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:33:50.298Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:33:55.065Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:33:55.398Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-01-21T10:33:55.728Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:33:56.447Z] Top recommended movies for user id 72:
[2026-01-21T10:33:56.447Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:33:56.447Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:33:56.447Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:33:56.447Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:33:56.447Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:33:56.447Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55650.090 ms) ======
[2026-01-21T10:33:56.447Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2026-01-21T10:33:57.173Z] GC before operation: completed in 951.282 ms, heap usage 288.208 MB -> 90.243 MB.
[2026-01-21T10:34:06.076Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:34:15.179Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:34:24.082Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:34:31.378Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:34:37.334Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:34:42.137Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:34:48.098Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:34:54.020Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:34:54.727Z] 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.
[2026-01-21T10:34:54.727Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:34:55.451Z] Top recommended movies for user id 72:
[2026-01-21T10:34:55.451Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:34:55.451Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:34:55.451Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:34:55.451Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:34:55.451Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:34:55.451Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (58096.832 ms) ======
[2026-01-21T10:34:55.451Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2026-01-21T10:34:56.189Z] GC before operation: completed in 924.975 ms, heap usage 369.931 MB -> 90.709 MB.
[2026-01-21T10:35:07.021Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:35:14.321Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:35:23.246Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:35:32.163Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:35:36.944Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:35:42.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:35:48.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:35:53.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:35:54.332Z] 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.
[2026-01-21T10:35:54.668Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:35:55.398Z] Top recommended movies for user id 72:
[2026-01-21T10:35:55.398Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:35:55.398Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:35:55.398Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:35:55.398Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:35:55.398Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:35:55.398Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (59016.251 ms) ======
[2026-01-21T10:35:55.398Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2026-01-21T10:35:56.136Z] GC before operation: completed in 901.476 ms, heap usage 388.892 MB -> 90.516 MB.
[2026-01-21T10:36:05.094Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:36:14.021Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:36:22.929Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:36:32.037Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:36:36.812Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:36:42.719Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:36:47.507Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:36:53.430Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:36:54.145Z] 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.
[2026-01-21T10:36:54.477Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:36:54.805Z] Top recommended movies for user id 72:
[2026-01-21T10:36:54.805Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:36:54.805Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:36:54.805Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:36:54.805Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:36:54.805Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:36:54.805Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (58760.693 ms) ======
[2026-01-21T10:36:54.805Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2026-01-21T10:36:55.996Z] GC before operation: completed in 925.531 ms, heap usage 404.861 MB -> 90.776 MB.
[2026-01-21T10:37:04.940Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:37:14.119Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:37:23.039Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:37:30.314Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:37:36.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:37:41.092Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:37:45.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:37:51.790Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:37:51.790Z] 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.
[2026-01-21T10:37:51.790Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:37:52.501Z] Top recommended movies for user id 72:
[2026-01-21T10:37:52.501Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:37:52.501Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:37:52.501Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:37:52.501Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:37:52.501Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:37:52.501Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (56625.077 ms) ======
[2026-01-21T10:37:52.501Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2026-01-21T10:37:53.264Z] GC before operation: completed in 928.285 ms, heap usage 266.258 MB -> 90.363 MB.
[2026-01-21T10:38:02.344Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:38:11.244Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:38:18.521Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:38:25.802Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:38:30.581Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:38:36.513Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:38:41.288Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:38:46.050Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:38:46.758Z] 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.
[2026-01-21T10:38:46.758Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:38:47.473Z] Top recommended movies for user id 72:
[2026-01-21T10:38:47.473Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:38:47.473Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:38:47.473Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:38:47.473Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:38:47.473Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:38:47.473Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53998.807 ms) ======
[2026-01-21T10:38:47.473Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2026-01-21T10:38:48.208Z] GC before operation: completed in 945.863 ms, heap usage 524.619 MB -> 90.795 MB.
[2026-01-21T10:38:57.119Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:39:06.012Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:39:13.419Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:39:22.318Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:39:26.105Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:39:32.237Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:39:37.000Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:39:42.925Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:39:43.295Z] 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.
[2026-01-21T10:39:43.295Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:39:44.017Z] Top recommended movies for user id 72:
[2026-01-21T10:39:44.017Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:39:44.017Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:39:44.017Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:39:44.017Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:39:44.017Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:39:44.017Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55534.005 ms) ======
[2026-01-21T10:39:44.017Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2026-01-21T10:39:44.748Z] GC before operation: completed in 946.195 ms, heap usage 492.132 MB -> 90.903 MB.
[2026-01-21T10:39:53.633Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:40:02.531Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:40:11.438Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:40:18.856Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:40:23.624Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:40:29.553Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:40:34.309Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:40:39.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:40:39.786Z] 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.
[2026-01-21T10:40:39.786Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:40:40.523Z] Top recommended movies for user id 72:
[2026-01-21T10:40:40.523Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:40:40.523Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:40:40.523Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:40:40.523Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:40:40.523Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:40:40.523Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (55567.311 ms) ======
[2026-01-21T10:40:40.523Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2026-01-21T10:40:41.265Z] GC before operation: completed in 935.101 ms, heap usage 267.126 MB -> 90.388 MB.
[2026-01-21T10:40:50.169Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:40:57.693Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:41:06.604Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:41:13.884Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:41:18.651Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:41:23.421Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:41:28.186Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:41:32.958Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:41:34.123Z] 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.
[2026-01-21T10:41:34.123Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:41:34.891Z] Top recommended movies for user id 72:
[2026-01-21T10:41:34.892Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:41:34.892Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:41:34.892Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:41:34.892Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:41:34.892Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:41:34.892Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53535.088 ms) ======
[2026-01-21T10:41:34.892Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2026-01-21T10:41:36.078Z] GC before operation: completed in 990.239 ms, heap usage 232.633 MB -> 90.574 MB.
[2026-01-21T10:41:44.993Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:41:52.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:42:01.262Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:42:08.549Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:42:13.320Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:42:18.096Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:42:24.210Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:42:28.976Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:42:29.306Z] 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.
[2026-01-21T10:42:29.306Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:42:30.033Z] Top recommended movies for user id 72:
[2026-01-21T10:42:30.033Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:42:30.033Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:42:30.033Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:42:30.033Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:42:30.033Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:42:30.033Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54019.867 ms) ======
[2026-01-21T10:42:30.033Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2026-01-21T10:42:30.768Z] GC before operation: completed in 947.021 ms, heap usage 487.573 MB -> 90.886 MB.
[2026-01-21T10:42:39.677Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:42:46.958Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:42:55.870Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:43:03.147Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:43:07.983Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:43:12.734Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:43:17.556Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:43:22.328Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:43:23.041Z] 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.
[2026-01-21T10:43:23.374Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:43:24.092Z] Top recommended movies for user id 72:
[2026-01-21T10:43:24.092Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:43:24.092Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:43:24.092Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:43:24.092Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:43:24.092Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:43:24.092Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (53187.577 ms) ======
[2026-01-21T10:43:24.092Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2026-01-21T10:43:24.830Z] GC before operation: completed in 937.090 ms, heap usage 168.341 MB -> 90.430 MB.
[2026-01-21T10:43:33.744Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:43:43.012Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:43:50.299Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:43:59.229Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:44:03.996Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:44:08.789Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:44:14.775Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:44:19.698Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:44:20.848Z] 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.
[2026-01-21T10:44:20.848Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:44:21.557Z] Top recommended movies for user id 72:
[2026-01-21T10:44:21.557Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:44:21.557Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:44:21.557Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:44:21.557Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:44:21.557Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:44:21.557Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (56525.550 ms) ======
[2026-01-21T10:44:21.557Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2026-01-21T10:44:22.294Z] GC before operation: completed in 938.240 ms, heap usage 489.671 MB -> 90.725 MB.
[2026-01-21T10:44:31.208Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:44:40.102Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:44:49.006Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:44:56.420Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:45:01.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:45:06.071Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:45:10.866Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:45:15.640Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:45:16.787Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-01-21T10:45:16.787Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:45:17.500Z] Top recommended movies for user id 72:
[2026-01-21T10:45:17.501Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:45:17.501Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:45:17.501Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:45:17.501Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:45:17.501Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:45:17.501Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (55012.370 ms) ======
[2026-01-21T10:45:17.501Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2026-01-21T10:45:18.685Z] GC before operation: completed in 991.987 ms, heap usage 893.348 MB -> 94.999 MB.
[2026-01-21T10:45:27.588Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-01-21T10:45:35.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-01-21T10:45:44.103Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-01-21T10:45:51.394Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-01-21T10:45:55.201Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-01-21T10:45:59.980Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-01-21T10:46:05.900Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-01-21T10:46:09.767Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-01-21T10:46:10.918Z] 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.
[2026-01-21T10:46:10.918Z] The best model improves the baseline by 14.52%.
[2026-01-21T10:46:11.625Z] Top recommended movies for user id 72:
[2026-01-21T10:46:11.625Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-01-21T10:46:11.625Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-01-21T10:46:11.625Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-01-21T10:46:11.625Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-01-21T10:46:11.625Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-01-21T10:46:11.625Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53202.917 ms) ======
[2026-01-21T10:46:15.406Z] -----------------------------------
[2026-01-21T10:46:15.406Z] renaissance-movie-lens_0_PASSED
[2026-01-21T10:46:15.406Z] -----------------------------------
[2026-01-21T10:46:15.406Z]
[2026-01-21T10:46:15.406Z] TEST TEARDOWN:
[2026-01-21T10:46:15.406Z] Nothing to be done for teardown.
[2026-01-21T10:46:15.406Z] renaissance-movie-lens_0 Finish Time: Wed Jan 21 10:46:14 2026 Epoch Time (ms): 1768992374856