renaissance-movie-lens_0
[2025-12-04T02:04:26.672Z] Running test renaissance-movie-lens_0 ...
[2025-12-04T02:04:26.672Z] ===============================================
[2025-12-04T02:04:26.672Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 02:04:26 2025 Epoch Time (ms): 1764813866580
[2025-12-04T02:04:26.672Z] variation: NoOptions
[2025-12-04T02:04:26.672Z] JVM_OPTIONS:
[2025-12-04T02:04:26.672Z] { \
[2025-12-04T02:04:26.672Z] echo ""; echo "TEST SETUP:"; \
[2025-12-04T02:04:26.672Z] echo "Nothing to be done for setup."; \
[2025-12-04T02:04:26.672Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17648122137108/renaissance-movie-lens_0"; \
[2025-12-04T02:04:26.672Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17648122137108/renaissance-movie-lens_0"; \
[2025-12-04T02:04:26.672Z] echo ""; echo "TESTING:"; \
[2025-12-04T02:04:26.672Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/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_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17648122137108/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-04T02:04:26.672Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17648122137108/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-04T02:04:26.672Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-04T02:04:26.672Z] echo "Nothing to be done for teardown."; \
[2025-12-04T02:04:26.672Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17648122137108/TestTargetResult";
[2025-12-04T02:04:26.672Z]
[2025-12-04T02:04:26.672Z] TEST SETUP:
[2025-12-04T02:04:26.672Z] Nothing to be done for setup.
[2025-12-04T02:04:26.672Z]
[2025-12-04T02:04:26.672Z] TESTING:
[2025-12-04T02:04:32.429Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-12-04T02:04:41.141Z] 02:04:40.214 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-04T02:04:43.386Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-04T02:04:44.486Z] Training: 60056, validation: 20285, test: 19854
[2025-12-04T02:04:44.486Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-04T02:04:44.486Z] GC before operation: completed in 146.298 ms, heap usage 142.448 MB -> 74.154 MB.
[2025-12-04T02:04:53.193Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:04:58.942Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:05:03.562Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:05:08.216Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:05:10.392Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:05:13.240Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:05:16.098Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:05:17.694Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:05:18.391Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:05:18.391Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:05:18.391Z] Top recommended movies for user id 72:
[2025-12-04T02:05:18.391Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:05:18.391Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:05:18.391Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:05:18.391Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:05:18.391Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:05:18.391Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33956.212 ms) ======
[2025-12-04T02:05:18.391Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-04T02:05:18.705Z] GC before operation: completed in 173.401 ms, heap usage 402.605 MB -> 84.996 MB.
[2025-12-04T02:05:23.328Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:05:26.243Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:05:31.479Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:05:33.643Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:05:35.238Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:05:37.412Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:05:39.579Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:05:41.172Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:05:41.849Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:05:41.849Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:05:41.849Z] Top recommended movies for user id 72:
[2025-12-04T02:05:41.849Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:05:41.849Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:05:41.849Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:05:41.849Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:05:41.849Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:05:41.849Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23201.205 ms) ======
[2025-12-04T02:05:41.849Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-04T02:05:42.160Z] GC before operation: completed in 165.890 ms, heap usage 168.918 MB -> 86.420 MB.
[2025-12-04T02:05:45.819Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:05:48.674Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:05:52.336Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:05:55.182Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:05:56.769Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:05:58.953Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:06:01.123Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:06:03.379Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:06:03.379Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:06:03.379Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:06:03.379Z] Top recommended movies for user id 72:
[2025-12-04T02:06:03.379Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:06:03.379Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:06:03.379Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:06:03.379Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:06:03.379Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:06:03.379Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21461.303 ms) ======
[2025-12-04T02:06:03.379Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-04T02:06:03.693Z] GC before operation: completed in 196.096 ms, heap usage 144.927 MB -> 87.018 MB.
[2025-12-04T02:06:07.359Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:06:10.212Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:06:13.890Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:06:17.545Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:06:19.129Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:06:20.717Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:06:22.946Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:06:24.539Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:06:24.947Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:06:24.947Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:06:24.947Z] Top recommended movies for user id 72:
[2025-12-04T02:06:24.947Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:06:24.947Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:06:24.947Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:06:24.947Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:06:24.947Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:06:24.947Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21300.602 ms) ======
[2025-12-04T02:06:24.947Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-04T02:06:25.258Z] GC before operation: completed in 168.399 ms, heap usage 320.437 MB -> 87.511 MB.
[2025-12-04T02:06:28.931Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:06:31.795Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:06:35.463Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:06:38.318Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:06:39.909Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:06:41.571Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:06:43.752Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:06:45.348Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:06:45.660Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:06:45.660Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:06:45.972Z] Top recommended movies for user id 72:
[2025-12-04T02:06:45.972Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:06:45.972Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:06:45.972Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:06:45.972Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:06:45.972Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:06:45.972Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20690.566 ms) ======
[2025-12-04T02:06:45.972Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-04T02:06:45.972Z] GC before operation: completed in 152.738 ms, heap usage 142.632 MB -> 87.201 MB.
[2025-12-04T02:06:49.632Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:06:52.487Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:06:55.353Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:06:58.265Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:07:00.436Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:07:02.038Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:07:04.203Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:07:05.796Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:07:06.109Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:07:06.109Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:07:06.421Z] Top recommended movies for user id 72:
[2025-12-04T02:07:06.421Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:07:06.421Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:07:06.421Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:07:06.421Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:07:06.421Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:07:06.421Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20274.321 ms) ======
[2025-12-04T02:07:06.421Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-04T02:07:06.421Z] GC before operation: completed in 150.529 ms, heap usage 116.319 MB -> 87.426 MB.
[2025-12-04T02:07:09.279Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:07:13.003Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:07:15.857Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:07:18.721Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:07:20.380Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:07:22.556Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:07:24.147Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:07:26.314Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:07:26.314Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:07:26.314Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:07:26.629Z] Top recommended movies for user id 72:
[2025-12-04T02:07:26.629Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:07:26.629Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:07:26.629Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:07:26.629Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:07:26.629Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:07:26.629Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20043.737 ms) ======
[2025-12-04T02:07:26.629Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-04T02:07:26.629Z] GC before operation: completed in 157.611 ms, heap usage 97.651 MB -> 87.278 MB.
[2025-12-04T02:07:30.302Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:07:33.147Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:07:36.066Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:07:38.919Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:07:40.507Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:07:42.682Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:07:44.273Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:07:46.450Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:07:46.450Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:07:46.450Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:07:46.770Z] Top recommended movies for user id 72:
[2025-12-04T02:07:46.770Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:07:46.770Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:07:46.770Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:07:46.770Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:07:46.770Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:07:46.770Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20130.351 ms) ======
[2025-12-04T02:07:46.770Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-04T02:07:47.082Z] GC before operation: completed in 177.180 ms, heap usage 167.971 MB -> 87.709 MB.
[2025-12-04T02:07:50.735Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:07:53.597Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:07:56.459Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:07:59.307Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:08:01.476Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:08:03.073Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:08:05.267Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:08:06.855Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:08:07.167Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:08:07.167Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:08:07.479Z] Top recommended movies for user id 72:
[2025-12-04T02:08:07.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:08:07.479Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:08:07.479Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:08:07.479Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:08:07.479Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:08:07.479Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20366.452 ms) ======
[2025-12-04T02:08:07.479Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-04T02:08:07.479Z] GC before operation: completed in 165.428 ms, heap usage 321.853 MB -> 87.834 MB.
[2025-12-04T02:08:11.159Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:08:13.328Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:08:16.190Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:08:18.357Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:08:20.527Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:08:21.624Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:08:23.220Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:08:24.810Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:08:25.123Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:08:25.123Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:08:25.123Z] Top recommended movies for user id 72:
[2025-12-04T02:08:25.123Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:08:25.123Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:08:25.123Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:08:25.123Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:08:25.123Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:08:25.123Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17730.703 ms) ======
[2025-12-04T02:08:25.123Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-04T02:08:25.436Z] GC before operation: completed in 173.575 ms, heap usage 262.873 MB -> 87.921 MB.
[2025-12-04T02:08:28.291Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:08:31.160Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:08:34.016Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:08:36.903Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:08:39.074Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:08:40.664Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:08:42.259Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:08:44.427Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:08:44.427Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:08:44.427Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:08:44.739Z] Top recommended movies for user id 72:
[2025-12-04T02:08:44.739Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:08:44.739Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:08:44.740Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:08:44.740Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:08:44.740Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:08:44.740Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19229.661 ms) ======
[2025-12-04T02:08:44.740Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-04T02:08:44.740Z] GC before operation: completed in 153.959 ms, heap usage 273.487 MB -> 87.665 MB.
[2025-12-04T02:08:47.603Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:08:49.864Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:08:52.719Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:08:54.901Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:08:56.496Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:08:58.090Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:08:59.679Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:09:01.271Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:09:01.271Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:09:01.271Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:09:01.585Z] Top recommended movies for user id 72:
[2025-12-04T02:09:01.585Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:09:01.585Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:09:01.585Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:09:01.585Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:09:01.585Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:09:01.585Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16733.657 ms) ======
[2025-12-04T02:09:01.585Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-04T02:09:01.585Z] GC before operation: completed in 168.964 ms, heap usage 281.085 MB -> 87.921 MB.
[2025-12-04T02:09:05.260Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:09:07.436Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:09:11.112Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:09:13.971Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:09:15.567Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:09:17.171Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:09:19.351Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:09:20.942Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:09:21.255Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:09:21.255Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:09:21.255Z] Top recommended movies for user id 72:
[2025-12-04T02:09:21.255Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:09:21.255Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:09:21.255Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:09:21.255Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:09:21.255Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:09:21.255Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (19605.730 ms) ======
[2025-12-04T02:09:21.255Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-04T02:09:21.566Z] GC before operation: completed in 154.516 ms, heap usage 239.492 MB -> 87.979 MB.
[2025-12-04T02:09:24.417Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:09:28.077Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:09:31.004Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:09:33.873Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:09:35.466Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:09:37.062Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:09:38.655Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:09:40.246Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:09:40.246Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:09:40.561Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:09:40.561Z] Top recommended movies for user id 72:
[2025-12-04T02:09:40.561Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:09:40.561Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:09:40.561Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:09:40.561Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:09:40.561Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:09:40.561Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19068.445 ms) ======
[2025-12-04T02:09:40.561Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-04T02:09:40.561Z] GC before operation: completed in 160.587 ms, heap usage 299.624 MB -> 87.848 MB.
[2025-12-04T02:09:43.425Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:09:45.599Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:09:48.455Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:09:50.625Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:09:52.792Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:09:54.418Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:09:56.009Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:09:57.110Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:09:57.422Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:09:57.734Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:09:57.734Z] Top recommended movies for user id 72:
[2025-12-04T02:09:57.734Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:09:57.734Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:09:57.734Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:09:57.734Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:09:57.734Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:09:57.734Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17094.577 ms) ======
[2025-12-04T02:09:57.734Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-04T02:09:58.046Z] GC before operation: completed in 165.193 ms, heap usage 422.033 MB -> 88.300 MB.
[2025-12-04T02:10:00.906Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:10:03.787Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:10:06.644Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:10:09.493Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:10:10.620Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:10:12.212Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:10:14.435Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:10:15.532Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:10:15.844Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:10:15.844Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:10:16.161Z] Top recommended movies for user id 72:
[2025-12-04T02:10:16.161Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:10:16.161Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:10:16.161Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:10:16.161Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:10:16.161Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:10:16.161Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18074.085 ms) ======
[2025-12-04T02:10:16.161Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-04T02:10:16.161Z] GC before operation: completed in 164.239 ms, heap usage 286.667 MB -> 87.877 MB.
[2025-12-04T02:10:19.012Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:10:21.869Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:10:24.718Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:10:27.605Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:10:29.193Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:10:30.790Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:10:32.957Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:10:34.548Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:10:34.548Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:10:34.548Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:10:34.861Z] Top recommended movies for user id 72:
[2025-12-04T02:10:34.861Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:10:34.861Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:10:34.861Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:10:34.861Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:10:34.861Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:10:34.861Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18657.586 ms) ======
[2025-12-04T02:10:34.861Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-04T02:10:34.861Z] GC before operation: completed in 154.422 ms, heap usage 146.723 MB -> 87.800 MB.
[2025-12-04T02:10:37.721Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:10:41.386Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:10:44.246Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:10:46.433Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:10:48.021Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:10:50.211Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:10:51.808Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:10:53.400Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:10:53.713Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:10:53.713Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:10:54.025Z] Top recommended movies for user id 72:
[2025-12-04T02:10:54.025Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:10:54.025Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:10:54.025Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:10:54.025Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:10:54.025Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:10:54.025Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19046.963 ms) ======
[2025-12-04T02:10:54.025Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-04T02:10:54.338Z] GC before operation: completed in 159.223 ms, heap usage 201.889 MB -> 87.653 MB.
[2025-12-04T02:10:57.197Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:11:00.120Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:11:02.984Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:11:05.839Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:11:07.443Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:11:09.654Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:11:11.248Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:11:13.421Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:11:13.421Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:11:13.421Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:11:13.421Z] Top recommended movies for user id 72:
[2025-12-04T02:11:13.421Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:11:13.421Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:11:13.421Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:11:13.421Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:11:13.421Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:11:13.421Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19231.929 ms) ======
[2025-12-04T02:11:13.421Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-04T02:11:13.738Z] GC before operation: completed in 156.443 ms, heap usage 215.634 MB -> 87.854 MB.
[2025-12-04T02:11:16.592Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T02:11:18.185Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T02:11:21.145Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T02:11:24.002Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T02:11:25.099Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T02:11:26.688Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T02:11:28.287Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T02:11:29.882Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T02:11:30.196Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-12-04T02:11:30.196Z] The best model improves the baseline by 14.34%.
[2025-12-04T02:11:30.196Z] Top recommended movies for user id 72:
[2025-12-04T02:11:30.196Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-12-04T02:11:30.196Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-12-04T02:11:30.196Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-12-04T02:11:30.196Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-12-04T02:11:30.196Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-12-04T02:11:30.196Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16637.457 ms) ======
[2025-12-04T02:11:30.872Z] -----------------------------------
[2025-12-04T02:11:30.872Z] renaissance-movie-lens_0_PASSED
[2025-12-04T02:11:30.872Z] -----------------------------------
[2025-12-04T02:11:30.872Z]
[2025-12-04T02:11:30.872Z] TEST TEARDOWN:
[2025-12-04T02:11:30.872Z] Nothing to be done for teardown.
[2025-12-04T02:11:30.872Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 02:11:30 2025 Epoch Time (ms): 1764814290662