renaissance-movie-lens_0
[2025-12-24T23:05:47.419Z] Running test renaissance-movie-lens_0 ...
[2025-12-24T23:05:47.419Z] ===============================================
[2025-12-24T23:05:47.419Z] renaissance-movie-lens_0 Start Time: Wed Dec 24 23:05:46 2025 Epoch Time (ms): 1766617546671
[2025-12-24T23:05:47.419Z] variation: NoOptions
[2025-12-24T23:05:47.419Z] JVM_OPTIONS:
[2025-12-24T23:05:47.419Z] { \
[2025-12-24T23:05:47.419Z] echo ""; echo "TEST SETUP:"; \
[2025-12-24T23:05:47.419Z] echo "Nothing to be done for setup."; \
[2025-12-24T23:05:47.419Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666142414256/renaissance-movie-lens_0"; \
[2025-12-24T23:05:47.419Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666142414256/renaissance-movie-lens_0"; \
[2025-12-24T23:05:47.419Z] echo ""; echo "TESTING:"; \
[2025-12-24T23:05:47.419Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666142414256/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-24T23:05:47.419Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666142414256/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-24T23:05:47.419Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-24T23:05:47.419Z] echo "Nothing to be done for teardown."; \
[2025-12-24T23:05:47.419Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17666142414256/TestTargetResult";
[2025-12-24T23:05:47.419Z]
[2025-12-24T23:05:47.419Z] TEST SETUP:
[2025-12-24T23:05:47.419Z] Nothing to be done for setup.
[2025-12-24T23:05:47.419Z]
[2025-12-24T23:05:47.419Z] TESTING:
[2025-12-24T23:05:58.965Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-24T23:06:20.220Z] 23:06:17.694 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.
[2025-12-24T23:06:22.373Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-24T23:06:23.332Z] Training: 60056, validation: 20285, test: 19854
[2025-12-24T23:06:23.332Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-24T23:06:23.332Z] GC before operation: completed in 224.572 ms, heap usage 370.000 MB -> 76.010 MB.
[2025-12-24T23:06:36.933Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:06:42.371Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:06:49.121Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:06:54.520Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:06:57.555Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:07:00.583Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:07:03.626Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:07:06.719Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:07:07.684Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:07:07.684Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:07:07.684Z] Top recommended movies for user id 72:
[2025-12-24T23:07:07.684Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:07:07.684Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:07:07.684Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:07:07.684Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:07:07.684Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:07:07.684Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (44454.760 ms) ======
[2025-12-24T23:07:07.684Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-24T23:07:07.684Z] GC before operation: completed in 216.232 ms, heap usage 459.944 MB -> 88.560 MB.
[2025-12-24T23:07:13.152Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:07:17.556Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:07:22.947Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:07:27.157Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:07:30.188Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:07:32.198Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:07:35.939Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:07:36.908Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:07:37.885Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:07:37.885Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:07:37.885Z] Top recommended movies for user id 72:
[2025-12-24T23:07:37.885Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:07:37.885Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:07:37.885Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:07:37.885Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:07:37.885Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:07:37.885Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (30060.118 ms) ======
[2025-12-24T23:07:37.885Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-24T23:07:37.885Z] GC before operation: completed in 216.310 ms, heap usage 488.770 MB -> 89.072 MB.
[2025-12-24T23:07:42.115Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:07:46.309Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:07:50.481Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:07:54.646Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:07:56.606Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:07:59.635Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:08:01.603Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:08:04.642Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:08:04.642Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:08:04.642Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:08:05.604Z] Top recommended movies for user id 72:
[2025-12-24T23:08:05.604Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:08:05.604Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:08:05.604Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:08:05.604Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:08:05.604Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:08:05.604Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (26992.898 ms) ======
[2025-12-24T23:08:05.604Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-24T23:08:05.604Z] GC before operation: completed in 193.589 ms, heap usage 106.810 MB -> 89.293 MB.
[2025-12-24T23:08:09.786Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:08:12.828Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:08:17.451Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:08:21.628Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:08:24.675Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:08:26.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:08:29.669Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:08:31.642Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:08:32.602Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:08:32.602Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:08:32.602Z] Top recommended movies for user id 72:
[2025-12-24T23:08:32.602Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:08:32.602Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:08:32.602Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:08:32.602Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:08:32.602Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:08:32.602Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (27139.938 ms) ======
[2025-12-24T23:08:32.602Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-24T23:08:32.602Z] GC before operation: completed in 240.097 ms, heap usage 174.244 MB -> 89.754 MB.
[2025-12-24T23:08:36.771Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:08:39.810Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:08:44.081Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:08:47.120Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:08:50.153Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:08:52.112Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:08:54.079Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:08:56.043Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:08:57.001Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:08:57.001Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:08:57.001Z] Top recommended movies for user id 72:
[2025-12-24T23:08:57.001Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:08:57.001Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:08:57.001Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:08:57.001Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:08:57.001Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:08:57.001Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24198.095 ms) ======
[2025-12-24T23:08:57.001Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-24T23:08:57.001Z] GC before operation: completed in 240.922 ms, heap usage 722.185 MB -> 95.114 MB.
[2025-12-24T23:09:01.943Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:09:04.993Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:09:08.038Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:09:12.259Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:09:14.334Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:09:16.413Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:09:18.380Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:09:21.426Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:09:21.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:09:21.426Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:09:22.382Z] Top recommended movies for user id 72:
[2025-12-24T23:09:22.382Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:09:22.382Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:09:22.382Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:09:22.382Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:09:22.382Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:09:22.382Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (24779.318 ms) ======
[2025-12-24T23:09:22.382Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-24T23:09:22.382Z] GC before operation: completed in 194.854 ms, heap usage 126.052 MB -> 90.902 MB.
[2025-12-24T23:09:26.550Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:09:29.746Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:09:33.968Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:09:37.008Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:09:40.054Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:09:42.029Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:09:44.074Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:09:47.135Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:09:47.135Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:09:47.135Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:09:48.539Z] Top recommended movies for user id 72:
[2025-12-24T23:09:48.539Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:09:48.539Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:09:48.539Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:09:48.539Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:09:48.539Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:09:48.539Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (25499.435 ms) ======
[2025-12-24T23:09:48.539Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-24T23:09:48.539Z] GC before operation: completed in 230.433 ms, heap usage 147.561 MB -> 89.798 MB.
[2025-12-24T23:09:52.787Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:09:57.009Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:10:00.065Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:10:04.256Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:10:06.245Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:10:09.292Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:10:12.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:10:14.290Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:10:14.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:10:14.290Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:10:15.252Z] Top recommended movies for user id 72:
[2025-12-24T23:10:15.252Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:10:15.252Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:10:15.252Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:10:15.252Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:10:15.252Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:10:15.252Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (26950.247 ms) ======
[2025-12-24T23:10:15.252Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-24T23:10:15.252Z] GC before operation: completed in 243.636 ms, heap usage 354.964 MB -> 90.346 MB.
[2025-12-24T23:10:19.453Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:10:23.889Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:10:28.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:10:32.661Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:10:34.678Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:10:37.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:10:40.170Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:10:43.205Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:10:43.205Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:10:43.205Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:10:44.193Z] Top recommended movies for user id 72:
[2025-12-24T23:10:44.193Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:10:44.193Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:10:44.193Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:10:44.193Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:10:44.193Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:10:44.193Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (28654.987 ms) ======
[2025-12-24T23:10:44.193Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-24T23:10:44.193Z] GC before operation: completed in 278.169 ms, heap usage 174.841 MB -> 89.940 MB.
[2025-12-24T23:10:48.380Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:10:51.441Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:10:55.654Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:10:59.819Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:11:01.905Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:11:04.932Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:11:06.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:11:08.906Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:11:09.912Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:11:09.912Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:11:09.912Z] Top recommended movies for user id 72:
[2025-12-24T23:11:09.912Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:11:09.912Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:11:09.912Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:11:09.912Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:11:09.912Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:11:09.912Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26008.873 ms) ======
[2025-12-24T23:11:09.912Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-24T23:11:10.875Z] GC before operation: completed in 361.798 ms, heap usage 261.365 MB -> 90.354 MB.
[2025-12-24T23:11:15.077Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:11:19.287Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:11:22.524Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:11:26.724Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:11:29.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:11:32.384Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:11:34.430Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:11:37.493Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:11:37.493Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:11:37.493Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:11:38.468Z] Top recommended movies for user id 72:
[2025-12-24T23:11:38.468Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:11:38.468Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:11:38.468Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:11:38.468Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:11:38.468Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:11:38.468Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27574.183 ms) ======
[2025-12-24T23:11:38.468Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-24T23:11:38.468Z] GC before operation: completed in 242.887 ms, heap usage 230.104 MB -> 89.948 MB.
[2025-12-24T23:11:42.648Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:11:46.950Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:11:52.341Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:11:56.515Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:11:59.626Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:12:01.669Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:12:04.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:12:07.880Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:12:07.880Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:12:07.880Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:12:07.880Z] Top recommended movies for user id 72:
[2025-12-24T23:12:07.880Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:12:07.880Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:12:07.880Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:12:07.880Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:12:07.880Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:12:07.880Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (30031.338 ms) ======
[2025-12-24T23:12:07.880Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-24T23:12:08.835Z] GC before operation: completed in 229.712 ms, heap usage 486.983 MB -> 90.615 MB.
[2025-12-24T23:12:13.131Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:12:17.941Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:12:21.484Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:12:26.065Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:12:29.096Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:12:32.130Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:12:34.331Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:12:37.540Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:12:37.540Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:12:37.540Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:12:37.540Z] Top recommended movies for user id 72:
[2025-12-24T23:12:37.540Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:12:37.540Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:12:37.540Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:12:37.540Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:12:37.540Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:12:37.540Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (29428.718 ms) ======
[2025-12-24T23:12:37.540Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-24T23:12:38.498Z] GC before operation: completed in 230.716 ms, heap usage 163.188 MB -> 90.955 MB.
[2025-12-24T23:12:43.010Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:12:47.232Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:12:51.565Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:12:57.007Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:12:59.140Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:13:02.302Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:13:05.340Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:13:08.126Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:13:09.099Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:13:09.099Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:13:09.099Z] Top recommended movies for user id 72:
[2025-12-24T23:13:09.099Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:13:09.099Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:13:09.099Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:13:09.099Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:13:09.099Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:13:09.099Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (31011.259 ms) ======
[2025-12-24T23:13:09.099Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-24T23:13:09.099Z] GC before operation: completed in 254.614 ms, heap usage 148.708 MB -> 90.003 MB.
[2025-12-24T23:13:14.515Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:13:18.920Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:13:23.116Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:13:27.290Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:13:30.329Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:13:33.374Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:13:35.356Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:13:38.478Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:13:38.478Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:13:38.478Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:13:38.478Z] Top recommended movies for user id 72:
[2025-12-24T23:13:38.478Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:13:38.478Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:13:38.478Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:13:38.478Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:13:38.478Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:13:38.478Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (29461.830 ms) ======
[2025-12-24T23:13:38.478Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-24T23:13:39.440Z] GC before operation: completed in 228.759 ms, heap usage 351.423 MB -> 90.546 MB.
[2025-12-24T23:13:43.655Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:13:47.885Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:13:52.301Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:13:56.715Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:13:58.750Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:14:01.509Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:14:04.667Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:14:06.637Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:14:07.593Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:14:07.593Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:14:07.593Z] Top recommended movies for user id 72:
[2025-12-24T23:14:07.593Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:14:07.593Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:14:07.593Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:14:07.593Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:14:07.593Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:14:07.593Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (28672.214 ms) ======
[2025-12-24T23:14:07.593Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-24T23:14:07.593Z] GC before operation: completed in 253.288 ms, heap usage 363.929 MB -> 90.422 MB.
[2025-12-24T23:14:11.762Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:14:15.998Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:14:20.184Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:14:24.369Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:14:26.355Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:14:28.316Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:14:31.354Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:14:33.322Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:14:34.282Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:14:34.282Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:14:34.282Z] Top recommended movies for user id 72:
[2025-12-24T23:14:34.282Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:14:34.282Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:14:34.282Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:14:34.282Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:14:34.282Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:14:34.282Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (26426.071 ms) ======
[2025-12-24T23:14:34.282Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-24T23:14:34.282Z] GC before operation: completed in 260.200 ms, heap usage 204.103 MB -> 90.181 MB.
[2025-12-24T23:14:39.746Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:14:42.791Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:14:47.021Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:14:50.104Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:14:52.564Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:14:55.606Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:14:58.634Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:15:00.595Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:15:00.595Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:15:00.595Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:15:01.548Z] Top recommended movies for user id 72:
[2025-12-24T23:15:01.548Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:15:01.549Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:15:01.549Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:15:01.549Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:15:01.549Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:15:01.549Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26486.051 ms) ======
[2025-12-24T23:15:01.549Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-24T23:15:01.549Z] GC before operation: completed in 236.892 ms, heap usage 496.436 MB -> 90.496 MB.
[2025-12-24T23:15:05.808Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:15:09.996Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:15:13.030Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:15:17.362Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:15:19.328Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:15:22.363Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:15:24.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:15:26.290Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:15:27.254Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:15:27.254Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:15:27.254Z] Top recommended movies for user id 72:
[2025-12-24T23:15:27.254Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:15:27.254Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:15:27.254Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:15:27.254Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:15:27.254Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:15:27.254Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (25772.066 ms) ======
[2025-12-24T23:15:27.254Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-24T23:15:27.254Z] GC before operation: completed in 230.577 ms, heap usage 454.361 MB -> 90.489 MB.
[2025-12-24T23:15:31.436Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-24T23:15:35.679Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-24T23:15:39.852Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-24T23:15:43.634Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-24T23:15:46.662Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-24T23:15:48.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-24T23:15:51.651Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-24T23:15:53.613Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-24T23:15:53.613Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-24T23:15:53.613Z] The best model improves the baseline by 14.52%.
[2025-12-24T23:15:54.570Z] Top recommended movies for user id 72:
[2025-12-24T23:15:54.571Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-24T23:15:54.571Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-24T23:15:54.571Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-24T23:15:54.571Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-24T23:15:54.571Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-24T23:15:54.571Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (26631.443 ms) ======
[2025-12-24T23:15:55.526Z] -----------------------------------
[2025-12-24T23:15:55.526Z] renaissance-movie-lens_0_PASSED
[2025-12-24T23:15:55.526Z] -----------------------------------
[2025-12-24T23:15:55.526Z]
[2025-12-24T23:15:55.526Z] TEST TEARDOWN:
[2025-12-24T23:15:55.526Z] Nothing to be done for teardown.
[2025-12-24T23:15:55.526Z] renaissance-movie-lens_0 Finish Time: Wed Dec 24 23:15:55 2025 Epoch Time (ms): 1766618155057