renaissance-movie-lens_0
[2025-11-27T00:04:19.577Z] Running test renaissance-movie-lens_0 ...
[2025-11-27T00:04:19.577Z] ===============================================
[2025-11-27T00:04:19.577Z] renaissance-movie-lens_0 Start Time: Thu Nov 27 00:04:15 2025 Epoch Time (ms): 1764201855767
[2025-11-27T00:04:19.577Z] variation: NoOptions
[2025-11-27T00:04:19.577Z] JVM_OPTIONS:
[2025-11-27T00:04:19.577Z] { \
[2025-11-27T00:04:19.577Z] echo ""; echo "TEST SETUP:"; \
[2025-11-27T00:04:19.577Z] echo "Nothing to be done for setup."; \
[2025-11-27T00:04:19.577Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1764196669606/renaissance-movie-lens_0"; \
[2025-11-27T00:04:19.577Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1764196669606/renaissance-movie-lens_0"; \
[2025-11-27T00:04:19.577Z] echo ""; echo "TESTING:"; \
[2025-11-27T00:04:19.577Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1764196669606/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-27T00:04:19.577Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1764196669606/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-27T00:04:19.577Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-27T00:04:19.577Z] echo "Nothing to be done for teardown."; \
[2025-11-27T00:04:19.577Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1764196669606/TestTargetResult";
[2025-11-27T00:04:19.577Z]
[2025-11-27T00:04:19.577Z] TEST SETUP:
[2025-11-27T00:04:19.577Z] Nothing to be done for setup.
[2025-11-27T00:04:19.577Z]
[2025-11-27T00:04:19.577Z] TESTING:
[2025-11-27T00:04:42.560Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-27T00:05:16.074Z] 00:05:10.740 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.
[2025-11-27T00:05:20.820Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-27T00:05:23.778Z] Training: 60056, validation: 20285, test: 19854
[2025-11-27T00:05:23.778Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-27T00:05:24.111Z] GC before operation: completed in 567.185 ms, heap usage 260.959 MB -> 76.217 MB.
[2025-11-27T00:05:51.857Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:06:07.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:06:20.852Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:06:33.936Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:06:41.181Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:06:48.408Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:06:54.308Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:07:01.625Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:07:01.625Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:07:02.333Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:07:03.035Z] Top recommended movies for user id 72:
[2025-11-27T00:07:03.035Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:07:03.035Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:07:03.035Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:07:03.035Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:07:03.035Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:07:03.035Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (99060.883 ms) ======
[2025-11-27T00:07:03.035Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-27T00:07:04.218Z] GC before operation: completed in 1093.739 ms, heap usage 284.520 MB -> 88.170 MB.
[2025-11-27T00:07:17.299Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:07:28.089Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:07:38.851Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:07:47.794Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:07:55.037Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:08:00.901Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:08:08.167Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:08:15.456Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:08:15.781Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:08:15.781Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:08:16.920Z] Top recommended movies for user id 72:
[2025-11-27T00:08:16.920Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:08:16.920Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:08:16.920Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:08:16.920Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:08:16.920Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:08:16.920Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (72505.103 ms) ======
[2025-11-27T00:08:16.920Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-27T00:08:17.630Z] GC before operation: completed in 854.244 ms, heap usage 302.891 MB -> 89.032 MB.
[2025-11-27T00:08:28.611Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:08:39.372Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:08:50.139Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:08:58.997Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:09:04.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:09:09.802Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:09:15.674Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:09:21.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:09:22.660Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:09:22.987Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:09:23.684Z] Top recommended movies for user id 72:
[2025-11-27T00:09:23.684Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:09:23.684Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:09:23.684Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:09:23.684Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:09:23.684Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:09:23.684Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (66041.406 ms) ======
[2025-11-27T00:09:23.684Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-27T00:09:24.403Z] GC before operation: completed in 818.133 ms, heap usage 143.357 MB -> 89.497 MB.
[2025-11-27T00:09:35.182Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:09:44.057Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:09:53.024Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:10:01.914Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:10:06.645Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:10:12.515Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:10:18.373Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:10:24.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:10:24.240Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:10:24.240Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:10:24.985Z] Top recommended movies for user id 72:
[2025-11-27T00:10:24.985Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:10:24.985Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:10:24.985Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:10:24.985Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:10:24.985Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:10:24.985Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60646.436 ms) ======
[2025-11-27T00:10:24.985Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-27T00:10:26.239Z] GC before operation: completed in 967.055 ms, heap usage 944.774 MB -> 94.673 MB.
[2025-11-27T00:10:37.026Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:10:45.861Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:10:54.701Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:11:03.594Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:11:08.336Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:11:14.285Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:11:18.997Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:11:24.849Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:11:25.548Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:11:25.872Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:11:26.570Z] Top recommended movies for user id 72:
[2025-11-27T00:11:26.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:11:26.570Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:11:26.570Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:11:26.570Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:11:26.570Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:11:26.570Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60434.344 ms) ======
[2025-11-27T00:11:26.570Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-27T00:11:27.374Z] GC before operation: completed in 898.083 ms, heap usage 276.797 MB -> 89.984 MB.
[2025-11-27T00:11:38.190Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:11:45.467Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:11:54.434Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:12:03.262Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:12:07.981Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:12:13.861Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:12:19.715Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:12:25.595Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:12:26.294Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:12:26.294Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:12:27.110Z] Top recommended movies for user id 72:
[2025-11-27T00:12:27.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:12:27.110Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:12:27.110Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:12:27.110Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:12:27.110Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:12:27.110Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (59633.404 ms) ======
[2025-11-27T00:12:27.110Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-27T00:12:27.827Z] GC before operation: completed in 838.514 ms, heap usage 183.973 MB -> 90.202 MB.
[2025-11-27T00:12:38.587Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:12:47.417Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:12:56.284Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:13:05.133Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:13:09.866Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:13:15.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:13:21.743Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:13:26.456Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:13:27.588Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:13:27.588Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:13:28.289Z] Top recommended movies for user id 72:
[2025-11-27T00:13:28.289Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:13:28.289Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:13:28.289Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:13:28.289Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:13:28.289Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:13:28.289Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (60296.946 ms) ======
[2025-11-27T00:13:28.289Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-27T00:13:29.009Z] GC before operation: completed in 857.215 ms, heap usage 401.525 MB -> 90.393 MB.
[2025-11-27T00:13:37.919Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:13:46.813Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:13:57.593Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:14:04.630Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:14:09.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:14:15.231Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:14:21.149Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:14:26.998Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:14:26.998Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:14:27.321Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:14:28.173Z] Top recommended movies for user id 72:
[2025-11-27T00:14:28.173Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:14:28.173Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:14:28.173Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:14:28.173Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:14:28.173Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:14:28.173Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (58769.106 ms) ======
[2025-11-27T00:14:28.173Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-27T00:14:28.898Z] GC before operation: completed in 878.872 ms, heap usage 513.283 MB -> 90.800 MB.
[2025-11-27T00:14:37.730Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:14:46.639Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:14:53.845Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:15:02.693Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:15:07.423Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:15:12.244Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:15:18.097Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:15:22.839Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:15:23.171Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:15:23.502Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:15:24.213Z] Top recommended movies for user id 72:
[2025-11-27T00:15:24.213Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:15:24.213Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:15:24.213Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:15:24.213Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:15:24.213Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:15:24.213Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55463.333 ms) ======
[2025-11-27T00:15:24.213Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-27T00:15:24.926Z] GC before operation: completed in 860.082 ms, heap usage 279.868 MB -> 90.422 MB.
[2025-11-27T00:15:33.903Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:15:41.446Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:15:50.632Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:15:57.875Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:16:02.661Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:16:08.591Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:16:13.339Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:16:18.053Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:16:18.378Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:16:18.702Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:16:19.397Z] Top recommended movies for user id 72:
[2025-11-27T00:16:19.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:16:19.397Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:16:19.397Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:16:19.397Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:16:19.397Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:16:19.397Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54317.348 ms) ======
[2025-11-27T00:16:19.397Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-27T00:16:20.100Z] GC before operation: completed in 890.000 ms, heap usage 686.192 MB -> 94.303 MB.
[2025-11-27T00:16:29.033Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:16:37.917Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:16:45.137Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:16:53.991Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:16:57.765Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:17:03.730Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:17:08.549Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:17:13.265Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:17:13.971Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:17:13.971Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:17:14.677Z] Top recommended movies for user id 72:
[2025-11-27T00:17:14.677Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:17:14.677Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:17:14.677Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:17:14.677Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:17:14.677Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:17:14.677Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54415.626 ms) ======
[2025-11-27T00:17:14.677Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-27T00:17:15.410Z] GC before operation: completed in 866.730 ms, heap usage 275.261 MB -> 90.270 MB.
[2025-11-27T00:17:24.300Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:17:32.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:17:40.997Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:17:49.946Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:17:55.079Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:17:59.801Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:18:04.581Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:18:10.518Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:18:10.847Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:18:11.180Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:18:11.893Z] Top recommended movies for user id 72:
[2025-11-27T00:18:11.893Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:18:11.894Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:18:11.894Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:18:11.894Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:18:11.894Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:18:11.894Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (56239.740 ms) ======
[2025-11-27T00:18:11.894Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-27T00:18:12.641Z] GC before operation: completed in 842.385 ms, heap usage 118.822 MB -> 90.271 MB.
[2025-11-27T00:18:25.148Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:18:29.979Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:18:38.886Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:18:47.718Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:18:52.535Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:18:58.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:19:04.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:19:10.434Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:19:10.434Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:19:10.758Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:19:11.089Z] Top recommended movies for user id 72:
[2025-11-27T00:19:11.089Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:19:11.089Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:19:11.089Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:19:11.089Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:19:11.089Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:19:11.089Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (58596.971 ms) ======
[2025-11-27T00:19:11.089Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-27T00:19:12.254Z] GC before operation: completed in 840.816 ms, heap usage 506.946 MB -> 90.895 MB.
[2025-11-27T00:19:21.108Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:19:29.936Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:19:38.773Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:19:47.612Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:19:53.716Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:19:58.455Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:20:04.491Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:20:09.256Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:20:10.384Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:20:10.384Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:20:11.091Z] Top recommended movies for user id 72:
[2025-11-27T00:20:11.091Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:20:11.091Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:20:11.091Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:20:11.091Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:20:11.091Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:20:11.091Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (58950.430 ms) ======
[2025-11-27T00:20:11.091Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-27T00:20:11.810Z] GC before operation: completed in 843.864 ms, heap usage 185.851 MB -> 90.396 MB.
[2025-11-27T00:20:20.771Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:20:29.681Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:20:36.911Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:20:45.743Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:20:49.480Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:20:54.194Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:20:58.921Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:21:04.815Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:21:04.815Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:21:05.145Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:21:05.475Z] Top recommended movies for user id 72:
[2025-11-27T00:21:05.475Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:21:05.475Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:21:05.475Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:21:05.475Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:21:05.475Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:21:05.475Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53762.880 ms) ======
[2025-11-27T00:21:05.475Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-27T00:21:06.627Z] GC before operation: completed in 887.131 ms, heap usage 440.771 MB -> 90.893 MB.
[2025-11-27T00:21:15.456Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:21:24.306Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:21:31.511Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:21:40.349Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:21:45.230Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:21:49.942Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:21:55.798Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:22:01.652Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:22:01.976Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:22:01.976Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:22:02.677Z] Top recommended movies for user id 72:
[2025-11-27T00:22:02.677Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:22:02.677Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:22:02.677Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:22:02.677Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:22:02.677Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:22:02.677Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (56190.760 ms) ======
[2025-11-27T00:22:02.677Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-27T00:22:03.401Z] GC before operation: completed in 843.270 ms, heap usage 170.165 MB -> 90.401 MB.
[2025-11-27T00:22:12.238Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:22:21.350Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:22:30.179Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:22:37.384Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:22:43.270Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:22:49.159Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:22:53.859Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:22:59.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:23:00.197Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:23:00.524Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:23:01.227Z] Top recommended movies for user id 72:
[2025-11-27T00:23:01.227Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:23:01.227Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:23:01.227Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:23:01.227Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:23:01.227Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:23:01.227Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (57655.951 ms) ======
[2025-11-27T00:23:01.227Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-27T00:23:01.944Z] GC before operation: completed in 856.034 ms, heap usage 299.147 MB -> 90.635 MB.
[2025-11-27T00:23:12.722Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:23:19.972Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:23:28.888Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:23:37.736Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:23:42.536Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:23:48.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:23:53.138Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:23:58.991Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:23:59.314Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:23:59.314Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:24:00.015Z] Top recommended movies for user id 72:
[2025-11-27T00:24:00.015Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:24:00.015Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:24:00.015Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:24:00.015Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:24:00.015Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:24:00.015Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (57961.597 ms) ======
[2025-11-27T00:24:00.015Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-27T00:24:00.720Z] GC before operation: completed in 867.700 ms, heap usage 582.525 MB -> 94.011 MB.
[2025-11-27T00:24:11.514Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:24:18.917Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:24:27.773Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:24:34.989Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:24:40.851Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:24:45.563Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:24:51.418Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:24:56.157Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:24:56.481Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:24:56.804Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:24:57.133Z] Top recommended movies for user id 72:
[2025-11-27T00:24:57.133Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:24:57.133Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:24:57.133Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:24:57.133Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:24:57.133Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:24:57.133Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (56402.090 ms) ======
[2025-11-27T00:24:57.133Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-27T00:24:58.324Z] GC before operation: completed in 917.472 ms, heap usage 873.271 MB -> 95.047 MB.
[2025-11-27T00:25:07.168Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T00:25:14.393Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T00:25:23.234Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T00:25:30.453Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T00:25:35.499Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T00:25:40.286Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T00:25:45.027Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T00:25:50.882Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T00:25:50.882Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T00:25:50.882Z] The best model improves the baseline by 14.52%.
[2025-11-27T00:25:51.580Z] Top recommended movies for user id 72:
[2025-11-27T00:25:51.580Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T00:25:51.580Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T00:25:51.580Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T00:25:51.580Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T00:25:51.580Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T00:25:51.580Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53396.367 ms) ======
[2025-11-27T00:25:55.338Z] -----------------------------------
[2025-11-27T00:25:55.338Z] renaissance-movie-lens_0_PASSED
[2025-11-27T00:25:55.338Z] -----------------------------------
[2025-11-27T00:25:55.338Z]
[2025-11-27T00:25:55.338Z] TEST TEARDOWN:
[2025-11-27T00:25:55.338Z] Nothing to be done for teardown.
[2025-11-27T00:25:55.338Z] renaissance-movie-lens_0 Finish Time: Thu Nov 27 00:25:55 2025 Epoch Time (ms): 1764203155105