renaissance-movie-lens_0
[2025-09-25T02:16:06.840Z] Running test renaissance-movie-lens_0 ...
[2025-09-25T02:16:06.840Z] ===============================================
[2025-09-25T02:16:06.840Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 02:16:05 2025 Epoch Time (ms): 1758766565707
[2025-09-25T02:16:06.840Z] variation: NoOptions
[2025-09-25T02:16:06.840Z] JVM_OPTIONS:
[2025-09-25T02:16:06.840Z] { \
[2025-09-25T02:16:06.840Z] echo ""; echo "TEST SETUP:"; \
[2025-09-25T02:16:06.840Z] echo "Nothing to be done for setup."; \
[2025-09-25T02:16:06.840Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17587619244372/renaissance-movie-lens_0"; \
[2025-09-25T02:16:06.840Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17587619244372/renaissance-movie-lens_0"; \
[2025-09-25T02:16:06.840Z] echo ""; echo "TESTING:"; \
[2025-09-25T02:16:06.840Z] "/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_17587619244372/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-25T02:16:06.840Z] 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_17587619244372/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-25T02:16:06.840Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-25T02:16:06.840Z] echo "Nothing to be done for teardown."; \
[2025-09-25T02:16:06.840Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17587619244372/TestTargetResult";
[2025-09-25T02:16:06.840Z]
[2025-09-25T02:16:06.840Z] TEST SETUP:
[2025-09-25T02:16:06.840Z] Nothing to be done for setup.
[2025-09-25T02:16:06.840Z]
[2025-09-25T02:16:06.840Z] TESTING:
[2025-09-25T02:16:29.889Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-25T02:17:03.153Z] 02:17:00.598 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-25T02:17:12.046Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-25T02:17:14.292Z] Training: 60056, validation: 20285, test: 19854
[2025-09-25T02:17:14.292Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-25T02:17:14.618Z] GC before operation: completed in 593.887 ms, heap usage 435.776 MB -> 76.089 MB.
[2025-09-25T02:17:42.362Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:18:01.689Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:18:14.814Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:18:27.916Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:18:36.979Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:18:42.976Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:18:50.583Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:18:58.095Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:18:58.425Z] 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.
[2025-09-25T02:18:58.749Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:18:59.890Z] Top recommended movies for user id 72:
[2025-09-25T02:18:59.890Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:18:59.890Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:18:59.890Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:18:59.890Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:18:59.890Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:18:59.890Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (105230.479 ms) ======
[2025-09-25T02:18:59.890Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-25T02:19:00.613Z] GC before operation: completed in 905.072 ms, heap usage 379.601 MB -> 86.924 MB.
[2025-09-25T02:19:13.702Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:19:25.005Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:19:38.085Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:19:46.972Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:19:52.866Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:19:58.742Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:20:04.629Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:20:10.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:20:11.229Z] 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.
[2025-09-25T02:20:11.556Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:20:12.254Z] Top recommended movies for user id 72:
[2025-09-25T02:20:12.255Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:20:12.255Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:20:12.255Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:20:12.255Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:20:12.255Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:20:12.255Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (71435.578 ms) ======
[2025-09-25T02:20:12.255Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-25T02:20:13.413Z] GC before operation: completed in 1044.165 ms, heap usage 718.737 MB -> 92.855 MB.
[2025-09-25T02:20:24.205Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:20:35.447Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:20:44.299Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:20:53.247Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:20:59.116Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:21:04.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:21:09.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:21:15.736Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:21:16.439Z] 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.
[2025-09-25T02:21:16.768Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:21:17.467Z] Top recommended movies for user id 72:
[2025-09-25T02:21:17.467Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:21:17.467Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:21:17.467Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:21:17.467Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:21:17.467Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:21:17.467Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (64240.600 ms) ======
[2025-09-25T02:21:17.467Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-25T02:21:18.613Z] GC before operation: completed in 1106.397 ms, heap usage 991.622 MB -> 94.238 MB.
[2025-09-25T02:21:29.396Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:21:38.241Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:21:47.142Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:21:56.003Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:22:01.926Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:22:07.798Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:22:13.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:22:19.695Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:22:20.019Z] 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.
[2025-09-25T02:22:20.344Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:22:21.050Z] Top recommended movies for user id 72:
[2025-09-25T02:22:21.050Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:22:21.050Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:22:21.050Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:22:21.050Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:22:21.050Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:22:21.050Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (62435.262 ms) ======
[2025-09-25T02:22:21.050Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-25T02:22:22.206Z] GC before operation: completed in 1001.439 ms, heap usage 559.538 MB -> 90.272 MB.
[2025-09-25T02:22:32.987Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:22:41.922Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:22:50.823Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:22:59.670Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:23:04.580Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:23:10.503Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:23:16.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:23:21.120Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:23:21.830Z] 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.
[2025-09-25T02:23:22.153Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:23:22.855Z] Top recommended movies for user id 72:
[2025-09-25T02:23:22.855Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:23:22.855Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:23:22.855Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:23:22.855Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:23:22.855Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:23:22.855Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60654.108 ms) ======
[2025-09-25T02:23:22.855Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-25T02:23:23.569Z] GC before operation: completed in 1019.585 ms, heap usage 275.268 MB -> 89.873 MB.
[2025-09-25T02:23:34.360Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:23:41.587Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:23:50.430Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:23:59.388Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:24:04.108Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:24:08.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:24:14.690Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:24:19.425Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:24:19.749Z] 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.
[2025-09-25T02:24:20.074Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:24:20.778Z] Top recommended movies for user id 72:
[2025-09-25T02:24:20.778Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:24:20.778Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:24:20.778Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:24:20.778Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:24:20.778Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:24:20.778Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (56933.841 ms) ======
[2025-09-25T02:24:20.778Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-25T02:24:21.503Z] GC before operation: completed in 1011.614 ms, heap usage 641.740 MB -> 93.925 MB.
[2025-09-25T02:24:32.273Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:24:39.512Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:24:48.378Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:24:55.618Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:25:00.356Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:25:06.238Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:25:10.951Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:25:15.665Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:25:16.806Z] 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.
[2025-09-25T02:25:16.806Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:25:17.959Z] Top recommended movies for user id 72:
[2025-09-25T02:25:17.959Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:25:17.959Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:25:17.959Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:25:17.959Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:25:17.959Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:25:17.959Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56134.854 ms) ======
[2025-09-25T02:25:17.959Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-25T02:25:18.680Z] GC before operation: completed in 990.346 ms, heap usage 309.092 MB -> 90.245 MB.
[2025-09-25T02:25:27.754Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:25:36.626Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:25:45.472Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:25:54.344Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:26:00.205Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:26:06.070Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:26:10.820Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:26:16.695Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:26:17.395Z] 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.
[2025-09-25T02:26:17.723Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:26:18.455Z] Top recommended movies for user id 72:
[2025-09-25T02:26:18.455Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:26:18.455Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:26:18.455Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:26:18.455Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:26:18.455Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:26:18.455Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (59690.493 ms) ======
[2025-09-25T02:26:18.455Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-25T02:26:19.612Z] GC before operation: completed in 972.544 ms, heap usage 439.084 MB -> 90.551 MB.
[2025-09-25T02:26:30.390Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:26:37.624Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:26:46.464Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:26:55.318Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:27:01.255Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:27:07.126Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:27:11.920Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:27:17.845Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:27:18.556Z] 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.
[2025-09-25T02:27:18.556Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:27:19.257Z] Top recommended movies for user id 72:
[2025-09-25T02:27:19.257Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:27:19.257Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:27:19.257Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:27:19.257Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:27:19.257Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:27:19.257Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (59909.466 ms) ======
[2025-09-25T02:27:19.257Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-25T02:27:20.406Z] GC before operation: completed in 984.497 ms, heap usage 381.560 MB -> 90.507 MB.
[2025-09-25T02:27:29.260Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:27:38.133Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:27:45.397Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:27:54.255Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:27:59.001Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:28:03.802Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:28:09.665Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:28:14.396Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:28:14.721Z] 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.
[2025-09-25T02:28:14.721Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:28:15.427Z] Top recommended movies for user id 72:
[2025-09-25T02:28:15.427Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:28:15.427Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:28:15.427Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:28:15.427Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:28:15.427Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:28:15.427Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (55093.507 ms) ======
[2025-09-25T02:28:15.427Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-25T02:28:16.583Z] GC before operation: completed in 987.478 ms, heap usage 376.547 MB -> 90.764 MB.
[2025-09-25T02:28:25.441Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:28:32.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:28:41.542Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:28:48.786Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:28:53.676Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:28:59.605Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:29:04.321Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:29:09.290Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:29:09.991Z] 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.
[2025-09-25T02:29:09.991Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:29:10.692Z] Top recommended movies for user id 72:
[2025-09-25T02:29:10.692Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:29:10.692Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:29:10.692Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:29:10.692Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:29:10.692Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:29:10.692Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54287.143 ms) ======
[2025-09-25T02:29:10.692Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-25T02:29:11.839Z] GC before operation: completed in 1003.258 ms, heap usage 569.415 MB -> 93.948 MB.
[2025-09-25T02:29:20.677Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:29:27.926Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:29:36.765Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:29:44.122Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:29:50.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:29:54.808Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:29:59.532Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:30:04.404Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:30:05.544Z] 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.
[2025-09-25T02:30:05.544Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:30:06.240Z] Top recommended movies for user id 72:
[2025-09-25T02:30:06.240Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:30:06.240Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:30:06.240Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:30:06.240Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:30:06.240Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:30:06.240Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (54612.293 ms) ======
[2025-09-25T02:30:06.240Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-25T02:30:07.415Z] GC before operation: completed in 1004.732 ms, heap usage 389.349 MB -> 90.632 MB.
[2025-09-25T02:30:16.274Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:30:25.146Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:30:32.507Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:30:39.739Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:30:45.603Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:30:51.500Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:30:56.217Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:31:00.927Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:31:01.637Z] 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.
[2025-09-25T02:31:01.961Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:31:02.674Z] Top recommended movies for user id 72:
[2025-09-25T02:31:02.674Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:31:02.674Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:31:02.674Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:31:02.674Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:31:02.674Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:31:02.674Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55240.700 ms) ======
[2025-09-25T02:31:02.674Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-25T02:31:03.395Z] GC before operation: completed in 970.800 ms, heap usage 258.564 MB -> 90.658 MB.
[2025-09-25T02:31:12.296Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:31:21.238Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:31:30.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:31:37.327Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:31:42.055Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:31:46.770Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:31:51.492Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:31:57.385Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:31:57.385Z] 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.
[2025-09-25T02:31:57.710Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:31:58.415Z] Top recommended movies for user id 72:
[2025-09-25T02:31:58.415Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:31:58.415Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:31:58.415Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:31:58.415Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:31:58.415Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:31:58.415Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (54876.543 ms) ======
[2025-09-25T02:31:58.415Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-25T02:31:59.568Z] GC before operation: completed in 984.231 ms, heap usage 171.262 MB -> 90.521 MB.
[2025-09-25T02:32:08.579Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:32:17.437Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:32:24.668Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:32:31.894Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:32:37.760Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:32:42.479Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:32:47.191Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:32:51.945Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:32:53.086Z] 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.
[2025-09-25T02:32:53.086Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:32:53.412Z] Top recommended movies for user id 72:
[2025-09-25T02:32:53.412Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:32:53.412Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:32:53.412Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:32:53.412Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:32:53.412Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:32:53.412Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54192.636 ms) ======
[2025-09-25T02:32:53.412Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-25T02:32:54.565Z] GC before operation: completed in 1015.029 ms, heap usage 570.344 MB -> 94.350 MB.
[2025-09-25T02:33:03.429Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:33:12.282Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:33:19.504Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:33:28.355Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:33:33.078Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:33:37.830Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:33:42.645Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:33:47.361Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:33:48.495Z] 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.
[2025-09-25T02:33:48.495Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:33:49.195Z] Top recommended movies for user id 72:
[2025-09-25T02:33:49.195Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:33:49.195Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:33:49.195Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:33:49.195Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:33:49.195Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:33:49.195Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54618.542 ms) ======
[2025-09-25T02:33:49.195Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-25T02:33:50.362Z] GC before operation: completed in 988.505 ms, heap usage 391.302 MB -> 90.654 MB.
[2025-09-25T02:33:59.223Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:34:06.472Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:34:15.313Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:34:22.533Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:34:28.507Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:34:33.231Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:34:37.943Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:34:42.663Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:34:44.305Z] 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.
[2025-09-25T02:34:44.305Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:34:45.010Z] Top recommended movies for user id 72:
[2025-09-25T02:34:45.010Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:34:45.010Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:34:45.010Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:34:45.010Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:34:45.010Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:34:45.010Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (54823.043 ms) ======
[2025-09-25T02:34:45.010Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-25T02:34:46.176Z] GC before operation: completed in 969.518 ms, heap usage 154.034 MB -> 90.417 MB.
[2025-09-25T02:34:55.051Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:35:03.936Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:35:12.807Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:35:21.651Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:35:26.363Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:35:32.242Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:35:38.123Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:35:42.875Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:35:44.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-25T02:35:44.337Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:35:45.056Z] Top recommended movies for user id 72:
[2025-09-25T02:35:45.056Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:35:45.056Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:35:45.056Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:35:45.056Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:35:45.057Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:35:45.057Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (58856.436 ms) ======
[2025-09-25T02:35:45.057Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-25T02:35:45.775Z] GC before operation: completed in 972.910 ms, heap usage 363.223 MB -> 90.587 MB.
[2025-09-25T02:35:56.603Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:36:03.903Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:36:12.752Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:36:21.594Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:36:26.320Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:36:32.193Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:36:38.057Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:36:42.806Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:36:43.967Z] 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.
[2025-09-25T02:36:44.290Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:36:45.001Z] Top recommended movies for user id 72:
[2025-09-25T02:36:45.001Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:36:45.001Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:36:45.001Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:36:45.001Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:36:45.001Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:36:45.001Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (58992.638 ms) ======
[2025-09-25T02:36:45.001Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-25T02:36:45.720Z] GC before operation: completed in 962.310 ms, heap usage 225.831 MB -> 90.454 MB.
[2025-09-25T02:36:54.568Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T02:37:03.476Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T02:37:12.910Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T02:37:20.142Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T02:37:26.016Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T02:37:32.074Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T02:37:36.829Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T02:37:42.690Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T02:37:43.392Z] 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.
[2025-09-25T02:37:43.392Z] The best model improves the baseline by 14.52%.
[2025-09-25T02:37:44.092Z] Top recommended movies for user id 72:
[2025-09-25T02:37:44.092Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T02:37:44.092Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T02:37:44.092Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T02:37:44.092Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T02:37:44.092Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T02:37:44.092Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (58328.101 ms) ======
[2025-09-25T02:37:47.851Z] -----------------------------------
[2025-09-25T02:37:47.851Z] renaissance-movie-lens_0_PASSED
[2025-09-25T02:37:47.851Z] -----------------------------------
[2025-09-25T02:37:47.851Z]
[2025-09-25T02:37:47.851Z] TEST TEARDOWN:
[2025-09-25T02:37:47.851Z] Nothing to be done for teardown.
[2025-09-25T02:37:47.851Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 02:37:47 2025 Epoch Time (ms): 1758767867082