renaissance-movie-lens_0
[2025-11-27T01:22:23.877Z] Running test renaissance-movie-lens_0 ...
[2025-11-27T01:22:23.877Z] ===============================================
[2025-11-27T01:22:23.877Z] renaissance-movie-lens_0 Start Time: Thu Nov 27 01:22:23 2025 Epoch Time (ms): 1764206543151
[2025-11-27T01:22:23.877Z] variation: NoOptions
[2025-11-27T01:22:23.877Z] JVM_OPTIONS:
[2025-11-27T01:22:23.877Z] { \
[2025-11-27T01:22:23.877Z] echo ""; echo "TEST SETUP:"; \
[2025-11-27T01:22:23.877Z] echo "Nothing to be done for setup."; \
[2025-11-27T01:22:23.877Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642047138919/renaissance-movie-lens_0"; \
[2025-11-27T01:22:23.877Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642047138919/renaissance-movie-lens_0"; \
[2025-11-27T01:22:23.877Z] echo ""; echo "TESTING:"; \
[2025-11-27T01:22:23.877Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642047138919/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-27T01:22:23.877Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642047138919/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-27T01:22:23.877Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-27T01:22:23.877Z] echo "Nothing to be done for teardown."; \
[2025-11-27T01:22:23.877Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17642047138919/TestTargetResult";
[2025-11-27T01:22:23.877Z]
[2025-11-27T01:22:23.877Z] TEST SETUP:
[2025-11-27T01:22:23.877Z] Nothing to be done for setup.
[2025-11-27T01:22:23.877Z]
[2025-11-27T01:22:23.877Z] TESTING:
[2025-11-27T01:22:35.049Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-27T01:22:48.794Z] 01:22:48.124 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.
[2025-11-27T01:22:53.057Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-27T01:22:54.573Z] Training: 60056, validation: 20285, test: 19854
[2025-11-27T01:22:54.573Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-27T01:22:54.573Z] GC before operation: completed in 310.132 ms, heap usage 345.937 MB -> 75.869 MB.
[2025-11-27T01:23:10.239Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:23:19.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:23:29.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:23:37.171Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:23:41.608Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:23:45.833Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:23:51.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:23:54.434Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:23:55.166Z] 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.
[2025-11-27T01:23:55.910Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:23:55.910Z] Top recommended movies for user id 72:
[2025-11-27T01:23:55.910Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:23:55.910Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:23:55.910Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:23:55.910Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:23:55.910Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:23:55.910Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (61549.187 ms) ======
[2025-11-27T01:23:55.910Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-27T01:23:56.639Z] GC before operation: completed in 291.399 ms, heap usage 543.769 MB -> 90.053 MB.
[2025-11-27T01:24:03.182Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:24:09.740Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:24:17.940Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:24:23.323Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:24:27.556Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:24:32.894Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:24:37.126Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:24:41.355Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:24:41.355Z] 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.
[2025-11-27T01:24:42.082Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:24:42.082Z] Top recommended movies for user id 72:
[2025-11-27T01:24:42.082Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:24:42.082Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:24:42.082Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:24:42.082Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:24:42.082Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:24:42.082Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45835.964 ms) ======
[2025-11-27T01:24:42.082Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-27T01:24:42.805Z] GC before operation: completed in 250.664 ms, heap usage 209.821 MB -> 88.524 MB.
[2025-11-27T01:24:49.402Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:24:55.952Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:25:02.798Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:25:07.537Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:25:11.796Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:25:15.017Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:25:18.366Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:25:21.590Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:25:22.315Z] 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.
[2025-11-27T01:25:23.038Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:25:23.038Z] Top recommended movies for user id 72:
[2025-11-27T01:25:23.038Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:25:23.038Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:25:23.038Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:25:23.038Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:25:23.038Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:25:23.038Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (40676.703 ms) ======
[2025-11-27T01:25:23.038Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-27T01:25:23.761Z] GC before operation: completed in 276.535 ms, heap usage 376.639 MB -> 89.436 MB.
[2025-11-27T01:25:30.336Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:25:35.664Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:25:42.222Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:25:47.541Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:25:52.282Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:25:56.526Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:25:59.762Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:26:03.990Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:26:04.722Z] 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.
[2025-11-27T01:26:04.722Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:26:05.448Z] Top recommended movies for user id 72:
[2025-11-27T01:26:05.448Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:26:05.448Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:26:05.448Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:26:05.448Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:26:05.448Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:26:05.448Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (41652.923 ms) ======
[2025-11-27T01:26:05.448Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-27T01:26:05.448Z] GC before operation: completed in 374.673 ms, heap usage 112.126 MB -> 90.806 MB.
[2025-11-27T01:26:11.990Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:26:18.559Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:26:23.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:26:29.211Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:26:31.545Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:26:34.765Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:26:38.189Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:26:41.402Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:26:42.132Z] 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.
[2025-11-27T01:26:42.132Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:26:42.132Z] Top recommended movies for user id 72:
[2025-11-27T01:26:42.133Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:26:42.133Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:26:42.133Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:26:42.133Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:26:42.133Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:26:42.133Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (36973.271 ms) ======
[2025-11-27T01:26:42.133Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-27T01:26:42.863Z] GC before operation: completed in 340.238 ms, heap usage 554.907 MB -> 93.114 MB.
[2025-11-27T01:26:49.410Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:26:53.644Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:26:59.073Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:27:04.427Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:27:07.680Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:27:10.022Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:27:14.244Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:27:17.558Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:27:18.274Z] 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.
[2025-11-27T01:27:18.274Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:27:18.274Z] Top recommended movies for user id 72:
[2025-11-27T01:27:18.274Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:27:18.274Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:27:18.274Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:27:18.274Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:27:18.274Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:27:18.274Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (35524.848 ms) ======
[2025-11-27T01:27:18.274Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-27T01:27:18.274Z] GC before operation: completed in 240.965 ms, heap usage 120.623 MB -> 89.747 MB.
[2025-11-27T01:27:24.104Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:27:29.439Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:27:35.987Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:27:41.302Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:27:44.539Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:27:47.782Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:27:51.998Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:27:55.260Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:27:55.979Z] 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.
[2025-11-27T01:27:55.979Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:27:56.714Z] Top recommended movies for user id 72:
[2025-11-27T01:27:56.714Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:27:56.714Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:27:56.714Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:27:56.714Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:27:56.714Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:27:56.714Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (38028.525 ms) ======
[2025-11-27T01:27:56.714Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-27T01:27:56.714Z] GC before operation: completed in 293.529 ms, heap usage 295.105 MB -> 89.850 MB.
[2025-11-27T01:28:03.261Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:28:08.595Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:28:14.120Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:28:18.430Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:28:22.659Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:28:25.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:28:29.171Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:28:32.406Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:28:33.128Z] 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.
[2025-11-27T01:28:33.128Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:28:33.859Z] Top recommended movies for user id 72:
[2025-11-27T01:28:33.859Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:28:33.859Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:28:33.859Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:28:33.859Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:28:33.859Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:28:33.859Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (36851.295 ms) ======
[2025-11-27T01:28:33.859Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-27T01:28:33.859Z] GC before operation: completed in 339.123 ms, heap usage 178.568 MB -> 89.911 MB.
[2025-11-27T01:28:40.414Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:28:44.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:28:50.531Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:28:55.858Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:28:59.072Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:29:03.309Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:29:06.609Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:29:09.864Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:29:10.595Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-27T01:29:10.595Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:29:11.324Z] Top recommended movies for user id 72:
[2025-11-27T01:29:11.324Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:29:11.324Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:29:11.324Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:29:11.324Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:29:11.324Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:29:11.324Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (36980.696 ms) ======
[2025-11-27T01:29:11.324Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-27T01:29:11.324Z] GC before operation: completed in 292.020 ms, heap usage 569.666 MB -> 93.546 MB.
[2025-11-27T01:29:16.669Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:29:22.136Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:29:28.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:29:33.970Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:29:36.645Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:29:40.878Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:29:44.133Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:29:48.385Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:29:48.385Z] 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.
[2025-11-27T01:29:49.119Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:29:49.119Z] Top recommended movies for user id 72:
[2025-11-27T01:29:49.119Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:29:49.119Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:29:49.119Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:29:49.119Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:29:49.119Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:29:49.119Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (37730.224 ms) ======
[2025-11-27T01:29:49.119Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-27T01:29:49.119Z] GC before operation: completed in 338.211 ms, heap usage 493.730 MB -> 90.450 MB.
[2025-11-27T01:29:55.654Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:29:59.868Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:30:05.314Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:30:09.555Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:30:13.790Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:30:17.046Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:30:20.776Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:30:24.014Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:30:24.014Z] 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.
[2025-11-27T01:30:24.729Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:30:24.729Z] Top recommended movies for user id 72:
[2025-11-27T01:30:24.729Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:30:24.729Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:30:24.729Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:30:24.729Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:30:24.729Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:30:24.729Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (35298.066 ms) ======
[2025-11-27T01:30:24.729Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-27T01:30:24.729Z] GC before operation: completed in 296.298 ms, heap usage 134.552 MB -> 89.649 MB.
[2025-11-27T01:30:30.055Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:30:35.361Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:30:41.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:30:47.223Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:30:50.462Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:30:53.689Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:30:56.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:31:00.204Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:31:00.204Z] 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.
[2025-11-27T01:31:00.204Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:31:00.927Z] Top recommended movies for user id 72:
[2025-11-27T01:31:00.927Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:31:00.927Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:31:00.927Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:31:00.927Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:31:00.927Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:31:00.927Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (35559.876 ms) ======
[2025-11-27T01:31:00.927Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-27T01:31:00.927Z] GC before operation: completed in 241.360 ms, heap usage 199.096 MB -> 90.014 MB.
[2025-11-27T01:31:06.239Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:31:10.990Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:31:16.305Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:31:20.535Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:31:23.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:31:27.027Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:31:30.264Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:31:33.503Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:31:33.503Z] 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.
[2025-11-27T01:31:33.503Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:31:34.228Z] Top recommended movies for user id 72:
[2025-11-27T01:31:34.228Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:31:34.228Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:31:34.228Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:31:34.228Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:31:34.228Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:31:34.228Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (33268.672 ms) ======
[2025-11-27T01:31:34.228Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-27T01:31:34.228Z] GC before operation: completed in 276.210 ms, heap usage 167.472 MB -> 90.127 MB.
[2025-11-27T01:31:39.562Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:31:44.886Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:31:50.229Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:31:55.732Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:31:59.106Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:32:02.366Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:32:05.621Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:32:07.953Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:32:08.687Z] 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.
[2025-11-27T01:32:08.688Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:32:09.428Z] Top recommended movies for user id 72:
[2025-11-27T01:32:09.428Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:32:09.428Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:32:09.428Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:32:09.428Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:32:09.428Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:32:09.428Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (34731.373 ms) ======
[2025-11-27T01:32:09.428Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-27T01:32:09.428Z] GC before operation: completed in 258.656 ms, heap usage 364.094 MB -> 90.163 MB.
[2025-11-27T01:32:14.760Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:32:20.163Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:32:26.719Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:32:32.050Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:32:34.380Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:32:38.104Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:32:41.361Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:32:44.604Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:32:45.323Z] 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.
[2025-11-27T01:32:45.323Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:32:45.323Z] Top recommended movies for user id 72:
[2025-11-27T01:32:45.323Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:32:45.323Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:32:45.323Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:32:45.323Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:32:45.323Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:32:45.323Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (36004.879 ms) ======
[2025-11-27T01:32:45.323Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-27T01:32:45.323Z] GC before operation: completed in 304.174 ms, heap usage 291.490 MB -> 90.336 MB.
[2025-11-27T01:32:50.638Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:32:55.980Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:33:00.224Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:33:05.577Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:33:08.790Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:33:11.231Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:33:14.482Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:33:17.280Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:33:18.017Z] 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.
[2025-11-27T01:33:18.017Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:33:18.017Z] Top recommended movies for user id 72:
[2025-11-27T01:33:18.017Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:33:18.017Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:33:18.017Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:33:18.017Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:33:18.017Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:33:18.017Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (32547.206 ms) ======
[2025-11-27T01:33:18.017Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-27T01:33:18.743Z] GC before operation: completed in 309.820 ms, heap usage 498.449 MB -> 90.491 MB.
[2025-11-27T01:33:24.060Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:33:29.377Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:33:34.724Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:33:40.054Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:33:42.397Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:33:45.655Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:33:52.724Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:33:55.977Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:33:56.698Z] 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.
[2025-11-27T01:33:56.698Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:33:56.698Z] Top recommended movies for user id 72:
[2025-11-27T01:33:56.698Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:33:56.698Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:33:56.698Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:33:56.698Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:33:56.698Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:33:56.698Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (38195.341 ms) ======
[2025-11-27T01:33:56.698Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-27T01:33:57.644Z] GC before operation: completed in 380.336 ms, heap usage 545.194 MB -> 93.880 MB.
[2025-11-27T01:34:05.557Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:34:12.871Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:34:20.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:34:26.746Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:34:32.699Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:34:35.956Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:34:39.199Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:34:44.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:34:44.520Z] 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.
[2025-11-27T01:34:44.520Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:34:44.520Z] Top recommended movies for user id 72:
[2025-11-27T01:34:44.520Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:34:44.520Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:34:44.520Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:34:44.520Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:34:44.520Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:34:44.520Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (47515.098 ms) ======
[2025-11-27T01:34:44.520Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-27T01:34:44.520Z] GC before operation: completed in 218.635 ms, heap usage 533.906 MB -> 90.503 MB.
[2025-11-27T01:34:50.309Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:34:55.649Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:35:00.990Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:35:06.306Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:35:09.549Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:35:11.897Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:35:15.596Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:35:18.969Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:35:18.969Z] 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.
[2025-11-27T01:35:18.969Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:35:19.710Z] Top recommended movies for user id 72:
[2025-11-27T01:35:19.710Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:35:19.710Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:35:19.710Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:35:19.710Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:35:19.710Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:35:19.710Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (34684.582 ms) ======
[2025-11-27T01:35:19.710Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-27T01:35:19.710Z] GC before operation: completed in 322.554 ms, heap usage 259.899 MB -> 90.235 MB.
[2025-11-27T01:35:25.010Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-27T01:35:30.318Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-27T01:35:35.025Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-27T01:35:40.356Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-27T01:35:43.572Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-27T01:35:45.911Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-27T01:35:49.676Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-27T01:35:52.895Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-27T01:35:52.895Z] 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.
[2025-11-27T01:35:53.630Z] The best model improves the baseline by 14.52%.
[2025-11-27T01:35:53.630Z] Top recommended movies for user id 72:
[2025-11-27T01:35:53.630Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-27T01:35:53.630Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-27T01:35:53.630Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-27T01:35:53.630Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-27T01:35:53.630Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-27T01:35:53.630Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (33706.581 ms) ======
[2025-11-27T01:35:54.350Z] -----------------------------------
[2025-11-27T01:35:54.350Z] renaissance-movie-lens_0_PASSED
[2025-11-27T01:35:54.350Z] -----------------------------------
[2025-11-27T01:35:54.350Z]
[2025-11-27T01:35:54.350Z] TEST TEARDOWN:
[2025-11-27T01:35:54.350Z] Nothing to be done for teardown.
[2025-11-27T01:35:54.350Z] renaissance-movie-lens_0 Finish Time: Thu Nov 27 01:35:54 2025 Epoch Time (ms): 1764207354113