renaissance-movie-lens_0
[2025-05-29T05:27:38.616Z] Running test renaissance-movie-lens_0 ...
[2025-05-29T05:27:38.616Z] ===============================================
[2025-05-29T05:27:38.617Z] renaissance-movie-lens_0 Start Time: Thu May 29 05:27:38 2025 Epoch Time (ms): 1748496458298
[2025-05-29T05:27:38.617Z] variation: NoOptions
[2025-05-29T05:27:38.617Z] JVM_OPTIONS:
[2025-05-29T05:27:38.617Z] { \
[2025-05-29T05:27:38.617Z] echo ""; echo "TEST SETUP:"; \
[2025-05-29T05:27:38.617Z] echo "Nothing to be done for setup."; \
[2025-05-29T05:27:38.617Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17484964571736/renaissance-movie-lens_0"; \
[2025-05-29T05:27:38.617Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17484964571736/renaissance-movie-lens_0"; \
[2025-05-29T05:27:38.617Z] echo ""; echo "TESTING:"; \
[2025-05-29T05:27:38.617Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17484964571736/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-05-29T05:27:38.617Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17484964571736/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-05-29T05:27:38.617Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-05-29T05:27:38.617Z] echo "Nothing to be done for teardown."; \
[2025-05-29T05:27:38.617Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17484964571736/TestTargetResult";
[2025-05-29T05:27:38.617Z]
[2025-05-29T05:27:38.617Z] TEST SETUP:
[2025-05-29T05:27:38.617Z] Nothing to be done for setup.
[2025-05-29T05:27:38.617Z]
[2025-05-29T05:27:38.617Z] TESTING:
[2025-05-29T05:27:51.673Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-05-29T05:28:04.352Z] 05:28:02.905 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-05-29T05:28:07.330Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-05-29T05:28:08.801Z] Training: 60056, validation: 20285, test: 19854
[2025-05-29T05:28:08.801Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-05-29T05:28:08.801Z] GC before operation: completed in 328.994 ms, heap usage 216.145 MB -> 74.429 MB.
[2025-05-29T05:28:27.607Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:28:39.239Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:28:50.150Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:28:57.863Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:29:04.447Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:29:10.674Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:29:17.122Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:29:22.266Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:29:22.927Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:29:22.927Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:29:22.927Z] Top recommended movies for user id 72:
[2025-05-29T05:29:22.927Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:29:22.927Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:29:22.927Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:29:22.927Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:29:22.927Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:29:23.880Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (74523.859 ms) ======
[2025-05-29T05:29:23.880Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-05-29T05:29:23.880Z] GC before operation: completed in 572.392 ms, heap usage 195.247 MB -> 88.372 MB.
[2025-05-29T05:29:31.957Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:29:37.177Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:29:44.773Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:29:52.430Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:29:56.628Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:30:01.731Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:30:06.805Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:30:11.878Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:30:11.878Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:30:11.878Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:30:11.878Z] Top recommended movies for user id 72:
[2025-05-29T05:30:11.878Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:30:11.878Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:30:11.878Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:30:11.878Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:30:11.878Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:30:11.878Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (48220.614 ms) ======
[2025-05-29T05:30:11.878Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-05-29T05:30:12.537Z] GC before operation: completed in 274.437 ms, heap usage 235.503 MB -> 86.757 MB.
[2025-05-29T05:30:18.923Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:30:26.416Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:30:31.428Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:30:37.195Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:30:40.210Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:30:43.209Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:30:47.176Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:30:51.413Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:30:51.413Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:30:51.413Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:30:51.413Z] Top recommended movies for user id 72:
[2025-05-29T05:30:51.413Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:30:51.413Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:30:51.413Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:30:51.413Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:30:51.413Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:30:51.413Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (39300.799 ms) ======
[2025-05-29T05:30:51.413Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-05-29T05:30:52.060Z] GC before operation: completed in 329.169 ms, heap usage 105.511 MB -> 87.131 MB.
[2025-05-29T05:30:58.387Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:31:04.069Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:31:10.305Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:31:16.538Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:31:20.613Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:31:23.730Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:31:28.800Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:31:32.902Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:31:33.568Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:31:33.568Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:31:33.568Z] Top recommended movies for user id 72:
[2025-05-29T05:31:33.568Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:31:33.568Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:31:33.568Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:31:33.568Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:31:33.568Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:31:33.568Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (41754.631 ms) ======
[2025-05-29T05:31:33.568Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-05-29T05:31:34.254Z] GC before operation: completed in 323.586 ms, heap usage 325.789 MB -> 87.768 MB.
[2025-05-29T05:31:40.449Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:31:48.034Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:31:57.339Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:32:04.901Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:32:09.378Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:32:14.703Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:32:18.673Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:32:23.991Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:32:24.648Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:32:24.648Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:32:25.324Z] Top recommended movies for user id 72:
[2025-05-29T05:32:25.324Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:32:25.324Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:32:25.324Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:32:25.324Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:32:25.324Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:32:25.324Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (51050.768 ms) ======
[2025-05-29T05:32:25.324Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-05-29T05:32:25.324Z] GC before operation: completed in 490.725 ms, heap usage 145.528 MB -> 87.456 MB.
[2025-05-29T05:32:33.132Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:32:41.036Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:32:52.842Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:33:03.119Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:33:08.488Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:33:12.518Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:33:16.569Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:33:23.351Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:33:23.351Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:33:23.351Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:33:24.060Z] Top recommended movies for user id 72:
[2025-05-29T05:33:24.060Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:33:24.060Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:33:24.060Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:33:24.060Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:33:24.060Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:33:24.060Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (58433.553 ms) ======
[2025-05-29T05:33:24.060Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-05-29T05:33:24.949Z] GC before operation: completed in 468.331 ms, heap usage 288.758 MB -> 87.988 MB.
[2025-05-29T05:33:37.571Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:33:47.148Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:33:59.194Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:34:07.277Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:34:12.452Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:34:18.759Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:34:25.169Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:34:30.694Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:34:31.368Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:34:32.069Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:34:32.069Z] Top recommended movies for user id 72:
[2025-05-29T05:34:32.069Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:34:32.069Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:34:32.069Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:34:32.069Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:34:32.069Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:34:32.069Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (67758.393 ms) ======
[2025-05-29T05:34:32.069Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-05-29T05:34:32.754Z] GC before operation: completed in 754.069 ms, heap usage 206.988 MB -> 87.787 MB.
[2025-05-29T05:34:40.511Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:34:46.917Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:34:54.641Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:34:59.848Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:35:06.638Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:35:11.789Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:35:17.520Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:35:23.932Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:35:24.671Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:35:24.671Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:35:24.671Z] Top recommended movies for user id 72:
[2025-05-29T05:35:24.671Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:35:24.671Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:35:24.671Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:35:24.671Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:35:24.671Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:35:24.671Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (51885.776 ms) ======
[2025-05-29T05:35:24.671Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-05-29T05:35:25.456Z] GC before operation: completed in 376.722 ms, heap usage 98.690 MB -> 88.132 MB.
[2025-05-29T05:35:34.955Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:35:42.630Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:35:50.364Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:35:59.591Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:36:06.203Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:36:11.778Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:36:18.112Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:36:21.164Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:36:22.921Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:36:22.921Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:36:22.921Z] Top recommended movies for user id 72:
[2025-05-29T05:36:22.921Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:36:22.921Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:36:22.921Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:36:22.921Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:36:22.921Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:36:22.921Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (57638.889 ms) ======
[2025-05-29T05:36:22.921Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-05-29T05:36:23.609Z] GC before operation: completed in 516.148 ms, heap usage 275.859 MB -> 87.964 MB.
[2025-05-29T05:36:33.186Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:36:40.978Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:36:48.995Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:36:55.420Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:36:58.512Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:37:03.624Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:37:08.987Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:37:13.016Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:37:14.415Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:37:14.415Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:37:14.415Z] Top recommended movies for user id 72:
[2025-05-29T05:37:14.415Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:37:14.415Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:37:14.415Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:37:14.415Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:37:14.415Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:37:14.415Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (50897.319 ms) ======
[2025-05-29T05:37:14.415Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-05-29T05:37:14.415Z] GC before operation: completed in 344.329 ms, heap usage 293.136 MB -> 88.153 MB.
[2025-05-29T05:37:24.599Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:37:32.208Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:37:38.442Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:37:46.277Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:37:49.287Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:37:53.346Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:37:57.378Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:38:01.711Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:38:02.399Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:38:02.399Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:38:02.399Z] Top recommended movies for user id 72:
[2025-05-29T05:38:02.399Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:38:02.399Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:38:02.399Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:38:02.399Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:38:02.399Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:38:02.399Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (47981.233 ms) ======
[2025-05-29T05:38:02.399Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-05-29T05:38:03.077Z] GC before operation: completed in 342.575 ms, heap usage 263.064 MB -> 87.900 MB.
[2025-05-29T05:38:10.827Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:38:16.579Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:38:25.595Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:38:32.054Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:38:37.179Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:38:40.310Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:38:45.767Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:38:49.933Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:38:50.595Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:38:51.348Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:38:51.348Z] Top recommended movies for user id 72:
[2025-05-29T05:38:51.348Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:38:51.348Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:38:51.348Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:38:51.348Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:38:51.348Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:38:51.348Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (48618.870 ms) ======
[2025-05-29T05:38:51.348Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-05-29T05:38:52.018Z] GC before operation: completed in 513.498 ms, heap usage 149.551 MB -> 87.940 MB.
[2025-05-29T05:38:59.685Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:39:06.870Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:39:16.189Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:39:22.428Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:39:27.967Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:39:31.997Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:39:38.348Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:39:42.538Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:39:42.538Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:39:42.538Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:39:43.185Z] Top recommended movies for user id 72:
[2025-05-29T05:39:43.185Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:39:43.185Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:39:43.185Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:39:43.185Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:39:43.185Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:39:43.185Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (50881.992 ms) ======
[2025-05-29T05:39:43.185Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-05-29T05:39:43.185Z] GC before operation: completed in 452.324 ms, heap usage 111.168 MB -> 88.025 MB.
[2025-05-29T05:39:51.294Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:39:57.737Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:40:05.850Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:40:13.487Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:40:17.629Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:40:23.137Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:40:28.598Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:40:36.176Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:40:36.176Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:40:36.176Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:40:36.904Z] Top recommended movies for user id 72:
[2025-05-29T05:40:36.904Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:40:36.904Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:40:36.904Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:40:36.904Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:40:36.904Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:40:36.904Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (53248.109 ms) ======
[2025-05-29T05:40:36.904Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-05-29T05:40:36.904Z] GC before operation: completed in 415.305 ms, heap usage 274.005 MB -> 88.034 MB.
[2025-05-29T05:40:45.077Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:40:55.348Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:41:08.619Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:41:17.870Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:41:30.933Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:41:35.805Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:41:45.628Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:41:50.631Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:41:52.338Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:41:52.338Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:41:52.338Z] Top recommended movies for user id 72:
[2025-05-29T05:41:52.338Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:41:52.338Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:41:52.338Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:41:52.338Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:41:52.338Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:41:52.338Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (74932.164 ms) ======
[2025-05-29T05:41:52.338Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-05-29T05:41:55.433Z] GC before operation: completed in 2579.911 ms, heap usage 113.473 MB -> 88.320 MB.
[2025-05-29T05:42:07.358Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:42:16.996Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:42:28.559Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:42:35.154Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:42:42.476Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:42:46.169Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:42:50.543Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:42:55.960Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:42:55.960Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:42:55.960Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:42:56.629Z] Top recommended movies for user id 72:
[2025-05-29T05:42:56.629Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:42:56.629Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:42:56.629Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:42:56.629Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:42:56.629Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:42:56.629Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (61756.373 ms) ======
[2025-05-29T05:42:56.629Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-05-29T05:42:56.629Z] GC before operation: completed in 443.861 ms, heap usage 312.345 MB -> 86.749 MB.
[2025-05-29T05:43:06.058Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:43:14.467Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:43:22.436Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:43:34.661Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:43:38.687Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:43:42.363Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:43:50.614Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:43:54.665Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:43:54.665Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:43:54.665Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:43:55.380Z] Top recommended movies for user id 72:
[2025-05-29T05:43:55.380Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:43:55.380Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:43:55.380Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:43:55.380Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:43:55.380Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:43:55.380Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (58370.294 ms) ======
[2025-05-29T05:43:55.380Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-05-29T05:43:55.380Z] GC before operation: completed in 302.389 ms, heap usage 106.765 MB -> 84.137 MB.
[2025-05-29T05:44:07.168Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:44:14.889Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:44:24.212Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:44:31.919Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:44:41.081Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:44:45.436Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:44:50.519Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:44:56.861Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:44:57.536Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:44:57.536Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:44:57.536Z] Top recommended movies for user id 72:
[2025-05-29T05:44:57.536Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:44:57.536Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:44:57.536Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:44:57.536Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:44:57.536Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:44:57.536Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (62008.006 ms) ======
[2025-05-29T05:44:57.536Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-05-29T05:44:58.318Z] GC before operation: completed in 508.155 ms, heap usage 398.061 MB -> 83.646 MB.
[2025-05-29T05:45:06.063Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:45:14.040Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:45:21.958Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:45:31.713Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:45:35.941Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:45:41.055Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:45:47.848Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:45:54.297Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:45:55.025Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:45:55.025Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:45:55.025Z] Top recommended movies for user id 72:
[2025-05-29T05:45:55.025Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:45:55.025Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:45:55.025Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:45:55.025Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:45:55.025Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:45:55.025Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (57069.057 ms) ======
[2025-05-29T05:45:55.025Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-05-29T05:45:55.693Z] GC before operation: completed in 538.393 ms, heap usage 279.192 MB -> 83.476 MB.
[2025-05-29T05:46:04.073Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T05:46:23.622Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T05:46:33.253Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T05:46:41.102Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T05:46:44.208Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T05:46:48.239Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T05:46:52.196Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T05:46:56.255Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T05:46:56.918Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T05:46:56.918Z] The best model improves the baseline by 14.34%.
[2025-05-29T05:46:56.918Z] Top recommended movies for user id 72:
[2025-05-29T05:46:56.918Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T05:46:56.918Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T05:46:56.918Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T05:46:56.918Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T05:46:56.918Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T05:46:56.918Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (61444.145 ms) ======
[2025-05-29T05:46:57.579Z] -----------------------------------
[2025-05-29T05:46:57.579Z] renaissance-movie-lens_0_PASSED
[2025-05-29T05:46:57.579Z] -----------------------------------
[2025-05-29T05:46:57.579Z]
[2025-05-29T05:46:57.579Z] TEST TEARDOWN:
[2025-05-29T05:46:57.579Z] Nothing to be done for teardown.
[2025-05-29T05:46:57.579Z] renaissance-movie-lens_0 Finish Time: Thu May 29 05:46:57 2025 Epoch Time (ms): 1748497617486