renaissance-movie-lens_0
[2025-11-06T00:22:17.834Z] Running test renaissance-movie-lens_0 ...
[2025-11-06T00:22:17.834Z] ===============================================
[2025-11-06T00:22:17.834Z] renaissance-movie-lens_0 Start Time: Thu Nov 6 00:22:17 2025 Epoch Time (ms): 1762388537501
[2025-11-06T00:22:17.834Z] variation: NoOptions
[2025-11-06T00:22:17.834Z] JVM_OPTIONS:
[2025-11-06T00:22:17.834Z] { \
[2025-11-06T00:22:17.834Z] echo ""; echo "TEST SETUP:"; \
[2025-11-06T00:22:17.834Z] echo "Nothing to be done for setup."; \
[2025-11-06T00:22:17.834Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17623873994805/renaissance-movie-lens_0"; \
[2025-11-06T00:22:17.834Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17623873994805/renaissance-movie-lens_0"; \
[2025-11-06T00:22:17.834Z] echo ""; echo "TESTING:"; \
[2025-11-06T00:22:17.834Z] "/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_17623873994805/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-06T00:22:17.834Z] 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_17623873994805/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-06T00:22:17.834Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-06T00:22:17.834Z] echo "Nothing to be done for teardown."; \
[2025-11-06T00:22:17.834Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17623873994805/TestTargetResult";
[2025-11-06T00:22:17.834Z]
[2025-11-06T00:22:17.834Z] TEST SETUP:
[2025-11-06T00:22:17.834Z] Nothing to be done for setup.
[2025-11-06T00:22:17.834Z]
[2025-11-06T00:22:17.834Z] TESTING:
[2025-11-06T00:22:40.010Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-06T00:22:58.543Z] 00:22:58.146 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-06T00:23:01.858Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-06T00:23:03.409Z] Training: 60056, validation: 20285, test: 19854
[2025-11-06T00:23:03.409Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-06T00:23:03.409Z] GC before operation: completed in 262.293 ms, heap usage 246.052 MB -> 75.994 MB.
[2025-11-06T00:23:17.026Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:23:25.205Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:23:33.314Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:23:38.915Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:23:42.269Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:23:45.605Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:23:48.946Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:23:53.310Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:23:53.310Z] 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.
[2025-11-06T00:23:53.311Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:23:54.065Z] Top recommended movies for user id 72:
[2025-11-06T00:23:54.065Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:23:54.065Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:23:54.065Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:23:54.065Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:23:54.065Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:23:54.065Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (50596.898 ms) ======
[2025-11-06T00:23:54.065Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-06T00:23:54.065Z] GC before operation: completed in 304.918 ms, heap usage 280.921 MB -> 95.729 MB.
[2025-11-06T00:24:03.740Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:24:10.523Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:24:18.607Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:24:24.102Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:24:27.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:24:31.216Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:24:35.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:24:38.900Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:24:39.654Z] 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.
[2025-11-06T00:24:39.654Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:24:39.654Z] Top recommended movies for user id 72:
[2025-11-06T00:24:39.654Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:24:39.654Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:24:39.654Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:24:39.654Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:24:39.654Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:24:39.654Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45435.117 ms) ======
[2025-11-06T00:24:39.654Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-06T00:24:40.400Z] GC before operation: completed in 287.653 ms, heap usage 551.836 MB -> 92.352 MB.
[2025-11-06T00:24:47.127Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:24:53.847Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:24:59.323Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:25:04.767Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:25:08.154Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:25:11.485Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:25:15.337Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:25:18.661Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:25:19.408Z] 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.
[2025-11-06T00:25:19.408Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:25:19.408Z] Top recommended movies for user id 72:
[2025-11-06T00:25:19.408Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:25:19.408Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:25:19.408Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:25:19.408Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:25:19.408Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:25:19.408Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (39518.469 ms) ======
[2025-11-06T00:25:19.408Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-06T00:25:20.157Z] GC before operation: completed in 283.582 ms, heap usage 628.696 MB -> 93.179 MB.
[2025-11-06T00:25:25.631Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:25:32.341Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:25:37.832Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:25:44.553Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:25:47.905Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:25:51.266Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:25:55.626Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:25:58.052Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:25:58.804Z] 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.
[2025-11-06T00:25:58.805Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:25:59.554Z] Top recommended movies for user id 72:
[2025-11-06T00:25:59.554Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:25:59.554Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:25:59.554Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:25:59.554Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:25:59.554Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:25:59.554Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (39219.700 ms) ======
[2025-11-06T00:25:59.554Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-06T00:25:59.554Z] GC before operation: completed in 221.012 ms, heap usage 432.971 MB -> 89.949 MB.
[2025-11-06T00:26:05.516Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:26:11.020Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:26:17.767Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:26:23.260Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:26:26.582Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:26:29.929Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:26:34.275Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:26:36.676Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:26:37.427Z] 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.
[2025-11-06T00:26:37.427Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:26:38.172Z] Top recommended movies for user id 72:
[2025-11-06T00:26:38.172Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:26:38.172Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:26:38.172Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:26:38.172Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:26:38.172Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:26:38.172Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (38562.394 ms) ======
[2025-11-06T00:26:38.172Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-06T00:26:38.172Z] GC before operation: completed in 229.420 ms, heap usage 246.334 MB -> 89.624 MB.
[2025-11-06T00:26:43.726Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:26:50.442Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:26:55.910Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:27:02.642Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:27:06.041Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:27:09.366Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:27:13.720Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:27:17.070Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:27:17.835Z] 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.
[2025-11-06T00:27:17.835Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:27:18.583Z] Top recommended movies for user id 72:
[2025-11-06T00:27:18.583Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:27:18.583Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:27:18.583Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:27:18.583Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:27:18.583Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:27:18.583Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (40240.020 ms) ======
[2025-11-06T00:27:18.583Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-06T00:27:18.583Z] GC before operation: completed in 346.068 ms, heap usage 378.745 MB -> 90.153 MB.
[2025-11-06T00:27:25.300Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:27:30.780Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:27:37.476Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:27:42.337Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:27:45.666Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:27:48.065Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:27:51.420Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:27:54.746Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:27:55.489Z] 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.
[2025-11-06T00:27:55.489Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:27:55.489Z] Top recommended movies for user id 72:
[2025-11-06T00:27:55.489Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:27:55.489Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:27:55.489Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:27:55.489Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:27:55.489Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:27:55.489Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (36905.710 ms) ======
[2025-11-06T00:27:55.489Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-06T00:27:56.237Z] GC before operation: completed in 220.516 ms, heap usage 273.789 MB -> 89.996 MB.
[2025-11-06T00:28:01.690Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:28:06.144Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:28:11.589Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:28:17.063Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:28:20.391Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:28:23.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:28:26.770Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:28:30.097Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:28:30.836Z] 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.
[2025-11-06T00:28:30.836Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:28:31.574Z] Top recommended movies for user id 72:
[2025-11-06T00:28:31.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:28:31.574Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:28:31.574Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:28:31.574Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:28:31.574Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:28:31.574Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (35334.201 ms) ======
[2025-11-06T00:28:31.574Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-06T00:28:31.574Z] GC before operation: completed in 271.276 ms, heap usage 540.434 MB -> 90.569 MB.
[2025-11-06T00:28:37.034Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:28:42.476Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:28:47.922Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:28:53.372Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:28:56.700Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:29:00.041Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:29:04.386Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:29:07.727Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:29:08.960Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-06T00:29:08.960Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:29:08.960Z] Top recommended movies for user id 72:
[2025-11-06T00:29:08.960Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:29:08.960Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:29:08.960Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:29:08.960Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:29:08.960Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:29:08.960Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (37265.796 ms) ======
[2025-11-06T00:29:08.960Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-06T00:29:09.785Z] GC before operation: completed in 279.164 ms, heap usage 125.042 MB -> 89.854 MB.
[2025-11-06T00:29:14.118Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:29:19.609Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:29:25.064Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:29:30.521Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:29:32.909Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:29:36.227Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:29:39.648Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:29:42.043Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:29:42.784Z] 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.
[2025-11-06T00:29:42.784Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:29:42.784Z] Top recommended movies for user id 72:
[2025-11-06T00:29:42.784Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:29:42.784Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:29:42.784Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:29:42.784Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:29:42.784Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:29:42.784Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (34086.194 ms) ======
[2025-11-06T00:29:42.784Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-06T00:29:43.531Z] GC before operation: completed in 296.152 ms, heap usage 554.216 MB -> 93.805 MB.
[2025-11-06T00:29:49.007Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:29:54.473Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:29:59.302Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:30:03.652Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:30:08.055Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:30:10.448Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:30:13.771Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:30:17.085Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:30:17.085Z] 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.
[2025-11-06T00:30:17.085Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:30:17.853Z] Top recommended movies for user id 72:
[2025-11-06T00:30:17.853Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:30:17.853Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:30:17.853Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:30:17.853Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:30:17.853Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:30:17.853Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (34212.278 ms) ======
[2025-11-06T00:30:17.853Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-06T00:30:17.853Z] GC before operation: completed in 319.292 ms, heap usage 239.660 MB -> 89.823 MB.
[2025-11-06T00:30:23.293Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:30:31.360Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:30:38.056Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:30:43.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:30:46.414Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:30:49.740Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:30:53.079Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:30:56.424Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:30:57.176Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-06T00:30:57.176Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:30:57.932Z] Top recommended movies for user id 72:
[2025-11-06T00:30:57.932Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:30:57.933Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:30:57.933Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:30:57.933Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:30:57.933Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:30:57.933Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (39788.137 ms) ======
[2025-11-06T00:30:57.933Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-06T00:30:57.933Z] GC before operation: completed in 282.718 ms, heap usage 180.717 MB -> 90.144 MB.
[2025-11-06T00:31:03.394Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:31:08.936Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:31:14.443Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:31:18.829Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:31:23.163Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:31:26.489Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:31:29.810Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:31:33.630Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:31:33.630Z] 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.
[2025-11-06T00:31:33.630Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:31:34.369Z] Top recommended movies for user id 72:
[2025-11-06T00:31:34.369Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:31:34.369Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:31:34.369Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:31:34.369Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:31:34.369Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:31:34.369Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36153.555 ms) ======
[2025-11-06T00:31:34.369Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-06T00:31:34.369Z] GC before operation: completed in 263.231 ms, heap usage 481.646 MB -> 90.524 MB.
[2025-11-06T00:31:41.032Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:31:46.501Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:31:53.215Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:31:59.938Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:32:02.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:32:05.918Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:32:09.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:32:12.582Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:32:12.582Z] 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.
[2025-11-06T00:32:12.582Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:32:13.337Z] Top recommended movies for user id 72:
[2025-11-06T00:32:13.337Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:32:13.337Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:32:13.337Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:32:13.337Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:32:13.337Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:32:13.337Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38592.290 ms) ======
[2025-11-06T00:32:13.337Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-06T00:32:13.337Z] GC before operation: completed in 271.863 ms, heap usage 270.745 MB -> 90.187 MB.
[2025-11-06T00:32:19.266Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:32:24.742Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:32:30.205Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:32:35.716Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:32:39.064Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:32:41.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:32:44.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:32:48.139Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:32:48.881Z] 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.
[2025-11-06T00:32:48.881Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:32:48.881Z] Top recommended movies for user id 72:
[2025-11-06T00:32:48.881Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:32:48.881Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:32:48.881Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:32:48.881Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:32:48.881Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:32:48.881Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (35888.783 ms) ======
[2025-11-06T00:32:48.881Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-06T00:32:49.628Z] GC before operation: completed in 258.818 ms, heap usage 175.039 MB -> 90.303 MB.
[2025-11-06T00:32:53.956Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:32:59.485Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:33:04.923Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:33:09.511Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:33:12.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:33:15.227Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:33:18.548Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:33:21.891Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:33:21.891Z] 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.
[2025-11-06T00:33:22.630Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:33:22.630Z] Top recommended movies for user id 72:
[2025-11-06T00:33:22.630Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:33:22.630Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:33:22.630Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:33:22.630Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:33:22.630Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:33:22.630Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (33180.985 ms) ======
[2025-11-06T00:33:22.630Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-06T00:33:22.630Z] GC before operation: completed in 277.543 ms, heap usage 272.408 MB -> 90.294 MB.
[2025-11-06T00:33:32.444Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:33:37.878Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:33:43.369Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:33:48.806Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:33:51.192Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:33:54.510Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:33:58.341Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:34:02.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:34:03.450Z] 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.
[2025-11-06T00:34:03.450Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:34:03.450Z] Top recommended movies for user id 72:
[2025-11-06T00:34:03.450Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:34:03.450Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:34:03.450Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:34:03.450Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:34:03.450Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:34:03.450Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (40660.718 ms) ======
[2025-11-06T00:34:03.450Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-06T00:34:04.198Z] GC before operation: completed in 337.286 ms, heap usage 533.278 MB -> 90.747 MB.
[2025-11-06T00:34:09.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:34:14.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:34:19.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:34:25.074Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:34:28.407Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:34:32.859Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:34:36.188Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:34:39.553Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:34:40.308Z] 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.
[2025-11-06T00:34:40.308Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:34:40.308Z] Top recommended movies for user id 72:
[2025-11-06T00:34:40.308Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:34:40.308Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:34:40.308Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:34:40.308Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:34:40.308Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:34:40.308Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (36556.352 ms) ======
[2025-11-06T00:34:40.308Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-06T00:34:41.070Z] GC before operation: completed in 255.456 ms, heap usage 309.616 MB -> 90.129 MB.
[2025-11-06T00:34:48.012Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:34:57.645Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:35:16.126Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:35:22.850Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:35:26.178Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:35:29.508Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:35:32.837Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:35:36.309Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:35:36.309Z] 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.
[2025-11-06T00:35:36.309Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:35:37.049Z] Top recommended movies for user id 72:
[2025-11-06T00:35:37.049Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:35:37.049Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:35:37.049Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:35:37.049Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:35:37.049Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:35:37.049Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (55966.830 ms) ======
[2025-11-06T00:35:37.049Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-06T00:35:37.049Z] GC before operation: completed in 262.599 ms, heap usage 286.006 MB -> 90.312 MB.
[2025-11-06T00:35:43.777Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-06T00:35:49.237Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-06T00:35:54.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-06T00:36:01.405Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-06T00:36:03.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-06T00:36:09.283Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-06T00:36:12.612Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-06T00:36:15.961Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-06T00:36:15.961Z] 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.
[2025-11-06T00:36:15.961Z] The best model improves the baseline by 14.52%.
[2025-11-06T00:36:16.705Z] Top recommended movies for user id 72:
[2025-11-06T00:36:16.706Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-06T00:36:16.706Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-06T00:36:16.706Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-06T00:36:16.706Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-06T00:36:16.706Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-06T00:36:16.706Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (39515.889 ms) ======
[2025-11-06T00:36:17.445Z] -----------------------------------
[2025-11-06T00:36:17.445Z] renaissance-movie-lens_0_PASSED
[2025-11-06T00:36:17.445Z] -----------------------------------
[2025-11-06T00:36:17.445Z]
[2025-11-06T00:36:17.445Z] TEST TEARDOWN:
[2025-11-06T00:36:17.445Z] Nothing to be done for teardown.
[2025-11-06T00:36:17.445Z] renaissance-movie-lens_0 Finish Time: Thu Nov 6 00:36:17 2025 Epoch Time (ms): 1762389377144