renaissance-movie-lens_0
[2025-05-29T04:27:22.763Z] Running test renaissance-movie-lens_0 ...
[2025-05-29T04:27:22.763Z] ===============================================
[2025-05-29T04:27:22.763Z] renaissance-movie-lens_0 Start Time: Thu May 29 04:27:21 2025 Epoch Time (ms): 1748492841910
[2025-05-29T04:27:22.763Z] variation: NoOptions
[2025-05-29T04:27:22.763Z] JVM_OPTIONS:
[2025-05-29T04:27:22.763Z] { \
[2025-05-29T04:27:22.763Z] echo ""; echo "TEST SETUP:"; \
[2025-05-29T04:27:22.763Z] echo "Nothing to be done for setup."; \
[2025-05-29T04:27:22.763Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17484905661127/renaissance-movie-lens_0"; \
[2025-05-29T04:27:22.763Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17484905661127/renaissance-movie-lens_0"; \
[2025-05-29T04:27:22.763Z] echo ""; echo "TESTING:"; \
[2025-05-29T04:27:22.763Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/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_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17484905661127/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-05-29T04:27:22.763Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17484905661127/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-05-29T04:27:22.763Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-05-29T04:27:22.763Z] echo "Nothing to be done for teardown."; \
[2025-05-29T04:27:22.763Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17484905661127/TestTargetResult";
[2025-05-29T04:27:22.763Z]
[2025-05-29T04:27:22.763Z] TEST SETUP:
[2025-05-29T04:27:22.763Z] Nothing to be done for setup.
[2025-05-29T04:27:22.763Z]
[2025-05-29T04:27:22.763Z] TESTING:
[2025-05-29T04:27:30.473Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-05-29T04:27:41.382Z] 04:27:40.783 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-05-29T04:27:45.457Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-05-29T04:27:46.127Z] Training: 60056, validation: 20285, test: 19854
[2025-05-29T04:27:46.127Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-05-29T04:27:46.127Z] GC before operation: completed in 235.647 ms, heap usage 273.151 MB -> 75.873 MB.
[2025-05-29T04:27:59.292Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:28:10.542Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:28:21.667Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:28:31.251Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:28:37.998Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:28:42.157Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:28:49.142Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:28:55.830Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:28:55.830Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T04:28:56.525Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:28:57.313Z] Top recommended movies for user id 72:
[2025-05-29T04:28:57.313Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:28:57.313Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:28:57.313Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:28:57.313Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:28:57.313Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:28:57.313Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (71189.796 ms) ======
[2025-05-29T04:28:57.313Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-05-29T04:28:57.997Z] GC before operation: completed in 488.199 ms, heap usage 390.988 MB -> 91.593 MB.
[2025-05-29T04:29:06.703Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:29:13.076Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:29:20.750Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:29:27.423Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:29:33.172Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:29:36.164Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:29:41.475Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:29:46.791Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:29:47.534Z] 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.
[2025-05-29T04:29:47.534Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:29:47.534Z] Top recommended movies for user id 72:
[2025-05-29T04:29:47.534Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:29:47.535Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:29:47.535Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:29:47.535Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:29:47.535Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:29:47.535Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (49629.642 ms) ======
[2025-05-29T04:29:47.535Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-05-29T04:29:48.192Z] GC before operation: completed in 417.909 ms, heap usage 281.893 MB -> 88.152 MB.
[2025-05-29T04:29:55.332Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:30:01.674Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:30:09.330Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:30:17.141Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:30:22.188Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:30:26.419Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:30:30.364Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:30:33.668Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:30:33.668Z] 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.
[2025-05-29T04:30:34.365Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:30:34.365Z] Top recommended movies for user id 72:
[2025-05-29T04:30:34.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:30:34.365Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:30:34.365Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:30:34.365Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:30:34.365Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:30:34.365Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (46172.902 ms) ======
[2025-05-29T04:30:34.365Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-05-29T04:30:34.365Z] GC before operation: completed in 249.847 ms, heap usage 195.454 MB -> 88.580 MB.
[2025-05-29T04:30:42.196Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:30:50.064Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:30:56.489Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:31:01.711Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:31:07.020Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:31:12.588Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:31:15.627Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:31:19.746Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:31:21.378Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T04:31:21.378Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:31:21.378Z] Top recommended movies for user id 72:
[2025-05-29T04:31:21.378Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:31:21.378Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:31:21.378Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:31:21.378Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:31:21.378Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:31:21.378Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (46743.856 ms) ======
[2025-05-29T04:31:21.378Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-05-29T04:31:21.378Z] GC before operation: completed in 213.487 ms, heap usage 282.425 MB -> 89.114 MB.
[2025-05-29T04:31:30.068Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:31:35.082Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:31:40.649Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:31:45.822Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:31:48.055Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:31:50.295Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:31:54.469Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:32:00.513Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:32:02.504Z] 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.
[2025-05-29T04:32:02.504Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:32:03.181Z] Top recommended movies for user id 72:
[2025-05-29T04:32:03.181Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:32:03.181Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:32:03.181Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:32:03.181Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:32:03.181Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:32:03.181Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (41545.344 ms) ======
[2025-05-29T04:32:03.181Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-05-29T04:32:03.181Z] GC before operation: completed in 371.751 ms, heap usage 239.654 MB -> 88.953 MB.
[2025-05-29T04:32:12.758Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:32:18.499Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:32:28.967Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:32:35.057Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:32:39.549Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:32:44.929Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:32:50.341Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:32:53.459Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:32:53.459Z] 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.
[2025-05-29T04:32:53.459Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:32:54.417Z] Top recommended movies for user id 72:
[2025-05-29T04:32:54.417Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:32:54.417Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:32:54.417Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:32:54.417Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:32:54.417Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:32:54.417Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (50915.596 ms) ======
[2025-05-29T04:32:54.417Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-05-29T04:32:55.096Z] GC before operation: completed in 1069.163 ms, heap usage 265.820 MB -> 89.392 MB.
[2025-05-29T04:33:01.900Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:33:09.728Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:33:17.539Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:33:25.125Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:33:28.795Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:33:31.884Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:33:35.998Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:33:39.246Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:33:39.246Z] 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.
[2025-05-29T04:33:39.246Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:33:39.953Z] Top recommended movies for user id 72:
[2025-05-29T04:33:39.953Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:33:39.953Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:33:39.953Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:33:39.953Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:33:39.953Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:33:39.953Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (44290.323 ms) ======
[2025-05-29T04:33:39.953Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-05-29T04:33:39.953Z] GC before operation: completed in 256.023 ms, heap usage 295.334 MB -> 89.463 MB.
[2025-05-29T04:33:45.039Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:33:50.188Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:33:56.816Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:34:04.583Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:34:08.793Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:34:14.940Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:34:17.169Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:34:20.331Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:34:20.973Z] 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.
[2025-05-29T04:34:20.973Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:34:21.641Z] Top recommended movies for user id 72:
[2025-05-29T04:34:21.641Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:34:21.641Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:34:21.641Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:34:21.641Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:34:21.641Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:34:21.641Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (41546.076 ms) ======
[2025-05-29T04:34:21.641Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-05-29T04:34:21.641Z] GC before operation: completed in 247.414 ms, heap usage 254.659 MB -> 89.691 MB.
[2025-05-29T04:34:28.035Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:34:33.728Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:34:41.358Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:34:46.848Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:34:52.202Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:34:54.410Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:34:57.497Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:35:01.796Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:35:02.596Z] 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.
[2025-05-29T04:35:03.781Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:35:03.781Z] Top recommended movies for user id 72:
[2025-05-29T04:35:03.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:35:03.781Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:35:03.781Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:35:03.781Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:35:03.781Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:35:03.781Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (41806.380 ms) ======
[2025-05-29T04:35:03.781Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-05-29T04:35:03.781Z] GC before operation: completed in 276.090 ms, heap usage 262.489 MB -> 89.480 MB.
[2025-05-29T04:35:10.262Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:35:16.729Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:35:24.469Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:35:30.882Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:35:35.018Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:35:40.328Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:35:46.086Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:35:50.448Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:35:51.103Z] 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.
[2025-05-29T04:35:51.103Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:35:51.103Z] Top recommended movies for user id 72:
[2025-05-29T04:35:51.103Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:35:51.103Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:35:51.103Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:35:51.103Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:35:51.103Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:35:51.103Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (47585.909 ms) ======
[2025-05-29T04:35:51.103Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-05-29T04:35:52.681Z] GC before operation: completed in 919.606 ms, heap usage 326.666 MB -> 89.815 MB.
[2025-05-29T04:36:04.851Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:36:12.859Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:36:19.654Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:36:27.418Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:36:31.398Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:36:34.495Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:36:39.025Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:36:43.093Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:36:43.746Z] 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.
[2025-05-29T04:36:43.746Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:36:43.746Z] Top recommended movies for user id 72:
[2025-05-29T04:36:43.746Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:36:43.746Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:36:43.746Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:36:43.746Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:36:43.746Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:36:43.746Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (51351.606 ms) ======
[2025-05-29T04:36:43.746Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-05-29T04:36:44.420Z] GC before operation: completed in 424.994 ms, heap usage 277.848 MB -> 89.414 MB.
[2025-05-29T04:36:50.502Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:36:54.464Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:36:59.388Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:37:04.522Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:37:08.530Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:37:10.730Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:37:14.748Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:37:17.106Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:37:17.769Z] 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.
[2025-05-29T04:37:17.769Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:37:17.769Z] Top recommended movies for user id 72:
[2025-05-29T04:37:17.769Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:37:17.769Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:37:17.769Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:37:17.769Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:37:17.769Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:37:17.769Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (33901.874 ms) ======
[2025-05-29T04:37:17.769Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-05-29T04:37:18.474Z] GC before operation: completed in 306.780 ms, heap usage 238.689 MB -> 89.484 MB.
[2025-05-29T04:37:25.144Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:37:31.468Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:37:39.274Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:37:42.888Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:37:47.269Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:37:51.603Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:37:57.102Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:38:00.340Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:38:01.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T04:38:01.008Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:38:01.670Z] Top recommended movies for user id 72:
[2025-05-29T04:38:01.670Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:38:01.670Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:38:01.670Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:38:01.670Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:38:01.670Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:38:01.670Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (43151.384 ms) ======
[2025-05-29T04:38:01.670Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-05-29T04:38:01.670Z] GC before operation: completed in 360.638 ms, heap usage 158.011 MB -> 91.876 MB.
[2025-05-29T04:38:09.705Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:38:14.690Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:38:21.283Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:38:26.303Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:38:30.220Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:38:33.406Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:38:37.478Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:38:40.491Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:38:41.183Z] 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.
[2025-05-29T04:38:41.183Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:38:41.183Z] Top recommended movies for user id 72:
[2025-05-29T04:38:41.183Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:38:41.183Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:38:41.183Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:38:41.183Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:38:41.183Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:38:41.183Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (39487.734 ms) ======
[2025-05-29T04:38:41.183Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-05-29T04:38:41.843Z] GC before operation: completed in 269.766 ms, heap usage 226.342 MB -> 89.496 MB.
[2025-05-29T04:38:45.889Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:38:52.458Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:39:00.609Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:39:06.942Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:39:11.047Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:39:15.038Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:39:18.810Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:39:22.878Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:39:23.597Z] 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.
[2025-05-29T04:39:23.597Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:39:24.280Z] Top recommended movies for user id 72:
[2025-05-29T04:39:24.280Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:39:24.280Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:39:24.280Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:39:24.280Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:39:24.280Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:39:24.280Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (42474.194 ms) ======
[2025-05-29T04:39:24.280Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-05-29T04:39:24.280Z] GC before operation: completed in 275.055 ms, heap usage 400.217 MB -> 89.969 MB.
[2025-05-29T04:39:32.137Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:39:38.492Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:39:43.589Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:39:48.787Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:39:52.784Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:39:55.899Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:39:58.979Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:40:01.168Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:40:01.841Z] 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.
[2025-05-29T04:40:01.842Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:40:02.578Z] Top recommended movies for user id 72:
[2025-05-29T04:40:02.578Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:40:02.578Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:40:02.578Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:40:02.578Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:40:02.578Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:40:02.578Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38184.597 ms) ======
[2025-05-29T04:40:02.578Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-05-29T04:40:03.360Z] GC before operation: completed in 426.456 ms, heap usage 285.282 MB -> 89.647 MB.
[2025-05-29T04:40:08.079Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:40:14.454Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:40:21.146Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:40:27.760Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:40:30.758Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:40:34.855Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:40:39.195Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:40:42.286Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:40:42.286Z] 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.
[2025-05-29T04:40:42.286Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:40:43.010Z] Top recommended movies for user id 72:
[2025-05-29T04:40:43.010Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:40:43.010Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:40:43.010Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:40:43.010Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:40:43.010Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:40:43.010Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (39686.185 ms) ======
[2025-05-29T04:40:43.010Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-05-29T04:40:43.010Z] GC before operation: completed in 251.268 ms, heap usage 226.520 MB -> 89.696 MB.
[2025-05-29T04:40:49.272Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:40:54.316Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:41:00.024Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:41:07.775Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:41:11.809Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:41:14.790Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:41:19.860Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:41:22.982Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:41:22.982Z] 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.
[2025-05-29T04:41:22.982Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:41:23.669Z] Top recommended movies for user id 72:
[2025-05-29T04:41:23.669Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:41:23.669Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:41:23.669Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:41:23.669Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:41:23.669Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:41:23.669Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (40562.086 ms) ======
[2025-05-29T04:41:23.669Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-05-29T04:41:23.669Z] GC before operation: completed in 264.416 ms, heap usage 176.636 MB -> 89.430 MB.
[2025-05-29T04:41:29.980Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:41:34.996Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:41:41.367Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:41:45.459Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:41:49.717Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:41:52.788Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:41:56.871Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:42:00.108Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:42:00.781Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-05-29T04:42:00.781Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:42:00.781Z] Top recommended movies for user id 72:
[2025-05-29T04:42:00.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:42:00.781Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:42:00.781Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:42:00.781Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:42:00.781Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:42:00.781Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (37157.538 ms) ======
[2025-05-29T04:42:00.781Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-05-29T04:42:01.478Z] GC before operation: completed in 250.043 ms, heap usage 210.843 MB -> 89.545 MB.
[2025-05-29T04:42:06.698Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-29T04:42:12.024Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-29T04:42:18.448Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-29T04:42:24.619Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-29T04:42:28.709Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-29T04:42:32.839Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-29T04:42:37.673Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-29T04:42:40.831Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-29T04:42:41.579Z] 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.
[2025-05-29T04:42:41.579Z] The best model improves the baseline by 14.34%.
[2025-05-29T04:42:41.579Z] Top recommended movies for user id 72:
[2025-05-29T04:42:41.579Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-05-29T04:42:41.579Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-05-29T04:42:41.579Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-05-29T04:42:41.579Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-05-29T04:42:41.579Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-05-29T04:42:41.579Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (40691.019 ms) ======
[2025-05-29T04:42:42.985Z] -----------------------------------
[2025-05-29T04:42:42.985Z] renaissance-movie-lens_0_PASSED
[2025-05-29T04:42:42.985Z] -----------------------------------
[2025-05-29T04:42:42.985Z]
[2025-05-29T04:42:42.985Z] TEST TEARDOWN:
[2025-05-29T04:42:42.985Z] Nothing to be done for teardown.
[2025-05-29T04:42:42.986Z] renaissance-movie-lens_0 Finish Time: Thu May 29 04:42:42 2025 Epoch Time (ms): 1748493762467