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cs.DB updates on arXiv.org

Block-Sphere Vector Quantization GroupAffect-4: A Multimodal Dataset of Four-Person Collaborative Interaction CogScale: Scalable Benchmark for Sequence Processing TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings IVF-TQ: Calibration-Free Streaming Vector Search via a Codebook-Free Residual Layer Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Gaussian Relational Graph Transformer Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift A Horn extension of DL-Lite with NL data complexity 3D Primitives are a Spatial Language for VLMs Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance A CAP-like Trilemma for Large Language Models: Correctness, Non-bias, and Utility under Semantic Underdetermination EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models Toward Multi-Database Query Reasoning for Text2Cypher Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers Reconciling Consistency-Based Diagnosis with Actual-Causality-Based Explanations PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation Building informative materials datasets beyond targeted objectives
Studio e confronto delle strutture di Apache Spark
Massimiliano Morrelli · 2018-10-29 · via cs.DB updates on arXiv.org

English. This document is designed to study the data structures that can be used in the Apache Spark framework and to evaluate the best performing ones to implement solutions, in particular we will evaluate advantages / disadvantages deriving from the use of Dataset for job creation. The observation of the results provides further support in evaluating the use of Dataset as an alternative to RDD, in order to understand its strengths and weaknesses. The examination of the results is possible thanks to specifically designed and implemented in Java 1.8 language. The execution of the jobs, entrusted to a suitable distributed environment, will end with the comparison between execution times and results obtained. Italiano. Il presente documento nasce allo scopo di studiare le strutture dati utilizzabili nel framework Apache Spark e valutare quelle più performanti per implementare soluzioni; valuteremo in articolare i vantaggi / svantaggi derivanti dall'utilizzo dei Dataset nella progettazione dei job. L'osservazione dei risultati fornisce ulteriore supporto nel valutare l'utilizzo dei Dataset in alternativa a RDD, al fine di comprederne i punti di forza e di debolezza. L'esame dei risultati è possibile in virtù di due casi appositamente pensati e implementati in linguaggio Java 1.8. L'esecuzione dei job, affidata a un adeguato ambiente distribuito, si concluderà con il confronto tra tempi di esecuzione e risultati ottenuti.