One Size Does Not Fit All: Querying Web Polystores

Abstract

Data retrieval systems are facing a paradigm shift due to the proliferation of specialized data storage engines (SQL, NoSQL, Column Stores, MapReduce, Data Stream, and Graph) supported by varied data models (CSV, JSON, RDB, RDF, and XML). One immediate consequence of this paradigm shift results into data bottleneck over the web; which means, web applications are unable to retrieve data with the intensity at which data are being generated from different facilities. Especially in the genomics and healthcare verticals, data are growing from petascale to exascale, and biomedical stakeholders are expecting seamless retrieval of these data over the web. In this paper, we argue that the bottleneck over the web can be reduced by minimizing the costly data conversion process and delegating query performance and processing loads to the specialized data storage engines over their native data models. We propose a web-based query federation mechanism-called PolyWeb-that unifies query answering over multiple native data models (CSV, RDB, and RDF). We emphasize two main challenges of query federation over native data models: 1) devise a method to select prospective data sources-with different underlying data models-that can satisfy a given query and 2) query optimization, join, and execution over different data models. We demonstrate PolyWeb on a cancer genomics use case, where it is often the case that a description of biological and chemical entities (e.g., gene, disease, drug, and pathways) spans across multiple data models and respective storage engines. In order to assess the benefits and limitations of evaluating queries over native data models, we evaluate PolyWeb with the state-of-the-art query federation engines in terms of result completeness, source selection, and overall query execution time.

An adaptive spark-based framework for querying large-scale NoSQL and relational databases

“…To reduce the latency of services provided by the platform, that adjust the data processing chain, they took an interest in Mongo and Cassandra databases and did not consider the rest of the databases. Khan et al [ 7 ]. and Duggan et al [ 17 ] it offers frameworks that called PolyWeb and BigDAWG, respectively.…”

GenomicsKG: A Knowledge Graph to Visualize Poly-Omics Data

“…The GenomicsKG will be optimizing querying of data from native data type through our in-house developed federation engine. 43,44 Personalized Medicine: With enrichment of functional annotation data and compatible visualization would make two important factors which might help in following Personalized medicine activities:…”

UCIS-X: An Updatable Compact Indexing Scheme for Efficient Extensible Markup Language Document Updating and Query Evaluation

“…Extensible markup language (XML) is increasingly used for data exchange and transfer [1], [2], such as in electronic publishing, web services, e-business, and search engines. In addition to the standard format for exchanging data, XML is one of the NoSQL database models [3], [4] and a new language for specifying video games, called the XMLbased video game description language (XVGDL) [5]. Because of its high availability and scalability, XML has rapidly gained attention [6].…”

“…(3) The length of the labels may increase after multiple XML updates. (4) The ability to maintain the initial labeling state may be weak. To address these issues, we present an update-friendly labeling scheme, i.e., branch map, and a compact indexing structure, i.e., UCIS-X.…”