NDLI: On scale independence for querying big data

Please wait, while we are loading the content...

Incomplete data: what went wrong, and how to fix it

Expressive languages for querying the semantic web

Weaker forms of monotonicity for declarative networking: a more fine-grained answer to the calm-conjecture

Model-data Ecosystems: challenges, tools, and trends

All-distances sketches, revisited: HIP estimators for massive graphs analysis

Enumerating answers to first-order queries over databases of low degree

Database principles in information extraction

Nested dependencies: structure and reasoning

Skew in parallel query processing

Independent range sampling

Expressiveness of guarded existential rule languages

Composable core-sets for diversity and coverage maximization

Counting solutions to conjunctive queries: structural and hybrid tractability

Cleaning inconsistencies in information extraction via prioritized repairs

Does query evaluation tractability help query containment?

The input/output complexity of triangle enumeration

A dynamic I/O-efficient structure for one-dimensional top-k range reporting

Containment and equivalence of well-designed SPARQL

Is min-wise hashing optimal for summarizing set intersection?

A dichotomy for non-repeating queries with negation in probabilistic databases

Generating low-cost plans from proofs

Beyond worst-case analysis for joins with minesweeper

Categorical range maxima queries

On scale independence for querying big data

Cost-oblivious storage reallocation

On scale independence for querying big data

Content Provider	ACM Digital Library
Author	Geerts, Floris Libkin, Leonid Fan, Wenfei
Abstract	To make query answering feasible in big datasets, practitioners have been looking into the notion of scale independence of queries. Intuitively, such queries require only a relatively small subset of the data, whose size is determined by the query and access methods rather than the size of the dataset itself. This paper aims to formalize this notion and study its properties. We start by defining what it means to be scale-independent, and provide matching upper and lower bounds for checking scale independence, for queries in various languages, and for combined and data complexity. Since the complexity turns out to be rather high, and since scale-independent queries cannot be captured syntactically, we develop sufficient conditions for scale independence. We formulate them based on access schemas, which combine indexing and constraints together with bounds on the sizes of retrieved data sets. We then study two variations of scale-independent query answering, inspired by existing practical systems. One concerns incremental query answering: we check when query answers can be maintained in response to updates scale-independently. The other explores scale-independent query rewriting using views.
Starting Page	51
Ending Page	62
Page Count	12
File Format	PDF
ISBN	9781450323758
DOI	10.1145/2594538.2594551
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-06-18
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Query answering Scale independence Big data
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Querying Big Data by Accessing Small Data

Querying big data

Semantic mediator querying

Approximate Queries on Big Heterogeneous Data

Query Relaxation across Heterogeneous Data Sources

Bounded Query Rewriting Using Views

Quegel: A General-Purpose System for Querying Big Graphs

Querying Large Databases

View-Based Query Answering and Query Containment over Semistructured Data (2001)

On scale independence for querying big data

Similar Documents

Querying Big Data by Accessing Small Data

Querying big data

Semantic mediator querying

Approximate Queries on Big Heterogeneous Data

Query Relaxation across Heterogeneous Data Sources

Bounded Query Rewriting Using Views

Quegel: A General-Purpose System for Querying Big Graphs

Querying Large Databases

View-Based Query Answering and Query Containment over Semistructured Data (2001)

On scale independence for querying big data