Compendious and Succinct Data Structures for Big Data

Data Representation in memory is one of the tasks in Big data. Data representation includes several types of tree data structures through the system can access accurate and efficient data in big data. Succinct data structures can play important role in data representation while data in big-data is processed in main memory. Data representation is a very complex problem in Big Data.We proposed some solution of problems of data representation in Big data. Data processing in big data can be utilized to take a decision on data mining. We know the function and rules for query processing. We have to either change the method of processor we can change the way of representation. In this paper, different kind of tree data structures is presented for data representation in main memory of computer system for big data by using succinct data structures. Here we first compare all data structures by the table. Each method has different space and time complexity. We know that Big data information services increasing day by day. So space complexity of succinct data structures is becoming very popular in practice in this era.

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Application-Oriented Succinct Data Structures for Big Data

The Review of Socionetwork Strategies ◽

10.1007/s12626-019-00045-1 ◽

2019 ◽

Vol 13 (2) ◽

pp. 227-236

Author(s):

Tetsuo Shibuya

Keyword(s):

Big Data ◽

Data Structure ◽

Data Structures ◽

Genome Assembly ◽

Original Data ◽

Succinct Data Structures ◽

Space Requirement ◽

Space Reduction ◽

Big Data Applications ◽

Application Specific

Abstract A data structure is called succinct if its asymptotical space requirement matches the original data size. The development of succinct data structures is an important factor to deal with the explosively increasing big data. Moreover, wider variations of big data have been produced in various fields recently and there is a substantial need for the development of more application-specific succinct data structures. In this study, we review the recently proposed application-oriented succinct data structures motivated by big data applications in three different fields: privacy-preserving computation in cryptography, genome assembly in bioinformatics, and work space reduction for compressed communications.

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Representation of Recipe Flow Graphs in Succinct Data Structures

Proceedings of the 11th Workshop on Multimedia for Cooking and Eating Activities - CEA '19 ◽

10.1145/3326458.3326930 ◽

2019 ◽

Author(s):

Takuya Namiki ◽

Tomonobu Ozaki

Keyword(s):

Data Structures ◽

Succinct Data Structures ◽

Flow Graphs

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From Theory to Practice: Plug and Play with Succinct Data Structures

Experimental Algorithms - Lecture Notes in Computer Science ◽

10.1007/978-3-319-07959-2_28 ◽

2014 ◽

pp. 326-337 ◽

Cited By ~ 131

Author(s):

Simon Gog ◽

Timo Beller ◽

Alistair Moffat ◽

Matthias Petri

Keyword(s):

Data Structures ◽

Succinct Data Structures ◽

Plug And Play ◽

Theory To Practice

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Scalable and Hierarchical Distributed Data Structures for Efficient Big Data Management

Algorithmic Aspects of Cloud Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-030-58628-7_8 ◽

2020 ◽

pp. 122-160

Author(s):

Spyros Sioutas ◽

Gerasimos Vonitsanos ◽

Nikolaos Zacharatos ◽

Christos Zaroliagis

Keyword(s):

Big Data ◽

Data Management ◽

Data Structures ◽

Distributed Data ◽

Distributed Data Structures

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LevioSAM: Fast lift-over of alternate reference alignments

10.1101/2021.02.05.429867 ◽

2021 ◽

Author(s):

Taher Mun ◽

Nae-Chyun Chen ◽

Ben Langmead

Keyword(s):

Population Genetics ◽

Coordinate System ◽

Data Structures ◽

Succinct Data Structures ◽

Reference Coordinate System ◽

Link Type ◽

A Chain ◽

Time Required ◽

Effective Use

AbstractMotivationAs more population genetics datasets and population-specific references become available, the task of translating (“lifting”) read alignments from one reference coordinate system to another is becoming more common. Existing tools generally require a chain file, whereas VCF files are the more common way to represent variation. Existing tools also do not make effective use of threads, creating a post-alignment bottleneck.ResultsLevioSAM is a tool for lifting SAM/BAM alignments from one reference to another using a VCF file containing population variants. LevioSAM uses succinct data structures and scales efficiently to many threads. When run downstream of a read aligner, levioSAM completes in less than 13% the time required by an aligner when both are run with 16 threads.Availabilityhttps://github.com/alshai/[email protected], [email protected]

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