HSQL: A Highly Scalable Cloud Database for Multi-user Query Processing

Chang, Chao-Rui; Hsieh, Meng-Ju; Wu, Jan‐Jan; Wu, Po-Yen; Liu, Pangfeng

doi:10.1109/cloud.2012.76

Cited by 9 publications

(8 citation statements)

References 1 publication

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“…We obtained 17 papers related to 16 approaches. These papers were published in three distinct journals and seven distinct conferences and workshops.…”

Section: Related Workmentioning

confidence: 99%

“…Chang et al proposed a new distributed B‐tree column indexing scheme for HBase, which can support indexing for non‐rowkey columns, as well as parallel B‐tree search in a large data table. Experiments presented by Chang et al demonstrate that the proposed approach can reach both high performance and scalability using the indexing scheme on point queries, range queries, and aggregation operations, when compared with standard HBase.…”

Section: Related Workmentioning

confidence: 99%

“…We obtained 17 papers 17,18,[59][60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75] related to 16 approaches. These papers were published in three distinct journals and seven distinct conferences and workshops.…”

Section: Related Workmentioning

confidence: 99%

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OLAP parallel query processing in clouds with C‐ParGRES

Ribeiro

Lima

Oliveira

2019

Concurrency and Computation

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Summary The advent of big data technologies has changed the way many companies manage their data. Several companies moved their data to the cloud using the concept of database‐as‐a‐service (DBaaS). Moving databases to the cloud presents several challenges related to flexible and scalable management of data. Although some of these companies migrated to NoSQL databases, most still rely on relational databases in the cloud to manage data, especially data that is critical to the decision making process. Online analytical processing (OLAP) queries take a long time to be processed, thus demanding high‐performance capabilities from their associated database systems to get results in a feasible time. In this article, we propose a middleware solution that can be deployed in any cloud provider, named C‐ParGRES, which explores database replication and interquery and intraquery parallelism to efficiently support OLAP queries in the cloud. C‐ParGRES is an extension of ParGRES, an open‐source database cluster middleware for high‐performance OLAP query processing in clusters. C‐ParGRES exploits cloud capabilities such as on‐demand resource provisioning and elasticity. In addition, C‐ParGRES can create multiple and independent virtual clusters for different database and users. We evaluate C‐ParGRES with two real‐world OLAP applications, both from the Brazilian Institute of Geography and Statistics. Results show that C‐ParGRES is a cost‐effective solution for OLAP query processing in the cloud.

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“…We obtained 17 papers related to 16 approaches. These papers were published in three distinct journals and seven distinct conferences and workshops.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

OLAP parallel query processing in clouds with C‐ParGRES

Ribeiro

Lima

Oliveira

2019

Concurrency and Computation

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“…The solution proposed in [10] is that of a dynamic B-tree indexing scheme that resides in the cloud. HSQL [11] similarly utilizes NoSQL databases to store a distributed B-tree. In [12], a tree-based structure is proposed that ensures database delete operations are external and permanent.…”

Section: Related Workmentioning

confidence: 99%

Cloud Tree: A Library to Extend Cloud Services for Trees

Tian

et al. 2015

2015 IEEE International Congress on Big Data

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Abstract-In this work, we propose a library that enables on a cloud the creation and management of tree data structures from a cloud client. As a proof of concept, we implement a new cloud service CloudTree. With CloudTree, users are able to organize big data into tree data structures of their choice that are physically stored in a cloud. We use caching, prefetching, and aggregation techniques in the design and implementation of CloudTree to enhance performance. We have implemented the services of Binary Search Trees (BST) and Prefix Trees as current members in CloudTree and have benchmarked their performance using the Amazon Cloud. The idea and techniques in the design and implementation of a BST and prefix tree is generic and thus can also be used for other types of trees such as B-tree, and other link-based data structures such as linked lists and graphs. Experimental results show that CloudTree is useful and efficient for various big data applications.

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“…Therefore, researchers began to study Hbase based on secondary indexes to meet the needs of retrieval according to theValue. At present, there are various programs of Hbase based on secondary indexes, such as ITHbase [1] based on MapReduce secondary indexes, Coprocessor [2] and Solr+Hbase [3], in which Coprocessor of Huawei is best known. It achieves more practical secondary indexes by cleverly constructing secondary indexes and combining with Coprocessor.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Management Mechanism Based on H-Index Secondary Indexes

Qin¹,

Xiong²,

Yuan³

2016

Proceedings of the 2016 International Symposium on Advances in Electrical, Electronics and Computer Engineering

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Hbase is a kind of non-relational database providing scalable technology methods and platform for managing big data, but it can only query through the primary key. This paper proposes a secondary index mechanism based on the heat value which derives from H-Index, a secondary index scheme of Huawei. It updates data regularly by tagging heat values of data on the secondary index, then it gets heat values together and combines with secondary index read caching strategies to improve query performance. Experimental results show that the proposed mechanism can reduce the average response time for data query.

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HSQL: A Highly Scalable Cloud Database for Multi-user Query Processing

Cited by 9 publications

References 1 publication

OLAP parallel query processing in clouds with C‐ParGRES

OLAP parallel query processing in clouds with C‐ParGRES

Cloud Tree: A Library to Extend Cloud Services for Trees

A Dynamic Management Mechanism Based on H-Index Secondary Indexes

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