Connecting Approximate Query Processing With Aggregate Precomputa-tion for Interactive Analytics. In SIGMOD’18: 2018 International Conference on Management of Data, June 10–15, 2018, Houston, TX, USA. ACM, New York, NY,
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· This paper proposes AQP++, a novel framework that achieves a more flexible and better trade-off among preprocessing cost, query response time, and answer quality than AQP or AggPre. Interactive analytics requires database systems to be able to answer aggregation queries within interactive response times. As the amount of data is
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:Yuxiang Wang, Yixing Xia, Qiming Fang, Xiaoliang XuPublish Year:2017We propose AQP++, a novel framework to enable the connection. The framework can leverage both a sample as well as a precomputed aggregate to answer user queries.
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AggregateResult is a read-only sObject and is only used for query results. Aggregate functions become a more powerful tool to generate reports when you use them with a GROUP BY clause. For example, you could find the average Amount for all your opportunities by campaign. AggregateResult[] groupedResults. = [SELECT CampaignId,
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· Recent approaches for approximate query processing make use of pre-computed aggregates or sampling, or a combination of both, for a more accurate question answering [16]- [18].Pure sampling-based
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SQL Aggregate Functions An aggregate function is a function that performs a calculation on a set of values, and returns a single value. Aggregate functions are often used with the GROUP BY clause of the SELECT statement. The GROUP BY clause splits the result-set into groups of values and the aggregate function can be used to return a single value for
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Sampling based approximate query processing and aggregate precomputation are the two methods proposed in the past to try to solve this problem. During interactive queries, the database will produce a large number of materialized views, and the queries on certain data sets are usually concentrated in practice, which makes the query results reusable.
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· Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing. Xi Liang, Stavros Sintos, Zechao Shang, Sanjay Krishnan. Sample-based approximate query processing (AQP) suffers from many pitfalls such as the inability to answer very selective queries and unreliable confidence intervals when sample sizes
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· For the purpose of reusing results of queries with aggregate function in distributed query processing, a multi-level hybrid view caching (HVC) scheme is introduced. The scheme retains the advantages of partial match and aggregate query results caching.
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· Worst-case optimal algorithms for parallel query processing. In Proc. International Conference on Database Theory, 2016. Google Scholar P. Koutris, S. Salihoglu, and D. Suciu. Algorithmic Aspects of Parallel Data Processing. Now Publishers, 2018. P. Koutris
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· This paper is about anti-tamper databases, where the database contents are encrypted for security in a way to allow efficient query processing directly on the encrypted database without decrypting it. We use a family of openform and closed-form homomorphism encryption/decryption functions and a computing architecture where (a)
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Approximate Query Processing Based on Approximate Materialized View. Abstract. In the context of big data, the interactive analysis database system needs to answer aggregate queries within a reasonable response time. The proposed AQP++ framework can integrate data preprocess-ing and AQP.
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This paper proposes a multi-attribute aggregation query mechanism in the context of edge computing, where an energy-aware IR-tree is constructed to process query processing in single edge networks, while an edge node routing graph is es-tablished to facilitate query processing for marginal smart things contained in contiguous edge networks. This in
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· Approximate Query Processing, Online Aggregation, OLAP, Big data 1 INTRODUCTION In recent world, there is an explosive growth in volume of data in various elds such as medical sectors, government
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Aggregate-Query Processing in Data Warehousing Environments*. Ashish Gupta Venky Harinarayan Dallan Quass. IBM Almaden Research Center. Abstract. In this paper we introduce generalized pro-. jections (GPs), an extension of duplicate- eliminating projections, that capture aggre- gations, groupbys, duplicate-eliminating pro- jections (distinct
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A multi-level hybrid view caching (HVC) scheme is introduced for the purpose of reusing results of queries with aggregate function in distributed query processing, and evaluations with distributed TPC-H queries show significant improvement on average response time. Our study introduces a novel distributed query plan refinement phase in an enhanced
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Relational aggregate query processing techniques for real-time databases. In this thesis, a new query processing technique is proposed to cut down systematically the time involved in processing aggregate relational algebra queries in relational databases. We use data samples and statistical methods to construct an approximate response to a
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· To remedy this issue, this paper proposes a processing technique for aggregated Boolean queries in the context of edge computing, where each sub-region of the network corresponds to an
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Applies to: SQL Server Azure SQL Database Azure SQL Managed Instance. The SQL Server Database Engine processes queries on various data storage architectures such as local tables, partitioned tables, and tables distributed across multiple servers. The following sections cover how SQL Server processes queries and optimizes query reuse through
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: Xi Liang, Stavros Sintos, Zechao Shang, Sanjay KrishnanIn this paper, we study and optimize the aggregate query processing in a highly distributed Cloud Data Warehouse, where each database stores a subset of relational data in a star
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:Swathi Kurunji, Tingjian Ge, Xinwen Fu, Benyuan Liu, Amrith Kumar, Cindy X. Chen · A sampling-based approximate query processing (AQP) method provides a fast way for users to obtain a trade-off between accuracy and time consumption by
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Abstract. We consider those database environments in which queries have strict timing constraints, and develop a time-constrained query evaluation methodology. For
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· A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data
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· {Day87} Umeshwar Dayal: Of Nests and Trees: A Unified Approach to Processing Queries That Contain Nested Subqueries, Aggregates, and Quantifiers. VLDB 1987: 197-208. Google Scholar Digital Library {G93}
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Aggregate query processing Among the aggregate operations, count is an im-portant one. We will present an algorithm for proc-essing the count operation and discuss how to im-plement the other aggregate operations. Int. Computer Symposium, Dec. 15-17 <A1
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In this paper, we propose an Eficient Spatial-Temporal range Aggregation query processing (ESTA) algorithm for UAV networks. First, a topology change graph is constructed based on the pre-planned trajectory information. Meanwhile, an eficient shortest path algorithm is proposed to obtain the user query delay.
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· Our study introduces a novel distributed query plan refinement phase in an enhanced architecture of distributed query processing engine (DQPE). Query plan refinement generates potentially efficient distributed query plan by reusable aggregate query shipping (RAQS) approach. The approach improves response time at the cost of
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· This paper points out that under differential privacy, the optimal strategy for answering an arbitrary batch of linear aggregate queries can be found, rather surprisingly, by solving a simple and elegant convex optimization program and proposes a efficient algorithm based on Newton's method, which proves t always converge to the optimal
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· Online aggregation-based AQP progressively generates approximate results with some error estimates (i.e., confidence interval) until the processing of all data is done. In Offline synopsis generation-based AQP, synopses are generated offline using a
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Processing Aggregate Queries with Materialized Views in Data Warehouse Environment Materialized views, which are derived from base relations and stored in the database, offer opportunities for significant performance gain in query evaluation by providing quick access to the pre-computed data.
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