(PDF) APPROXIMATE QUERY PROCESSING …
In [1], the presented Approxima tion Query Processing Technique (AQPT) addresses four aggregate operations: Sum, Average, Variance and Standard Deviation. This AQPT is designed using Map …
Query processing in data-warehousing environments
Query processing in data-warehousing environments. Decision support, also known as On-Line Analytical Processing (OLAP) is a rapidly growing application of databases. OLAP systems involve processing complex aggregate queries on very large databases commonly called "data warehouses." Query response times can thus be very large for …
SAMPLING BASED JOIN-AGGREGATE QUERY PROCESSING TECHNIQUE FOR BIG DATA
non-join aggregate query as depicted in Query 1, for Big Data q ueries. Here, aggregate() denotes the aggregate function such as: Sum, Average, Variance, Standard Deviation et c. Additionally ...
Combining Aggregation and Sampling (Nearly) …
nearly 40 years of approximate query processing (AQP) research, where a database deliberately saces accuracy for faster [10, 27] or more resource-efficient results [29] for aggregate queries. Data sampling has been the primary approach used in AQP since the research area's conception [33]. To this day, there are
How to Aggregate Data in Power BI
Select the column you want to aggregate, and click "Group By" from the "Transform" tab. In the "Group By" dialog box, specify the column (s) you want to group your data by and the aggregation function (s) you want to apply, like SUM, AVERAGE, MAX, or MIN. Click "OK" to create your grouped data table. Export your grouped data ...
also aggregate data for query processing and the siz
Also Aggregate Data For Query Processing And The Siz Chapter 11 Flashcards | Quizlet A DBA determines the initial size of the data files Index is a measure of howdata mining formulas greenrevolution data hammer mills unit; also aggregate data for query processing and the siz; TON data systems mini sport computer; data aggregation …
What Is Aggregate Data?
It referred to data gathered and reported at the group, cohort, or institutional level and is aggregated using techniques that preserve each individual's anonymity. An aggregate analysis produces a summary of data from several sources. Collecting relevant data from various locations or data aggregation may provide valuable insights.
Cache-Based Aggregate Query Shipping: An Efficient …
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 …
Introduction to Query Processing | SpringerLink
Abstract. Query processing in databases can be divided into two steps: selecting an 'optimal' evaluation strategy, and executing it. We first present elementary nested loop and relational algebra algorithms for query execution and point out some opportunities for improving their performance.
Learn SQL: Aggregate Functions
We can notice a few things: 1 st query returned 8 rows. These are the same 6 rows as in a query using INNER JOIN and 2 more rows for countries that don't have any related city (Russia & Spain) ; 2 nd query counts the number of rows 1 st query returns, so this number is 8 ; 3 rd query has two important things to comment on. The first one is …
Approximate Query Processing: What is New and Where to Go? | Data
Online analytical processing (OLAP) is a core functionality in database systems. The performance of OLAP is crucial to make online decisions in many applications. However, it is rather costly to support OLAP on large datasets, especially big data, and the methods that compute exact answers cannot meet the high-performance …
Processing complex aggregate queries over data streams
This paper relies on randomizing techniques that compute small "sketch" summaries of the streams that can be used to provide approximate answers to aggregate queries with provable guarantees on the approximation error, and results indicate that sketches provide significantly more accurate answers compared to histograms for …
Combining Aggregation and Sampling (Nearly) …
nearly 40 years of approximate query processing (AQP) research, where a database deliberately saces accuracy for faster [10, 27] or more resource-efficient results [29] …
Accurate Aggregation Query-Result Estimation and Its
Given a query Q, we use pre-aggregated values for the grids that are completely included in the query range.This part follows the All-Scan method. On the other hand, for the surrounding grids, we use statistical data obtained from MHIST and KDE to estimate aggregation results (Fig. 2). We now discuss our two naïve methods for …
Approximately Processing Multi-granularity Aggregate Queries over Data
Aggregate monitoring over data streams is attracting more and more attention in research community due to its broad potential applications. Existing methods suffer two problems, 1) The aggregate functions which could be monitored are restricted to be first-order statistic or monotonic with respect to the window size.
AQP++: Connecting Approximate Query Processing With Aggregate
In the past, the database community has proposed two separate ideas, sampling-based approximate query processing (AQP) and aggregate precomputation (AggPre) such as data cubes, to address this challenge. In this paper, we argue for the need to connect these two separate ideas for interactive analytics.
Processing complex aggregate queries over data streams
There has been much recent interest in approximate query processing over data streams (a very small subset of these papers is listed in the References section [1, 21, 34]); even some work on ...
Efficient Aggregation Query Processing for Large-Scale
This method can also reduce the amount of data to be scanned on query processing by using the precomputed aggregation values. We implemented our method using PostgreSQL and HBase, and evaluated the insertion and query performances by comparing it to PostgreSQL, HBase, and MD-HBase which is an existing …
Optimizing Aggregate Query Processing in Cloud Data …
aggregate query processing. We analyzed some of the works which optimize the aggregate query operations. Along with that knowledge, we propose our storage …
How to Aggregate Data in Excel (Multiple Ways) | Layer Blog
4. In the Power Query Editor, go to Home > New Source > File to add data from a different file. How to Aggregate Data in Excel (Multiple Ways) - New File Source. 5. Select the file to import data from and then click on "Import". How to Aggregate Data in Excel (Multiple Ways) - Import New File Source. 6.
Optimizing Performance of Aggregate Query Processing …
In this paper, we study the characteristics of aggregate query, a typical type of analytical query, and proposed an approximate query processing approach to optimize the execution of massive data based aggregate query with a histogram data structure. We implemented this approach into big data system Hive and compare it with Hive and AQP …
Oracle Database In-Memory: In-Memory Aggregation
Introduction. Benefits of In-Memory Aggregation. Data Set Size, Concurrent Users and Query Complexity. Understanding In-Memory Aggregation Processing. Sample Query …
also aggregate data for query processing and the siz
A link-based storage scheme for efficient aggregate query ..., A link-based storage scheme for efficient aggregate query processing ... where Cptr denotes the size of a pointer to a data ... query log generation are also used ... Go to Product Center. Approximate Aggregate Query Processing: Olap, Approximate Aggregate Query Processing: ...
Approximately Processing Multi-granularity …
sic requirements of data stream processing, in this paper, we propose a novel approximate method for continuously mon-itoring a set of aggregate queries with different window size parameters over a data stream. 1.1 Related Work Monitoring and mining data stream has received consid-erable attention recently [13, 21, 8, 14, 5, 7, 20]. Klein-
Logical Query Processing Part 7: GROUP BY and HAVING
This article continues the series about logical query processing, which describes the logical, or conceptual, interpretation of queries. Part 1 provided an overview of the topic and also a sample database called TSQLV4.It also provided sample queries which I'll referred to as simple sample query and complex sample query.I'll use the …
Aggregate-Query Processing in Data Warehousing Environments
Aggregate-Query Processing in Data Warehousing Environments. Applied computing. Enterprise computing. Business process management. Human-centered computing. Human computer interaction (HCI) Interaction devices. Sound-based input / output. Information systems. Data management systems.
(PDF) APPROXIMATE QUERY PROCESSING TECHNIQUE FOR …
non-join aggregate query as depicted in Query 1, for Big Data q ueries. Here, aggregate() denotes the aggregate function such as: Sum, Average, Variance, Standard Deviation et c. Additionally ...
A secure paillier cryptosystem based privacy-preserving data …
The concept of data aggregation was introduced in 2010 and considers a gateway node to aggregate the smart meter data ... Proposed model is also used for query processing of smart meter data on outsourced cloud by the utility provider. Id-based and time-based queries are processed in the proposed work. ... Full size table.
Processing Complex Aggregate Queries over Data …
We now briefly describe the key elements of our generic archi- tecture for query processing over continuous data streams (depicted in Figure 1); similar architectures for stream processing have been described elsewhere (e.g., [4, 15]). Consider an arbitrary (possibly complex) SQL query Qover a set of relations R.
Optimal Linear Aggregate Query Processing under …
Given a batch of linear aggregate queries (called the workload), we aim to improve their overall ac-curacy by answering a different set of queries (called the strategy) under …