 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: March 2026
Volume 11 | Issue 3
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21604
Article Published : 8531
Total Authors : 22438
Total Reviewer : 805
Total Countries : 159
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Multi Instance Task in Data Stream Management System |
| Authors Name: | Swapna Vanguru , R Suhasini |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_183840
|
| Published Paper Id: | IJRTI2209020 |
| Published In: | Volume 7 Issue 9, September-2022 |
| DOI: | |
| Abstract: | Now a days “Big data” is became part of the day. It is a collection of data sets so large and complex that it becomes difficult to process, manage, and analyse data in a just-in-time manner. The rapid growth in the amount of data created in the world continues to accelerate and surprise us. Moreover, big data is more complicated to handle efficiently. In a data stream management system (DSMS), multi-task in a service and multi-instance in a task are commonly used. In other words, a service is composed of input, output, and tasks: The input constantly reads new messages and emits them to the stream. The output is also written streams in the specified format (e.g., a file). A task is executed often in response to newly arrived stream from the input or previous task emission. When a task would interfere with processing in other tasks, the task must be necessary to run multiple copies of the source (i.e., a single task). So, a single task splits multi-instance where resides in physical instances. Today, there are many big data processing frameworks to handle large volume of big data. In this paper, we will discuss in top level projects of the Apache Software Foundation (ASF), is a general-purpose data processing platform. They have a wide field of application and are usable for dozens of big data scenarios. Apache Spark is based on resilient distributed datasets(RDDs). This in-memory data structure gives the power to sparks functional programming paradigm. It is capable of big batch calculations by pinning memory. Especially, Spark Streaming wraps data streams into mini-batches. It collects all data that arrives within a certain period of time and runs a regular batch program on the collected data. While the batch program is running, the data for the next mini-batch is collected. |
| Keywords: | data, streaming,framework |
| Cite Article: | "Multi Instance Task in Data Stream Management System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 9, page no.157 - 161, September-2022, Available :http://www.ijrti.org/papers/IJRTI2209020.pdf |
| Downloads: | 000205219 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2209020
Registration ID:183840
Published In: Volume 7 Issue 9, September-2022
DOI (Digital Object Identifier):
Page No: 157 - 161 Country: Malkajigiri, Telanagana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2209020 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2209020 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||