Data Ingestion using a Novel Method: H-Stream Framework
Gunturi S. Raghavendra1, Shanthi Mahesh2, M. V. P. Chandrasekhara Rao3
1Gunturi S. Raghavendra*, Department of CSE, Atria Institute of Technology, Bangalore, India.
2Dr. Shanthi Mahesh, *, Department of ISE, Atria Institute of Technology, Bangalore, India.
3Dr. M. V. P. Chandrasekhara Rao*, Department of CSE, R.V.R & J.C College of Engineering, Guntur, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 1945-1949 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6045018520/2020©BEIESP | DOI: 10.35940/ijrte.E6045.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Current huge volumes of data is generated from wide variety of data sources and there is lot of demand for processing, this data. Apache Hadoop is designed for batch processing. Though Hadoop is used for batch processing there is lot of requirement for real time stream processing and querying on unstructured data. Data ingestion tools of Hadoop are playing a key role in processing of streamed log data. With the increase of volume of the data performance of data ingestion tools goes down linearly. In this paper we discuss solutions for performance issues of data ingestion tools, capturing and processing of streamed multimedia data along with real-time stream processing with the help of frame work known as H-Stream framework. (Abstract)
Keywords: Ingestion, Kera, Frame work, Lambda, H-stream
Scope of the Article: Patterns and frameworks.