Big Data Processing-Beyond Batch Processing
S.Anuradha1, L.Srinivasa Rao2, G.Raghu Ram3
1S.Anuradha*, PG Student, CSE Dept., Mother Teresa Institute of Science & Technology, Sathupalli, Khammam Dt., JNTU, Hyderabad, Telengana State, India.
2L.Srinivasa Rao, 2Assoc.Professor CSE Dept., Mother Teresa Institute of Science & Technology, Sathupalli, Khammam Dt., JNTU Hyderabad, Telengana State, India.
3G.RaghuRam, Assoc.Professor & PRO CSE Dept., G.Pulla Reddy Engineering College, Kurnool, Andhra Pradesh, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 2221-2224 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7903118419/2019©BEIESP | DOI: 10.35940/ijrte.D7903.118419

Open Access | Ethics and Policies | Cite  | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: This paper mainly focus on analysis of large sets of students data with one of the batch processing analysis techniques Beyond batch process, analysis of data streaming is done based on program of word counting program which executes data with HDFS along with dynamic created data. To compute similar coherent strategies one can implement a schema named batch and streaming process which dynamically creates data. The architecture is reduced to serve as X-Platform which uses ample number of tools for batch and stream analysis on this proposed frame work. Here we use spark-sql, a query language which acts as interface for interactive process to have iterative processes. Real time streaming data processing involves spark streaming works. Here we focus on preliminary evaluation of results and analysis report which compares data sets performance and also achieve low latency rate with usage of RDD.
Keywords: HDFS, Coherent strategies, X-Platform, SQL-Spark.s.
Scope of the Article: Big Data Security.