Best Practices for Implementing Continuous Streaming with Azure Databricks

Authors

  • Ravi Kiran Pagidi Independent Researcher, Jawaharlal Nehru Technological University, Hyderabad, India,
  • Jaswanth Alahari Independent Researcher, University of Illinois Springfield. , Nellore , Andhra Pradesh, India,
  • Aravind Ayyagiri Independent Researcher, Wichita State University, Yapral, Hyderabad, 500087,
  • Prof.(Dr) Punit Goel Research Supervisor , Maharaja Agrasen Himalayan Garhwal University, Uttarakhand,
  • Prof.(Dr.) Arpit Jain Independent Researcher , KL University, Vijaywada, Andhra Pradesh,
  • Er. Aman Shrivastav Independent Researcher , ABESIT Engineering College , Ghaziabad ,

DOI:

https://doi.org/10.36676/urr.v8.i4.1428

Keywords:

Continuous streaming, Azure Databricks, real-time data processing, Apache Spark, Delta Lake, data ingestion

Abstract

Continuous data streaming is essential for modern applications that require real-time processing of large data sets. Azure Databricks, a scalable data analytics platform, is widely used to implement such streaming systems. This paper presents best practices for implementing continuous streaming with Azure Databricks, focusing on key aspects such as architecture design, data ingestion, and stream processing optimization. The integration of Apache Spark within Databricks enables efficient, fault-tolerant stream processing at scale, making it ideal for handling high-throughput data streams.

Key considerations discussed include selecting appropriate data sources, leveraging Delta Lake for reliable data storage, and ensuring efficient stream processing through resource allocation and checkpointing. The paper emphasizes the importance of partitioning data to optimize processing performance and reduce latency, alongside monitoring and alerting strategies to maintain system health. Best practices for handling common challenges such as late data arrival, scaling out the infrastructure, and managing backpressure are also explored.

Furthermore, the use of Azure Databricks in conjunction with other Azure services, like Event Hubs and Azure Data Lake Storage, is highlighted to ensure seamless data flow across the streaming pipeline. Finally, security and compliance aspects are discussed, focusing on the secure handling of sensitive data during real-time processing.

This paper aims to provide a comprehensive guide for organizations looking to implement robust, scalable, and efficient continuous streaming solutions using Azure Databricks in various real-world scenarios

References

Karau, H., & Lee, J. (2016). Learning Spark: Lightning-Fast Data Analytics. O'Reilly Media.

Khattak, H. A., & Rauf, A. (2020). Performance analysis of real-time data processing with Apache Spark. Journal of Computer Networks and Communications, 2020, 1-9. https://doi.org/10.1155/2020/8836781

Kiran, R., & Saini, R. (2019). Comparative study of real-time data processing frameworks: Apache Spark vs. Apache Flink. International Journal of Engineering Research and Applications, 9(3), 1-6. https://doi.org/10.35629/7729-09030106

Lago, P., & Macias, M. (2019). Stream processing with Apache Spark: A performance study. Journal of Computer and Communications, 7(5), 20-30. https://doi.org/10.4236/jcc.2019.75003

Li, K., Wang, W., Li, Y., & Chen, X. (2018). A review on real-time stream processing systems. ACM Computing Surveys, 51(5), 1-36. https://doi.org/10.1145/3242539

Lin, J. (2017). Spark: The Definitive Guide: Big Data Processing Made Simple. O'Reilly Media.

Mehfuz, H., & Ramli, A. (2016). Exploring the challenges of big data analytics in streaming data. International Journal of Computer Applications, 139(6), 19-23. https://doi.org/10.5120/ijca2016909469

Microsoft. (2019). Azure Databricks documentation. Microsoft Docs. Retrieved from https://docs.microsoft.com/en-us/azure/databricks/

Nair, R. S., & Ramachandran, M. (2019). Enhancing real-time analytics with Azure Databricks. Journal of Cloud Computing: Advances, Systems and Applications, 8(1), 1-12. https://doi.org/10.1186/s13677-019-0130-3

O'Reilly, T. (2015). What is the future of big data? Harvard Business Review. Retrieved from https://hbr.org/2015/03/what-is-the-future-of-big-data

Pande, S., & Sharma, A. (2018). An overview of streaming analytics and its applications. International Journal of Computer Applications, 182(27), 10-15. https://doi.org/10.5120/ijca2018917268

Pires, A., & Ferreira, C. (2020). Performance evaluation of Azure Databricks in big data processing. Journal of Computer Science and Technology, 35(2), 283-293. https://doi.org/10.1007/s11390-020-00070-3

Reddy, P. K., & Kumar, K. B. S. (2016). Data stream processing: A survey. International Journal of Computer Applications, 135(10), 1-7. https://doi.org/10.5120/ijca2016909828

Singh, A., & Singh, M. (2019). Understanding the big data analytics with Apache Spark. Journal of Big Data, 6(1), 1-12. https://doi.org/10.1186/s40537-019-0198-7

Stonebraker, M., & Cetintemel, U. (2016). "One Size Fits All": An idea whose time has come and gone. Proceedings of the 2016 ACM International Conference on Management of Data, 1-6. https://doi.org/10.1145/2914898.2914937

Tzeng, J. M., & Wang, Y. (2020). A performance study of Apache Spark for large-scale data processing. Future Generation Computer Systems, 108, 832-842. https://doi.org/10.1016/j.future.2019.05.033

CHANDRASEKHARA MOKKAPATI, Shalu Jain, & Shubham Jain. "Enhancing Site Reliability Engineering (SRE) Practices in Large-Scale Retail Enterprises". International Journal of Creative Research Thoughts (IJCRT), Volume.9, Issue 11, pp.c870-c886, November 2021. http://www.ijcrt.org/papers/IJCRT2111326.pdf

Arulkumaran, Rahul, Dasaiah Pakanati, Harshita Cherukuri, Shakeb Khan, & Arpit Jain. (2021). "Gamefi Integration Strategies for Omnichain NFT Projects." International Research Journal of Modernization in Engineering, Technology and Science, 3(11). doi: https://www.doi.org/10.56726/IRJMETS16995.

Agarwal, Nishit, Dheerender Thakur, Kodamasimham Krishna, Punit Goel, & S. P. Singh. (2021). "LLMS for Data Analysis and Client Interaction in MedTech." International Journal of Progressive Research in Engineering Management and Science (IJPREMS), 1(2): 33-52. DOI: https://www.doi.org/10.58257/IJPREMS17.

Alahari, Jaswanth, Abhishek Tangudu, Chandrasekhara Mokkapati, Shakeb Khan, & S. P. Singh. (2021). "Enhancing Mobile App Performance with Dependency Management and Swift Package Manager (SPM)." International Journal of Progressive Research in Engineering Management and Science, 1(2), 130-138. https://doi.org/10.58257/IJPREMS10.

Vijayabaskar, Santhosh, Abhishek Tangudu, Chandrasekhara Mokkapati, Shakeb Khan, & S. P. Singh. (2021). "Best Practices for Managing Large-Scale Automation Projects in Financial Services." International Journal of Progressive Research in Engineering Management and Science, 1(2), 107-117. doi: https://doi.org/10.58257/IJPREMS12.

Salunkhe, Vishwasrao, Dasaiah Pakanati, Harshita Cherukuri, Shakeb Khan, & Arpit Jain. (2021). "The Impact of Cloud Native Technologies on Healthcare Application Scalability and Compliance." International Journal of Progressive Research in Engineering Management and Science, 1(2): 82-95. DOI: https://doi.org/10.58257/IJPREMS13.

Voola, Pramod Kumar, Krishna Gangu, Pandi Kirupa Gopalakrishna, Punit Goel, & Arpit Jain. (2021). "AI-Driven Predictive Models in Healthcare: Reducing Time-to-Market for Clinical Applications." International Journal of Progressive Research in Engineering Management and Science, 1(2): 118-129. DOI: 10.58257/IJPREMS11.

Agrawal, Shashwat, Pattabi Rama Rao Thumati, Pavan Kanchi, Shalu Jain, & Raghav Agarwal. (2021). "The Role of Technology in Enhancing Supplier Relationships." International Journal of Progressive Research in Engineering Management and Science, 1(2): 96-106. doi:10.58257/IJPREMS14.

Mahadik, Siddhey, Raja Kumar Kolli, Shanmukha Eeti, Punit Goel, & Arpit Jain. (2021). "Scaling Startups through Effective Product Management." International Journal of Progressive Research in Engineering Management and Science, 1(2): 68-81. doi:10.58257/IJPREMS15.

Arulkumaran, Rahul, Shreyas Mahimkar, Sumit Shekhar, Aayush Jain, & Arpit Jain. (2021). "Analyzing Information Asymmetry in Financial Markets Using Machine Learning." International Journal of Progressive Research in Engineering Management and Science, 1(2): 53-67. doi:10.58257/IJPREMS16.

Agarwal, Nishit, Umababu Chinta, Vijay Bhasker Reddy Bhimanapati, Shubham Jain, & Shalu Jain. (2021). "EEG Based Focus Estimation Model for Wearable Devices." International Research Journal of Modernization in Engineering, Technology and Science, 3(11): 1436. doi: https://doi.org/10.56726/IRJMETS16996.

Kolli, R. K., Goel, E. O., & Kumar, L. (2021). "Enhanced Network Efficiency in Telecoms." International Journal of Computer Science and Programming, 11(3), Article IJCSP21C1004. rjpn ijcspub/papers/IJCSP21C1004.pdf.

Eeti, E. S., Jain, E. A., & Goel, P. (2020). Implementing data quality checks in ETL pipelines: Best practices and tools. International Journal of Computer Science and Information Technology, 10(1), 31-42. https://rjpn.org/ijcspub/papers/IJCSP20B1006.pdf

"Effective Strategies for Building Parallel and Distributed Systems". International Journal of Novel Research and Development, Vol.5, Issue 1, page no.23-42, January 2020. http://www.ijnrd.org/papers/IJNRD2001005.pdf

"Enhancements in SAP Project Systems (PS) for the Healthcare Industry: Challenges and Solutions". International Journal of Emerging Technologies and Innovative Research, Vol.7, Issue 9, page no.96-108, September 2020. https://www.jetir.org/papers/JETIR2009478.pdf

Venkata Ramanaiah Chintha, Priyanshi, & Prof.(Dr) Sangeet Vashishtha (2020). "5G Networks: Optimization of Massive MIMO". International Journal of Research and Analytical Reviews (IJRAR), Volume.7, Issue 1, Page No pp.389-406, February 2020. (http://www.ijrar.org/IJRAR19S1815.pdf)

Cherukuri, H., Pandey, P., & Siddharth, E. (2020). Containerized data analytics solutions in on-premise financial services. International Journal of Research and Analytical Reviews (IJRAR), 7(3), 481-491. https://www.ijrar.org/papers/IJRAR19D5684.pdf

Sumit Shekhar, Shalu Jain, & Dr. Poornima Tyagi. "Advanced Strategies for Cloud Security and Compliance: A Comparative Study". International Journal of Research and Analytical Reviews (IJRAR), Volume.7, Issue 1, Page No pp.396-407, January 2020. (http://www.ijrar.org/IJRAR19S1816.pdf)

"Comparative Analysis of GRPC vs. ZeroMQ for Fast Communication". International Journal of Emerging Technologies and Innovative Research, Vol.7, Issue 2, page no.937-951, February 2020. (http://www.jetir.org/papers/JETIR2002540.pdf)

Singh, S. P. & Goel, P. (2009). Method and Process Labor Resource Management System. International Journal of Information Technology, 2(2), 506-512.

Goel, P., & Singh, S. P. (2010). Method and process to motivate the employee at performance appraisal system. International Journal of Computer Science & Communication, 1(2), 127-130.

Goel, P. (2012). Assessment of HR development framework. International Research Journal of Management Sociology & Humanities, 3(1), Article A1014348. https://doi.org/10.32804/irjmsh

Goel, P. (2016). Corporate world and gender discrimination. International Journal of Trends in Commerce and Economics, 3(6). Adhunik Institute of Productivity Management and Research, Ghaziabad.

Eeti, E. S., Jain, E. A., & Goel, P. (2020). Implementing data quality checks in ETL pipelines: Best practices and tools. International Journal of Computer Science and Information Technology, 10(1), 31-42. https://rjpn.org/ijcspub/papers/IJCSP20B1006.pdf

"Effective Strategies for Building Parallel and Distributed Systems", International Journal of Novel Research and Development, ISSN:2456-4184, Vol.5, Issue 1, page no.23-42, January-2020. http://www.ijnrd.org/papers/IJNRD2001005.pdf

"Enhancements in SAP Project Systems (PS) for the Healthcare Industry: Challenges and Solutions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 9, page no.96-108, September-2020, https://www.jetir.org/papers/JETIR2009478.pdf

Venkata Ramanaiah Chintha, Priyanshi, Prof.(Dr) Sangeet Vashishtha, "5G Networks: Optimization of Massive MIMO", IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348-1269, P- ISSN 2349-5138, Volume.7, Issue 1, Page No pp.389-406, February-2020. (http://www.ijrar.org/IJRAR19S1815.pdf )

Cherukuri, H., Pandey, P., & Siddharth, E. (2020). Containerized data analytics solutions in on-premise financial services. International Journal of Research and Analytical Reviews (IJRAR), 7(3), 481-491 https://www.ijrar.org/papers/IJRAR19D5684.pdf

Sumit Shekhar, SHALU JAIN, DR. POORNIMA TYAGI, "Advanced Strategies for Cloud Security and Compliance: A Comparative Study", IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348-1269, P- ISSN 2349-5138, Volume.7, Issue 1, Page No pp.396-407, January 2020. (http://www.ijrar.org/IJRAR19S1816.pdf )

"Comparative Analysis OF GRPC VS. ZeroMQ for Fast Communication", International Journal of Emerging Technologies and Innovative Research, Vol.7, Issue 2, page no.937-951, February-2020. (http://www.jetir.org/papers/JETIR2002540.pdf )

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Published

2021-12-30
CITATION
DOI: 10.36676/urr.v8.i4.1428
Published: 2021-12-30

How to Cite

Ravi Kiran Pagidi, Jaswanth Alahari, Aravind Ayyagiri, Prof.(Dr) Punit Goel, Prof.(Dr.) Arpit Jain, & Er. Aman Shrivastav. (2021). Best Practices for Implementing Continuous Streaming with Azure Databricks. Universal Research Reports, 8(4), 268–292. https://doi.org/10.36676/urr.v8.i4.1428

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