InfoQ Homepage Batch Processing Content on InfoQ
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Batch Processing in 2019
Michael Minella and Mahmoud Ben Hassine walk through the typical lifecycle of a batch job using modern tools.
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Peloton - Uber's Webscale Unified Scheduler on Mesos & Kubernetes
Mayank Bansal and Apoorva Jindal present Peloton, a Unified Resource Scheduler for collocating heterogeneous workloads in shared Mesos clusters.
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High Performance Batch Processing
Mahmoud Ben Hassine and Michael Minella walk through performance tuning and scaling Spring Batch applications via the enhancements of 4.1.
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Case Study of Batch Processing with Spring Cloud Data Flow Server in Cloud Foundry
Bruce Thelen discusses how CoreLogic implemented a batch processing system on Pivotal Cloud Foundry with Spring Cloud Data Flow Server, Spring Task, and Spring Batch.
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Cloud-Native Batch Processing with Spring Batch 4
Michael Minella discusses what’s new in Spring Batch 4 and how to use it in a cloud setting.
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Get Off the Bus, Gus: 50 Ways to Leave Your Mainframe
Rohit Kelapure provides guidance and best practices in migrating monolithic mainframe apps and data including JCLs wrapped in CICS and IMS using Spring components like Spring Data Flow, Cloud, Batch.
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Elements of Scale
Ben Stopford examines tools, mechanisms and tradeoffs that allow a data architecture to scale, from disk formats to fully blown architectures for real-time storage, streaming and batch processing.
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Java EE 7 Using Eclipse
Arun Gupta explains how to do Java EE 7 development with Eclipse, leveraging the new APIs - WebSocket, Batch, JSON Processing, and Concurrency Utilities.
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API Abstraction and API Chaining in Grails
Owen Rubel discusses the benefits of API abstraction: easier externalization, synchronization and sharing, reloading the API config on the fly, DRY'r code, batching, reduced throughput and much more.
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Remote Access Made Easy and Fast with Haskell
Simon Marlow explains how to use Haxl to automatically batch and overlap requests for data from multiple data sources.
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Building a Recommendation Engine with Spring and Hadoop
Michael Minella uses Spring XD and Spring Batch to orchestrate the full lifecycle of Hadoop processing and uses Apache Mahout to provide the audience with the recommendation processing.
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Spring Batch Performance Tuning
Gunnar Hillert and Chris Schaefer examine various scalability options in order to improve the robustness and performance of the Spring Batch applications.
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