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Walking Through Spring Cloud Data Flow
This document provides an overview and safe harbor statement for the "Walking Through Spring Cloud Data Flow" presentation at SpringOne 2020. It outlines that any information provided is intended for informational purposes only and is subject to change. The presentation will cover topics like Spring Cloud Stream for event-driven applications, Spring Cloud Task for batch applications, application development, deployment and monitoring using Spring Cloud Data Flow. It also provides details about the presenters and includes a sample demo data.
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Walking Through Spring Cloud Data Flow
- 1. Walking Through Spring CloudData Flow September 2–3, 2020 springone.io
- 2. Safe Harbor Statement Thefollowing is intended to outline the general direction of VMware's offerings. It is intended for information purposes only and may not be incorporated into any contract. Any information regarding pre-release of VMware offerings, future updates or other planned modifications is subject to ongoing evaluation by VMware and is subject to change. This information is provided without warranty or any kind, express or implied, and is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions regarding VMware's offerings. These purchasing decisions should only be based on features currently available. The development, release, and timing of any features or functionality described for VMware's offerings in this presentation remain at the sole discretion of Pivotal. Pivotal has no obligation to update forward looking information in this presentation. 2
- 3. 3 Glenn Renfro Twitter: @cppwfs Github:github.com/cppwfs Ilayaperumal Gopinathan Twitter: @ilayaperumalg Github: github.com/ilayaperumalg
- 4. Data In theEnterprise
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- 9. Application Development Spring CloudStream Event-driven, long-lived streaming apps Spring Cloud Task Ephemeral, batch apps Continuous Integration Kubernetes / Cloud Foundry Message Broker / / / / / Application Deployment Streaming applications Task (batch) applications Monitor Performance Track Lifecycle Deploy Streams Orchestration using Spring Cloud Data Flow Launch Jobs
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- 14. What’s New! Single StepBatch Job Auto Configuration
- 15. @EnableBatchProcessing @EnableTask @Configuration public class MyBatchConfiguration{ … @Bean public Job myBatchJob(Step step) { return jobBuilderFactory.get(this.properties.getJobName()). … } … @Bean public ItemReader<Map<Object, Object>> itemReader() { return new JdbcCurserItemReaderBuilder(). … } @Bean public ItemWriter<Map<Object,Object>> itemWriter(DataSource dataSource) { return new JdbcBatchItemWriterBuilder<Map<Object, Object>>(). … }
- 16. What’s New! Single StepBatch Job Auto Configuration spring.batch.job.jobName=job spring.batch.job.stepName=step1 spring.batch.job.chunkSize=5 spring.batch.job.jdbccursorreader.name=fooReader spring.batch.job.jdbccursorreader.sql=select item_name from item_sample spring.batch.job.jdbcwriter.name=jdbcWriter spring.batch.job.jdbcwriter.sql=INSERT INTO item (item_name) VALUES (:ITEM_NAME) <dependency> <groupId>org.springframework.cloud</groupId> <artifactId>spring-cloud-starter-single-step-batch-job</artifactId> </dependency>
- 17. What’s new! Spring CloudData Flow OSS • 2.6.1 RELEASE ● Task Improvements ● OOTB Functional applications ● Wavefront monitoring support ● Multi platform scheduling support ● Bitnami helm charts for SCDF
- 18. Commercial Offering Spring CloudData Flow For Kubernetes • Built on top of SCDF OSS • SCDF Pro Server and Pro Dashboard UI • Packaging • Certified Container Images • Image Relocation • Provisioning of SCDF components • Multi IO Stream DSL and Editor
- 21. What’s Up Next! SpringCloud Data Flow OSS • 2.7.0 in the works ○ Dashboard redesign using Clarity ○ Observability support ○ Single Step Batch Job support
- 22. What’s Up Next! SpringCloud Data Flow for Kubernetes (SCDF4K8s) • Container Registry Integration • Single Step Batch Job Auto Config • Multi IO support enhancements
- 23. Want to learnmore? #springone@s1p SCDF microsite SCDF for Kubernetes
- 24. Stay Connected. https://springone.io/2020/sessions/iot-scale-event-stream-processing-for- predictive-maintenance-at-penske #springone@s1p IoT ScaleEvent-Stream Processing for Predictive Maintenance at Penske