Hadoop Workflows and Distributed YARN Apps using Spring technologies

on YouTube ↗01h 27m

" summary

Shows how the Spring for Apache Hadoop project (using Spring Data, Integration, Batch and Boot) provides unified configuration and APIs for HDFS, MapReduce, Pig, Hive and Spark to simplify building Hadoop workflows and make them portable across Apache, Cloudera, Hortonworks and Pivotal distributions. Also demonstrates using Spring Cloud features—centralized configuration, leader election, distributed locks and distributed state—to build distributed applications that run on Hadoop YARN.

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" chapters (10)

1. 0:00Start
2. 1:19Spring for Apache Hadoop
3. 1:46Consistent Programming Model
4. 3:02Developer Productivity
5. 4:44Common Use Cases
6. 9:17Used in Spring XD and Spring Cloud Data Flow
7. 11:02What is new in 2.3?
8. 39:53Common issues with Hadoop Cloud Clusters
9. 41:08Connecting to Hadoop in a cloud environment
10. 42:34Use Hadoop with Cloud Foundry