Automate Spark Jobs Using Oozie

Mike Grimes shows how to use Oozie to automate Hadoop and Spark jobs:

This problem is easy to solve, right? You can write scripts that run jobs in sequence, and use the output of one program as the input to another—no problem. But what if your workflow is complex and requires specific triggers, such as specific data volumes or resource constraints, or must meet strict SLAs? What if parts of your workflow don’t depend on each other and can be run in parallel?

Building your own infrastructure around this problem can seem like an attractive idea, but doing so can quickly become laborious. If, or rather when, those requirements change, modifying such a tool isn’t easy . And what if you need monitoring around these jobs? Monitoring requires another set of tools and headaches.

This is a pretty detailed look at the basics of Oozie.

Related Posts

It’s All ETL (Or ELT) In The End

Robin Moffatt notes that ETL (and ELT) doesn’t go away in a streaming world: In the past we used ETL techniques purely within the data-warehousing and analytic space. But, if one considers why and what ETL is doing, it is actually a lot more applicable as a broader concept. Extract: Data is available from a source system Transform: We […]

Read More

Flint: Time Series With Spark

Li Jin and Kevin Rasmussen cover the concepts of Flint, a time-series library built on Apache Spark: Time series analysis has two components: time series manipulation and time series modeling. Time series manipulation is the process of manipulating and transforming data into features for training a model. Time series manipulation is used for tasks like data […]

Read More

Categories

June 2016
MTWTFSS
« May Jul »
 12345
6789101112
13141516171819
20212223242526
27282930