Chapter 10. Data Collection with Flume
In the previous two chapters, we've seen how Hive and Sqoop give a relational database interface to Hadoop and allow it to exchange data with "real" databases. Although this is a very common use case, there are, of course, many different types of data sources that we may want to get into Hadoop.
In this chapter, we will cover:
- An overview of data commonly processed in Hadoop
- Simple approaches to pull this data into Hadoop
- How Apache Flume can make this task a lot easier
- Common patterns for simple through sophisticated, Flume setups
- Common issues, such as the data lifecycle, that need to be considered regardless of technology
A note about AWS
This chapter will discuss AWS less than any other in the book. In fact, ...
Get Hadoop: Data Processing and Modelling now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
