By Jean-Marc Spaggiari, Kevin O'Dell
Lots of HBase books, on-line HBase courses, and HBase mailing lists/forums can be found if you would like to grasp how HBase works. but when you must take a deep dive into use circumstances, gains, and troubleshooting, Architecting HBase functions is the best resource for you.
With this booklet, you’ll research a managed set of APIs that coincide with use-case examples and simply deployed use-case versions, in addition to sizing/best practices to assist bounce commence your business software improvement and deployment.
- Learn layout patterns—and not only components—necessary for a profitable HBase deployment
- Go intensive into the entire HBase shell operations and API calls required to enforce documented use cases
- Become accustomed to the most typical matters confronted via HBase clients, establish the reasons, and comprehend the consequences
- Learn document-specific API calls which are difficult or extremely important for users
- Get use-case examples for each subject presented
Read or Download Architecting HBase Applications: A Guidebook for Successful Development and Design PDF
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Additional info for Architecting HBase Applications: A Guidebook for Successful Development and Design
Sample text
Counting from MapReduce The second way to count the number of rows in an HBase table is to use the Row‐ Counter MapReduce tool. The big benefit of using MapReduce to count your rows is HBase will create one mapper per region in your table. For a very big table this will distribute the work on multiple nodes to perform the count operation in parallel instead of scanning regions sequentially, which is what the shell’s count command does. RowCounter sensors Here is the most important part of the output and we will detail below the important fields to look at.
This is one of the HFiles we have initially created. By looking at the size of this file and by com‐ paring it to the initial HFiles created by the MapReduce job, we can match it to ch09/hfiles/v/ed40f94ee09b434ea1c55538e0632837. You can also look at the other regions and map them to the other input HFiles. Data validation Now that data is in the table we need to verify that it is expected. The first thing we will do is to make sure we have as many rows as expected. Then we will verify the records contain what we expect.
Table size Looking into an HFile using the HFilePrettyPrinter gives us the number of cells within a single HFile, but how many unique rows does it really represent? Since an HFile only represents a subset of rows, we need to count rows at the table level. HBase provides two different mechanisms to count the rows. 30 | Chapter 2: Underlying storage engine - Implementation Counting from the shell Counting the rows from the shell is pretty straightforward, simple, and efficient for small examples.