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 want to understand how HBase works. but when you need to take a deep dive into use circumstances, positive aspects, and troubleshooting, Architecting HBase functions is the perfect resource for you.
With this ebook, you’ll examine a managed set of APIs that coincide with use-case examples and simply deployed use-case types, in addition to sizing/best practices to assist bounce commence what you are promoting 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 conversant in the commonest matters confronted by means of HBase clients, establish the factors, and comprehend the consequences
- Learn document-specific API calls which are tough or vitally important for users
- Get use-case examples for each subject presented
Read Online or Download Architecting HBase Applications: A Guidebook for Successful Development and Design PDF
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Extra resources for Architecting HBase Applications: A Guidebook for Successful Development and Design
To summarize, we have validated the size of the HFiles, their format, the num‐ bers of entries in the HFiles and in the table, and the table content itself. We can now confirm that our data has been correctly and fully loaded into the table. Data indexing The next and last step of the implementation consists of indexing the table we have just loaded, to be able to quickly search for any of the records using SOLR. Indexation is an incremental process. Indeed, Omneo receive new files daily. As seen in the pre‐ vious chapter, data from those files is loaded into a main table which contains data from the previous days, and an indexation table.
Try to modify the create table statement to have a single region and load more than 10GB of data into it. You should see the region splitting after the data is inserted, however, since we are using bulkload, you should still not see any hotspot‐ ting on this region. You can validate your tables splits and the content of each region by looking in HDFS has seen in “Bulk loading” on page 29 Impact on table parameters We have created our table using the parameters which are good for our current usecase.
Now let’s have a look at the mapper. Goal of the mapper is to read the content from HBase and translate it for SOLR. We have already done a class to create an Avro 36 | Chapter 2: Underlying storage engine - Implementation object from an HBase cell. We are going to reuse the same code here as this is exactly what we want to achieve. We want to read each and every cell, convert it back to an Avro object and provide to SOLR the data we want to index. The code for that is the following: Example 2-6.