hbase

Topics: Hadoop, Java, Representational State Transfer Pages: 22 (2218 words) Published: November 3, 2014
© 2012 coreservlets.com and Dima May

HBase Overview
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Agenda





Overview
Data Model
Architecture
Resources

4

HBase
• Column-Oriented data store, known as
“Hadoop Database”
• Supports random real-time CRUD
operations (unlike HDFS)
• Distributed – designed to serve large tables
– Billions of rows and millions of columns

• Runs on a cluster of commodity hardware
– Server hardware, not laptop/desktops

• Open-source, written in Java
• Type of “NoSQL” DB
5

– Does not provide a SQL based access
– Does not adhere to Relational Model for storage

HBase
• Horizontally scalable
– Automatic sharding







Strongly consistent reads and writes
Automatic fail-over
Simple Java API
Integration with Map/Reduce framework
Thrift, Avro and REST-ful Web-services

6

HBase
• Based on Google's Bigtable
– http://labs.google.com/papers/bigtable.html

• Just like BigTable is built on top of Google
File System (GFS), HBase is implemented
on top of HDFS

7

HBase History
0.92 release
Apache top-level project
Hadoop’s sub project
Hadoop’s contrib
BigTable paper

2006

2007

2008

2010

2011

Source: Lars, George. HBase The Definitive Guide. O'Reilly Media. 2011

8

Who Uses HBase?
• Here is a very limited list of well known
names









9

Facebook
Adobe
Twitter
Yahoo!
Netflix
Meetup
Stumbleupon
You????

When To Use HBase
• Not suitable for every problem
– Compared to RDBMs has VERY simple and limited API

• Good for large amounts of data
– 100s of millions or billions of rows
– If data is too small all the records will end up on a single node leaving the rest of the cluster idle

10

When To Use HBase
• Have to have enough hardware!!
– At the minimum 5 nodes
• There are multiple management daemon processes:
Namenode, HBaseMaster, Zookeeper, etc....
• HDFS won't do well on anything under 5 nodes anyway;
particularly with a block replication of 3
• HBase is memory and CPU intensive

• Carefully evaluate HBase for mixed work
loads
– Client Request vs. Batch processing (Map/Reduce)
• SLAs on client requests would need evaluation

– HBase has intermittent but large IO access
• May affect response latency!!!
11

When to Use HBase
• Two well-known use cases
– Lots and lots of data (already mentioned)
– Large amount of clients/requests (usually cause a lot of data)

• Great for single random selects and range
scans by key
• Great for variable schema
– Rows may drastically differ
– If your schema has...
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