Apache HBase
Apache HBase
HBase was developed out of the need for real-time, random read/write access to very large datasets. Since it is built upon HDFS, it provides low-latency access to structured data by utilizing distributed computing techniques. Apache HBase was first developed at Powerset, a search startup that was later acquired by Microsoft in 2008. The goal was to provide a system to support real-time access to petabytes of unstructured data for interactive search. In 2006, Powerset engineers started building a distributed storage system based on Google’s BigTable design. To meet their performance requirements, they had to extend the design and wrote a new code base. This code base was eventually open sourced in 2009 as Apache HBase. Since then, Apache HBase has been heavily used in production by many companies and powers applications such as Facebook’s Messages Service, Yahoo’s Messaging Infrastructure, LinkedIn’s Realtime Activity Streams, OpenX advertising platform and many others.
History of Apache HBase
Apache HBase was originally created in the spring of 2006 by Powerset, a technology company in San Francisco, CA. The company’s goal was to build an efficient system to handle large datasets of unstructured data. The first version of HBase was released in July 2008 as an open source project under the Apache Software Foundation. Since then, the project has grown rapidly, with more than 5,000 commits to its source code and close to 1,000 contributors all over the world.
What is Apache HBase
Apache HBase is a distributed, column-oriented database that runs on top of HDFS. It is modelled on Google’s BigTable and provides random read/write access to data using HDFS as the underlying storage layer. It supports both batch processing and real-time search.
HBase is designed to scale from single servers to thousands of machines, each offeringlocal computation and storage. This enables HBase to handle massive data sets with billions of rows and millions of columns, and at the same time provides low latency and high throughput for a wide range of Big Data applications.
How to Use Apache HBase
HBase is mainly used for real-time lookup and analysis of large datasets. For example, HBase can be used as a storage layer for a website to provide real-time search and analytics capabilities. It can also be used in conjunction with other Apache projects such as Apache Hive and Apache Pig to provide interactive queries and analytics.
In order to use Apache HBase, you need to deploy a cluster of machines and install the HBase software. Once the HBase software is installed, you can create tables and insert data. You can then query the data using MapReduce or JRuby.
Apache HBase adoption
Apache HBase is commonly used for a variety of different purposes, including:
- Storing web logs and clickstream data
- Maintaining user profiles and session data
- Real-time analytics on streaming data
- Building real-time recommendation systems
- Indexing the full text of documents
Features
At its core, Apache HBase is a column-oriented database management system that runs on top of the Hadoop Distributed File System (HDFS). It allows users to store and process large amounts of data quickly and reliably. Some of the key features of Apache HBase include:
- Flexible schema: HBase has a schema-less data model that allows users to add, modify, or delete columns on the fly. This makes it easy to store and query massive amounts of structured and semi-structured data.
- Real-time read/write access: HBase provides real-time read and write access to large-amounts of unstructured data. This makes it well suited for applications that require low latency response times.
- Fault tolerance: Apache HBase is designed for fault tolerance, meaning it can automatically recover from hardware or software failures without any manual intervention.
- Scalability: Apache HBase is designed for horizontal scalability, meaning it can easily scale across multiple machines if needed.
Code Examples
Here are some examples of how to use Apache HBase:
Creating a Table
The following example shows how to create a table in HBase using the Java API:
// Create an HBase admin object
HBaseAdmin admin=new HBaseAdmin(configuration);
// Create a Description of the table
HTableDescriptor tableDescriptor=new HTableDescriptor("my_table");
// Create a column family
HColumnDescriptor family=new HColumnDescriptor("my_family");
tableDescriptor.addFamily(family);
// Create the table
admin.createTable(tableDescriptor);
Inserting Data
The following example shows how to insert data into a table in HBase using the Java API:
// Create an HBase connection object
Configuration configuration=HBaseConfiguration.create();
HTable table=new HTable(configuration,"my_table");
// Create aPut object to insert data
Put put=new Put("row1" .getBytes());
put.add("my_family","column1" .getBytes(),"value1" .getBytes());
put.add("my_family","column2" .getBytes(),"value2" .getBytes());
// Insert the data
table.put(put);
Querying Data
The following example shows how to query data from a table in HBase using the Java API:
// Create an HBase connection object
Configuration configuration=HBaseConfiguration.create();
HTable table=new HTable(configuration,"my_table");
// Create a Get object to query data
Get get=new Get("row1" .getBytes());
get.addColumn("my_family","column1" .getBytes());
// Retrieve the data
Result result=table.get(get);
String value=new String(result.getValue("my_family","column1" .getBytes()));
System.out.println(value); // prints "value1"
Below is a basic example of how to set up and use a HBase table in Java. This example creates a table named “TestTable” and adds two columns, “name” and “age”.
// Create configuration
Configuration conf=HBaseConfiguration.create();
// Create a connection
Connection connection=ConnectionFactory.createConnection(conf);
// Create a new table
Admin admin=connection.getAdmin();
TableName tableName=TableName.valueOf("TestTable");
HTableDescriptor desc=new HTableDescriptor(tableName);
// Add columns
HColumnDescriptor namecol=new HColumnDescriptor("name");
desc.addFamily(namecol);
HColumnDescriptor agecol=new HColumnDescriptor("age");
desc.addFamily(agecol);
admin.createTable(desc);
// Put some data
Table table=connection.getTable(tableName);
Put put=new Put(Bytes.toBytes("row1"));
put.addColumn(Bytes.toBytes("name"),Bytes.toBytes("John"),Bytes.toBytes("Smith"));
put.addColumn(Bytes.toBytes("age"),Bytes.toBytes("34"));
table.put(put);
// Get some data
Get get=new Get(Bytes.toBytes("row1"));
get.addColumn(Bytes.toBytes("name"));
Result result=table.get(get);
String name=Bytes.toString(result.getValue(Bytes.toBytes("name"),Bytes.toBytes("John")));
System.out.println("Name: "+name);
// Close resources
table.close();
connection.close();
This example shows how to create a table, add columns, insert data, and retrieve data from the table.
HBase also provides a rich set of APIs, such as the Java API, REST API, Thrift API, Avro API, and so on that can be used to interact with the data stored in HBase tables.
Examples of Usage
There are many use cases for Apache HBase, including:
Storing Web Log Data
Apache HBase can be used to store huge amounts of web log data. HBase’s schema-less data model and real-time access make it ideal for logging and analyzing user activity on websites.
For example, Yahoo uses HBase to store terabytes of web logs to analyze user usage patterns and optimize their website performance.
Real-time Analytics
Apache HBase can be used to store and analyze streaming datasets in real-time. This makes it well suited for anyone who needs to make decisions quickly, such as stock traders, data scientists, and researchers.
For example, Apache HBase is used by financial firms to store and analyze streaming market data in real-time to make trading decisions.
Storing Social Network Data
Apache HBase can be used to store and analyze large amounts of social network data. This makes it well suited for applications that require understanding user relationships and trends such as recommendation engines.
For example, Facebook uses HBase to store and analyze terabytes of social network data to understand user relationships and trends.
Code Examples
Writing Data
This example shows how to write some data to an HBase table using the Java API:
Configuration conf=HBaseConfiguration.create();
HTable table=new HTable(conf,"TABLE_NAME");
Put put=new Put(Bytes.toBytes("rowKey"));
put.add(Bytes.toBytes("cf"),Bytes.toBytes("columnName"),
Bytes.toBytes("value"));
table.put(put);
Reading Data
This example shows how to read some data from an HBase table using the Java API:
Configuration conf=HBaseConfiguration.create();
HTable table=new HTable(conf,"TABLE_NAME");
Get get=new Get(Bytes.toBytes("rowKey"));
Result result=table.get(get);
byte[]value=result.getValue(Bytes.toBytes("cf"),
Bytes.toBytes("columnName"));
String valueStr=Bytes.toString(value);
import org.apache.hadoop.hbase.*;
import org.apache.hadoop.conf.Configuration;
Configuration config=HBaseConfiguration.create();
HTable table=new HTable(config,"myTableName");
Put put=new Put(Bytes.toBytes("row_key"));
put.add(Bytes.toBytes("column_family"),Bytes.toBytes("column_name"),Bytes.toBytes("value"));
table.put(put);
The above code creates a new row in an HBase table and sets the value of a specific column.
Conclusion
Apache HBase is an open source, distributed, versioned, column-oriented store modeled after Google’s BigTable. It provides data model facilities to store huge amounts of unstructured, sparse data with low latency and is used by many companies and organizations for various applications. Examples of applications that can use HBase include time series data, real-time updates, full-text search, and fast analytics over large datasets.