This tutorial is a quick introduction to HBase, a distributed, column-oriented database. It explains the basics of HBase, how it works, and why it is a powerful tool for data storage and processing.
Audience
This HBase tutorial is meant for software professionals, students, and researchers who are interested in learning about the Hadoop-based distributed database, HBase. It is primarily meant for those who have some experience with databases and Apache Hadoop, and are looking to explore the features and capabilities of HBase.
Prerequisites
Before you start practicing various types of examples given in this tutorial, we are assuming that you are already aware about basics of HBase.
If you are not aware about HBase, we recommend you to go through our HBase Tutorial.
Also, we are assuming that you have setup your HBase environment. If not, visit HBase Setup page.
HBase – Overview
Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google’s Bigtable. It is built on top of Apache Hadoop and is designed to provide quick random access to huge amounts of structured data. It is well-suited for sparse data sets, which are common in many big data use cases. HBase enables clients to store and access large quantities of data quickly and efficiently. It supports both batch and real-time access to data stored in its tables, and it can be used to store structured and unstructured data. HBase also provides an API for accessing data stored in its tables. This makes it easy to integrate with other applications, including MapReduce, Apache Spark, and Apache Hive.
Limitations of Hadoop
1. Hadoop is not suitable for low latency data processing.
2. Hadoop is not suitable for small data sets because the distributed processing model of Hadoop is designed to work on large amounts of data.
3. The storage capacity offered by Hadoop is limited because it is based on commodity hardware that may not be able to scale up effectively as data grows.
4. The cost of maintaining a Hadoop cluster is high due to the complexity of deploying and managing the system.
5. Hadoop does not provide real-time processing, as it is batch-oriented and data must be stored before it can be processed.
6. Hadoop does not provide a user-friendly interface for data analysis and the learning curve is steep.
7. Security and data privacy are limited due to the lack of advanced security features such as encryption.
Hadoop Random Access Databases
Hadoop Random Access Database is a type of database that utilizes the Hadoop distributed file system (HDFS) to provide random access to data stored in the database. It is an open source system developed by Apache Software Foundation. It is an ideal choice for applications that need to store and process large amounts of data. Hadoop Random Access Database provides efficient, reliable and distributed storage and processing of large data sets. It is also highly scalable and can be used to store and process data from any number of machines. Hadoop Random Access Database is well-suited for data analysis and data warehousing applications.
What is HBase?
HBase is a NoSQL database that runs on top of the Hadoop Distributed File System (HDFS). It is designed to provide a high-performance, fault-tolerant data store for large amounts of unstructured data. It is well-suited for real-time data access and can be used to store massive amounts of data on commodity hardware. HBase also provides features such as replication, data compression, and versioning.
HBase and HDFS
Apache HBase is an open source distributed database modeled after Google’s BigTable. It is written in Java and runs on top of Apache Hadoop and the Hadoop Distributed File System (HDFS). HBase provides real-time read/write access to data stored in HDFS. It is used for storing large data sets in a distributed and fault tolerant manner. It also provides support for MapReduce jobs to process data stored in HDFS. HBase is highly scalable and provides a fault tolerant environment for data storage and retrieval.
HDFS is a distributed file system designed to store very large data sets reliably and to enable rapid data access. It is the primary storage layer for many Hadoop applications. HDFS stores data in a distributed manner across multiple nodes in a cluster. It is designed to be resilient to node failure and provides high throughput access to data. HDFS stores data in files and directories, and provides support for data replication and fault tolerance.
Storage Mechanism
HBase uses a column-oriented storage mechanism. It stores data in tables composed of rows and columns, similar to a traditional relational database. Each row is identified by a unique row key. Within each row, data is organized into a set of columns, which can be further organized into column families. Each cell in the table is identified by its row key, column family, and column qualifier. By storing related columns together in column families, HBase is able to optimize disk I/O and increase data locality.
Column Oriented and Row Oriented
HBase is a column-oriented data store, meaning that data is stored in columns instead of rows. This makes it much more efficient for retrieving data from large datasets. HBase also uses row-oriented storage, meaning that each row of data is stored in a separate file. This makes it easier to retrieve data from specific rows and columns, as well as to update data in a single row without having to update the entire dataset.
Features of HBase
1. Easy to scale: HBase makes it easy to scale up or scale down your data storage needs. It is designed to run on top of existing infrastructure, so you can easily add or remove servers to the cluster without any disruption to your data.
2. Fault tolerant: HBase is designed to be fault-tolerant and highly available, meaning that if any server in the cluster fails, the system continues to operate without any disruption.
3. High performance: HBase provides high performance with low latency, allowing for fast data retrieval from large datasets.
4. Flexible data model: HBase provides a flexible data model that allows you to store data in a variety of formats, including tables, columns, and key-value pairs.
5. Easy integration: HBase is designed to integrate easily with other data sources and applications, allowing you to access and analyze data from multiple sources in one place.
Where to Use HBase
HBase is used in scenarios where there is a need to store and process large amounts of data quickly. It is used by companies such as Facebook, Twitter, Yahoo, and Google to store and query massive amounts of data. It can be used in applications such as web indexing, real-time analytics, and content management.
Applications of HBase
1. Content Management – HBase is used to power content management systems such as Apache Sling, which provides a framework for building content-centric applications.
2. User Profiles – HBase is used to store user profiles in applications such as Yahoo! Pipes.
3. Data Storage – HBase is a great choice for storing large datasets that need to be accessed quickly and reliably.
4. Logging – HBase can be used to store log files for analysis, such as those generated by Hadoop.
5. Online Gaming – HBase is used to store game state and player data in online games such as Zynga Poker.
6. Search Indexes – HBase is used to store search indexes for applications such as Apache Solr.
7. Real-Time Analytics – HBase is used to store and analyze streaming data in real-time.
8. Fraud Detection – HBase is used to store and analyze transaction data for fraud detection.
HBase History
HBase is a distributed, column-oriented database developed as part of the Apache Software Foundation’s Hadoop project. It was created by the engineers at Google in 2006 as a part of their BigTable project and was later open sourced in 2008. HBase is a NoSQL database and is used for real-time, random access to large datasets. It is highly scalable and can handle structured as well as semi-structured data. HBase is used by many companies and organizations such as Facebook, Adobe, eBay and Twitter. HBase is a distributed database that allows for the management of large datasets across multiple nodes. It is designed to provide quick and reliable access to data regardless of where it is stored. It is used in a variety of applications such as web indexing, real-time analytics, e-commerce, fraud detection, and more. HBase is built on top of the Hadoop Distributed File System (HDFS) and is designed to be horizontally scalable, meaning that it can easily be deployed across multiple nodes.
HBase – Architecture
HBase is an open-source, distributed, non-relational database that is designed to provide real-time random access to large amounts of data stored in Hadoop. It is horizontally scalable, meaning that it can store and process vast amounts of data with no single point of failure.
At a high level, HBase is built upon the Hadoop Distributed File System (HDFS) and is managed by a master node called the HMaster. This node stores the configuration information for the cluster and is responsible for resolving region splits and other administrative tasks.
In addition, HBase is composed of one or more RegionServers that manage the actual data stored in the HDFS. The RegionServers store and serve the data that is stored in tables. Tables are collections of rows, each of which contains a key/value pair. The key is used to locate the row, and the value is the actual data stored in that row.
HBase also includes an API for writing custom applications that can interact with the database. This API can be used to read and write data to HBase tables and to perform various administrative tasks such as creating new tables, modifying existing ones, and deleting tables.
Regions
HBase divides tables into regions. A region is a range of rows stored together and managed by a single RegionServer. These regions are split and distributed across multiple Region Servers in an HBase cluster, allowing for horizontal scalability. HBase regions are not fixed in size and can grow or shrink as needed.
MasterServer
The HBase Master is responsible for monitoring all the RegionServers. It assigns regions to RegionServers, and handles load balancing and failover. It keeps track of the state of all Regions in all RegionServers and acts as the single point of failure for the HBase cluster. It also monitors the ZooKeeper cluster, which is responsible for maintaining configuration information.
Zookeeper
Zookeeper is an open-source distributed coordination service for distributed systems. It provides a high-performance, distributed, fault-tolerant, consistent and highly available coordination service for a wide variety of distributed applications, such as distributed databases, distributed messaging systems, distributed file systems, and distributed configuration services. Zookeeper allows distributed applications to maintain a consistent view of their data across multiple nodes. It also provides a simple API for distributed coordination and allows applications to maintain a consistent view of their data across multiple nodes. Zookeeper is used to manage distributed applications, as it provides a simple and reliable coordination service.
HBase – Installation
1. Download and install the latest version of HBase from the Apache website.
2. Configure the HBase environment by editing the configuration files hbase-env.sh, hbase-site.xml, and log4j.properties.
3. Create the data directory, which will contain HBase’s data.
4. Start the HBase Master and Region servers, either manually or using the provided start scripts.
5. Create the HBase tables using the provided shell or API.
6. Load data into the tables.
7. Monitor HBase through the HBase web UI or the provided shell.
SSH Setup and Key Generation in Hbase
1. To setup SSH in HBase, you need to generate a public/private RSA key pair. This can be done using the ssh-keygen command.
2. Once the key pair has been generated, you need to configure SSH to use the key pair. This can be done by editing the sshd_config file.
3. Once the configuration is complete, you can start the SSH service by running the command “service ssh start”.
4. You can then connect to the HBase cluster using the generated SSH key.
5. To ensure that the connection is secure, you should configure the firewall to only allow connections from trusted hosts.
Downloading Hadoop
The latest version of Apache Hadoop can be downloaded from the Apache Software Foundation website. The download page provides links to the latest stable version of Apache Hadoop as well as other related projects.
Once you have downloaded the correct version of Hadoop, you will need to extract it and install it on your system. The installation process involves setting up the environment variables, configuring the various Hadoop components, and running the setup scripts. Once the installation is complete, you should be able to start using Hadoop.
Installing Hadoop
1. Download and install Java
The first step to setting up a Hadoop cluster is to download and install Java. This can be done by downloading the latest version from the Oracle website and then following the installation instructions.
2. Download and Install Hadoop
Once Java is installed, the next step is to download and install Hadoop. This can be done by downloading the latest version from the Apache website and then following the installation instructions.
3. Configure Hadoop
The next step is to configure the Hadoop cluster. This involves setting up the necessary environment variables, configuring the Hadoop daemons, and creating the necessary Hadoop directories.
4. Format the NameNode
The next step is to format the NameNode. This is done by running the ‘hdfs namenode -format’ command.
5. Start the Hadoop Services
The final step is to start the Hadoop services. This can be done by running the ‘start-dfs.sh’ script. Once the services are started, the Hadoop cluster is ready for use.
Verifying Hadoop Installation
To verify the Hadoop installation is working properly, you can run the “hadoop version” command from the command line. This will display the version of Hadoop that is installed. You can also use the “hadoop fs -ls” command to list the files and directories in the Hadoop filesystem.
Installing HBase
1. Download the HBase binary distribution from the Apache HBase website: http://hbase.apache.org/downloads.html
2. Unpack the HBase binary distribution: tar xvzf hbase-x.y.z.tar.gz
3. Create the /etc/hbase directory and copy the hbase-site.xml configuration file to it: mkdir /etc/hbase
4. Edit the hbase-site.xml configuration file to set the configuration parameters for your HBase cluster.
5. Set the environment variables for HBase:
export HBASE_HOME=/path/to/hbase
export PATH=$HBASE_HOME/bin:$PATH
6. Start the HBase master and regionserver daemons:
$HBASE_HOME/bin/start-hbase.sh
7. Verify that HBase is running correctly by accessing the HBase shell:
$HBASE_HOME/bin/hbase shell
Installing HBase in Pseudo-Distributed Mode
1. Install Java: First, install Java 8 or later on the system.
2. Download HBase: Next, download the version of HBase that is compatible with the version of Hadoop installed.
3. Configure HBase: Once the software is downloaded, configure the HBase environment. This includes setting up the necessary environment variables and configuring the HBase configuration file.
4. Start HBase: Finally, start HBase in pseudo-distributed mode. This can be done by running the ‘start-hbase.sh’ script.
Configuring HBase in Standalone Mode
1. Download and install Hadoop and HBase.
2. Set up environment variables for Hadoop and HBase.
3. Configure your HBase configuration files.
4. Edit the hbase-env.sh file to set the JAVA_HOME variable.
5. Run the start-hbase.sh command to start the HBase service.
6. Connect to the HBase master server using the Hbase shell command.
7. Create tables and insert data into them.
8. Run the stop-hbase.sh command to shut down the HBase service.
Checking the HBase Directory in HDFS
To check the HBase directory in HDFS, use the command hdfs dfs -ls /hbase. This will list the contents of the HBase directory in HDFS.
Starting and Stopping a Master
To start a master, use the command “start-master.sh” in the /bin folder of your Spark installation. To stop a master, use the command “stop-master.sh” in the /bin folder of your Spark installation.
Starting HBaseShell
To start the HBaseShell, open a command prompt and type the command “hbase shell”. This will open the HBaseShell.
Once the HBaseShell is open, you can type in commands to interact with the HBase cluster.
HBase Web Interface
HBase Web Interface is a web-based graphical user interface that provides access to HBase data and configuration. This web interface provides a user-friendly interface for managing and querying data stored in HBase. It also provides a graphical view of the HBase cluster and allows users to modify HBase configuration settings. The web interface also allows users to view and monitor the status of their HBase cluster, including metrics such as region server availability, cluster utilization, and memory usage.
HBase – Shell
HBase shell is a command-line interface that allows users to interact with Apache HBase. It can be used to perform administrative tasks such as creating and deleting tables, as well as to query and manipulate data. The shell also provides a scripting environment for automating HBase tasks.
HBase Shell General Commands
1. status: Displays basic information about the HBase cluster, such as the number of regions, the number of regions in transition, and the HBase version.
2. version: Displays the version of HBase and its associated Java classes.
3. create_namespace: Creates a namespace in HBase.
4. disable_namespace: Disables a namespace in HBase.
5. enable_namespace: Enables a namespace in HBase.
6. drop_namespace: Drops a namespace from HBase.
7. create: Creates a table in HBase.
8. disable: Disables a table in HBase.
9. enable: Enables a table in HBase.
10. drop: Drops a table from HBase.
11. alter: Alters a table in HBase.
12. describe: Displays the details of a table in HBase.
13. list: Lists all tables in HBase.
14. put: Inserts or updates a row in a table.
15. get: Retrieves a row from a table.
16. delete: Deletes a row from a table.
17. scan: Scans a table, returning the requested columns and rows.
18. count: Counts the number of rows in a table.
19. truncate: Truncates a table.
20. help: Displays help for HBase Shell commands.
Data Definition Language
Data Definition Language (DDL) is a set of commands in Structured Query Language (SQL) used to create and manage database objects such as tables, views, and other database structures.
Examples of DDL commands include:
CREATE – Used to create objects in the database
ALTER – Used to modify objects in the database
DROP – Used to delete objects in the database
TRUNCATE – Used to delete all records from a table, including all spaces allocated for the records are removed
COMMENT – Used to add comments to the data dictionary
RENAME – Used to rename an object
Data Manipulation Language
Data Manipulation Language (DML) is a language used to manipulate (insert, update, delete) data stored in a relational database. DML statements are usually part of a larger script that may also include DDL (Data Definition Language) statements that define and structure the data. Examples of DML statements include INSERT, UPDATE, and DELETE.
1. SELECT: used to select data from a database
2. INSERT: used to insert data into a database
3. UPDATE: used to update existing data in a database
4. DELETE: used to delete data from a database
5. CREATE: used to create new databases and database objects
6. ALTER: used to modify existing databases and database objects
7. DROP: used to drop databases and database objects
Starting HBase Shell
To start the hbase shell, enter the command hbase shell on the terminal.
HBase – General Commands
1. List all tables: `list`
2. Create a new table: `create <table name>`
3. Describe a table: `describe <table name>`
4. Enable a table: `enable <table name>`
5. Disable a table: `disable <table name>`
6. Delete a table: `drop <table name>`
7. Add a column family: `alter <table name> add <column family name>`
8. Rename a column family: `alter <table name> rename <old column family name> <new column family name>`
9. Delete a column family: `alter <table name> drop <column family name>`
10. Add a column to a table: `alter <table name> add <column family name>:<column name> <data type>`
11. Delete a column from a table: `alter <table name> drop <column family name>:<column name>`
12. Scan a table: `scan <table name>`
13. Get a row from a table: `get <table name> <row key>`
14. Put data into a table: `put <table name> <row key> <column family name>:<column name> <value>`
15. Delete data from a table: `delete <table name> <row key> <column family name>:<column name>`
HBase – Admin API
The HBase Admin API is a set of Java APIs that allow administrators to manage an HBase instance. It provides methods for creating, deleting, and modifying tables, as well as other administrative tasks such as setting permissions and snapshots. Additionally, it provides methods for retrieving information about tables, regions, and cluster status.
Class HBaseAdmin
HBaseAdmin is a Java class in the Apache HBase library that provides administrative functions for the HBase database. It allows users to create, delete, modify, and list tables, as well as perform other administrative tasks such as setting and modifying user permissions, configuring cluster replication, and performing server-side operations. It is used to manage the entire HBase cluster, and its methods are used for tasks such as creating and deleting tables, setting region replicas, and configuring cluster replication.
Class Descriptor
HBase is a distributed, column-oriented data store that is part of the Apache Hadoop ecosystem. It is a NoSQL database that is well suited for storing large amounts of structured data. HBase provides fast, flexible access to data stored in its tables. It is an open source project developed and maintained by the Apache Software Foundation. HBase is written in Java and is built on top of the Apache Hadoop Distributed File System (HDFS). It provides an API for interacting with the data stored in its tables. HBase is designed to provide scalability, high availability, and low latency for applications that require real-time access to data. HBase also provides features such as versioning, column-level security, and distributed transactions.
HBase – Create Table
To create a table in HBase, the user must use the create command. The syntax for creating a table in HBase is as follows:
Create ‘<table_name>’, ‘<column_family_name>’, {NAME => ‘<column_name>’, COMPRESSION => ‘<compression_algorithm>’}
For example, to create a table named ‘mytable’ with a single column family named ‘myfamily’, the command would be as follows:
Create ‘mytable’, ‘myfamily’, {NAME => ‘mycolumn’, COMPRESSION => ‘GZ’}
Creating a Table using HBase Shell
Create ’employee’, ‘personal_data’, ‘professional_data’
hbase> create ’employee’, ‘personal_data’, ‘professional_data’
Creating a Table Using java API
import java.sql.*;
public class CreateTableDemo {
static final String JDBC_DRIVER = “com.mysql.jdbc.Driver”;
static final String DB_URL = “jdbc:mysql://localhost/STUDENTS”;
// Database credentials
static final String USER = “username”;
static final String PASS = “password”;
public static void main(String[] args) {
Connection conn = null;
Statement stmt = null;
try{
//STEP 2: Register JDBC driver
Class.forName(“com.mysql.jdbc.Driver”);
//STEP 3: Open a connection
System.out.println(“Connecting to a selected database…”);
conn = DriverManager.getConnection(DB_URL, USER, PASS);
System.out.println(“Connected database successfully…”);
//STEP 4: Execute a query
System.out.println(“Creating table in given database…”);
stmt = conn.createStatement();
String sql = “CREATE TABLE REGISTRATION ” +
“(id INTEGER not NULL, ” +
” first VARCHAR(255), ” +
” last VARCHAR(255), ” +
” age INTEGER, ” +
” PRIMARY KEY ( id ))”;
stmt.executeUpdate(sql);
System.out.println(“Created table in given database…”);
}catch(SQLException se){
//Handle errors for JDBC
se.printStackTrace();
}catch(Exception e){
//Handle errors for Class.forName
e.printStackTrace();
}finally{
//finally block used to close resources
try{
if(stmt!=null)
conn.close();
}catch(SQLException se){
}// do nothing
try{
if(conn!=null)
conn.close();
}catch(SQLException se){
se.printStackTrace();
}//end finally try
}//end try
System.out.println(“Goodbye!”);
}//end main
}//end JDBCExample
HBase – Listing Table
To list the tables in HBase, you can use the command-line tool hbase shell. In the hbase shell, use the list command to list all tables in the database.
Example:
hbase> list
This will list all the tables in the database.
Listing a Table using HBase Shell
To list a table in HBase Shell, use the list command.
For example:
hbase> list
TABLE
user_table
test_table
another_table
Listing Tables Using Java API
The following code snippet shows how to list tables using Java API:
// Create a Cluster object Cluster cluster = Cluster.builder().addContactPoint(“127.0.0.1”).build();
// Create a Session object Session session = cluster.connect();
// Execute the query String query = “SELECT * FROM system.schema_keyspaces”;
ResultSet resultSet = session.execute(query);
// Iterate over the result set and print the table names Iterator<Row> iterator = resultSet.iterator();
while (iterator.hasNext()) { Row row = iterator.next(); System.out.println(row.getString(“keyspace_name”)); }
// Close the session and cluster objects session.close(); cluster.close();
HBase – Disabling a Table
To disable a table in HBase, the disable command can be used. This command will make the table unavailable for read and write operations.
Syntax :
disable ‘<table_name>’
Example :
disable ’employees’
Disable a Table Using Java API
//Disable the table
TableName tableName = TableName.valueOf(“tableName”);
Admin admin = connection.getAdmin();
admin.disableTable(tableName);
admin.close();
HBase – Enabling a Table
1. Access the HBase Shell:
$ hbase shell
2. Create a Table:
hbase> create ‘table_name’, ‘column_family_1’, ‘column_family_2’
3. Enable the Table:
hbase> enable ‘table_name’
Enabling a Table using HBase Shell
To enable a table using HBase shell, use the following command:
Enable ‘<table_name>’
Enable a Table Using Java API
This example uses the Apache Derby database and the java.sql.* APIs to enable a table.
import java.sql.*;
public class EnableTable {
public static void main(String[] args) {
//Create a variable for the connection string.
String connectionUrl = “jdbc:derby:sampleDB;create=true”;
//Declare the JDBC objects.
Connection con = null;
Statement stmt = null;
ResultSet rs = null;
try {
//Establish the connection.
Class.forName(“org.apache.derby.jdbc.ClientDriver”);
con = DriverManager.getConnection(connectionUrl);
//Create and execute an SQL statement that enables the table.
String SQL = “ALTER TABLE myTable ENABLE;”;
stmt = con.createStatement();
stmt.executeUpdate(SQL);
//Display the result.
System.out.println(“Table enabled successfully.”);
}
//Handle any errors that may have occurred.
catch (Exception e) {
e.printStackTrace();
}
finally {
if (rs != null) try { rs.close(); } catch(Exception e) {}
if (stmt != null) try { stmt.close(); } catch(Exception e) {}
if (con != null) try { con.close(); } catch(Exception e) {}
}
}
}
HBase – Describe & Alter
Describe:
Describe is a command that allows users to view metadata information about tables in an HBase database. This command will list information such as the table name, column families, and other details about the table.
Alter:
Alter is a command that allows users to modify existing tables in an HBase database. This command can be used to add or remove column families, modify table properties, or set the table name. It can also be used to enable or disable certain table features, such as replication or compression.
Changing the Maximum Number of Cells of a Column Family
The maximum number of cells of a column family can be changed by setting the property “max_versions” in the column family definition. The value of this property determines the maximum number of versions of each column that can be stored in the column family.
Adding a Column Family Using Java API
Create a ColumnFamily object and set the required settings such as name, key, and column validator. Then, use the Cassandra Java API to execute the createColumnFamily method to add the column family to the keyspace. The following is an example of code to add a column family using the Java API:
Cluster cluster = Cluster.builder().addContactPoint(“127.0.0.1”).build();
Session session = cluster.connect(“mykeyspace”);
ColumnFamilyDefinition cfDef = HFactory.createColumnFamilyDefinition(“mykeyspace”, “myColumnFamily”, ComparatorType.UTF8TYPE);
cfDef.setKeyValidationClass(“UTF8Type”);
session.execute(HFactory.createColumnFamilyDefinition(“mykeyspace”, cfDef));
Deleting a Column Family Using Java API
Cassandra provides a Java API to delete a column family from a keyspace. The following example demonstrates how to delete a column family using the Java API.
// Connect to the cluster
Cluster cluster = Cluster.builder().addContactPoint(“127.0.0.1”).build();
// Get the session
Session session = cluster.connect(“keyspace”);
// Delete the column family
session.execute(“DROP TABLE columnfamilyname”);
// Close the session
session.close();
// Close the cluster
cluster.close();
HBase – Exists
HBase is a distributed, open source, non-relational database written in Java and modeled after Google’s BigTable. It is developed under the Apache Software Foundation and runs on top of the Hadoop Distributed File System (HDFS). HBase is designed to store large amounts of data in a column-oriented fashion and to support low-latency random access to data. It is especially efficient for real-time read/write operations and is used to support high-traffic web applications, such as social networks and search engines. HBase is used in many large-scale production systems, such as Facebook, Twitter, and Yahoo.
Existence of Table using HBase Shell
To determine the existence of a table using the HBase Shell, use the command “list”. This command will list all the tables that exist in the HBase database. For example, if you type “list” in the HBase Shell, you will get a list of all the tables in the database.
Verifying the Existence of Table Using Java API
The Java Database Connectivity (JDBC) API allows developers to check for the existence of a table in a database by using the DatabaseMetaData interface. The DatabaseMetaData interface provides methods such as getTables() and tableExists() that can be used to verify the existence of a table.
HBase – Drop a Table
Dropping a table in HBase is an irreversible operation. Before dropping a table, you should ensure that you no longer need the data stored in it.
To drop a table, use the following command:
hbase> disable ‘table_name’
hbase> drop ‘table_name’
Dropping a Table using HBase Shell
To drop a table using HBase shell, use the command:
disable ‘<table_name>’
drop ‘<table_name>’
Deleting a Table Using Java API
// Import necessary packages
import java.sql.Connection;
import java.sql.DatabaseMetaData;
import java.sql.DriverManager;
import java.sql.SQLException;
import java.sql.Statement;
// Create a class to delete a table
public class DeleteTable {
// Create a method to execute the delete
public static void deleteTable(String dbName, String tableName) throws SQLException {
// Establish connection to the database
Connection connection = DriverManager.getConnection(“jdbc:sqlite:” + dbName);
// Create a statement object
Statement statement = connection.createStatement();
// Get the database metadata
DatabaseMetaData metaData = connection.getMetaData();
// Check if the table exists in the database
if (metaData.getTables(null, null, tableName, null).next()) {
// Execute the delete statement
statement.execute(“DROP TABLE ” + tableName);
System.out.println(“Table ” + tableName + ” deleted successfully!”);
} else {
System.out.println(“Table ” + tableName + ” does not exist in the database!”);
}
}
// Main method
public static void main(String[] args) throws SQLException {
// Call the deleteTable method
deleteTable(“myDatabase.db”, “myTable”);
}
}
HBase – Shutting Down Master
To shut down a HBase Master, the following steps can be taken:
1. Log into the host machine running the HBase Master.
2. Stop the HBase Master process. This can be done by running the following command:
$ hbase-daemon.sh stop master
3. Verify that the HBase Master process has been stopped. This can be done by running the following command:
$ jps
If the HBase Master process is still running, repeat step 2.
4. Once the HBase Master process has been stopped, exit the host machine.
Stopping HBase
In order to stop HBase, you can use the stop-hbase.sh script. This script can be found in the bin directory of the HBase installation. To run it, open a terminal window and navigate to the bin directory, then enter the command:
./stop-hbase.sh
Stopping HBase Using Java API
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.HBaseAdmin;
public class StopHBase {
public static void main(String[] args) throws IOException {
// Instantiating configuration class
Configuration con = HBaseConfiguration.create();
// Instantiating HBaseAdmin class
HBaseAdmin admin = new HBaseAdmin(con);
// Stopping HBase
admin.shutdown();
System.out.println(“HBase has been stopped”);
}
}
HBase – Client API
The HBase client API is a Java API that allows applications to interact with the HBase database. It provides methods for creating, reading, updating, and deleting data from the database. The API also provides methods for managing the database, such as creating and deleting tables. The client API can be used to access data from HBase through various programming languages, such as Java, Scala, Python, and Go.
Class HBase Configuration
HBase is an open-source, non-relational, distributed database built on top of the Hadoop framework. HBase is designed to provide quick random access to large amounts of structured data. It stores data in the form of tables which are split into regions and managed by RegionServers.
The HBase configuration consists of two main components: hbase-site.xml and hbase-default.xml. The hbase-site.xml file contains site-specific configuration parameters, while the hbase-default.xml file contains default values that can be overridden in the hbase-site.xml file.
The hbase-site.xml file contains settings such as the HDFS port number, the directory where HBase stores its files, and the ZooKeeper quorum to be used for distributed coordination. It also contains settings for how regions and tables are split and stored.
The hbase-default.xml file contains settings such as the maximum size of data stored in memory, the number of threads used for background tasks, and the number of writes allowed before a flush. It also contains settings for the replication factor and the block size used when storing data in HDFS.
Class HTable
The HTable class is used in Apache HBase to provide a client-side representation of an HBase table. This class allows the user to do various operations on the table such as putting, getting, deleting, scanning, and checking for the existence of rows. It also provides access to the table’s metadata, such as the table name, column families, and configuration settings.
HBase – Create Data
HBase is a NoSQL database that provides a distributed, column-oriented data store for rapid, random read/write access to data.
To create data in HBase, you first need to create a table. You can do this by using the HBase shell command line utility. The syntax for creating a table is as follows:
create ‘<table_name>’, ‘<column_family_name>’
Where <table_name> is the name of the table you want to create, and <column_family_name> is the name of the column family you want to create inside the table.
After you have created a table, you can insert data into it by using the HBase shell command line utility. The syntax for inserting data is as follows:
put ‘<table_name>’, ‘<row_key>’, ‘<column_family_name>:<column_name>’, ‘<value>’
Where <table_name> is the name of the table you want to insert data into, <row_key> is the key of the row you want to insert the data into, <column_family_name> is the name of the column family the data will be inserted into, <column_name> is the name of the column the data will be inserted into, and <value> is the value to be inserted.
You can also use the HBase shell command line utility to batch insert data. The syntax for batch inserting data is as follows:
batch put ‘<table_name>’, ‘<row_key>’, [<column_family_name>:<column_name>, <value>, <column_family_name>:<column_name>, <value>, …]
Where <table_name> is the name of the table you want to insert data into, <row_key> is the key of the row you want to insert the data into, <column_family_name> is the name of the column family the data will be inserted into, <column_name> is the name of the column the data will be inserted into, and <value> is the value to be inserted.
Inserting Data using HBase Shell
Step 1: Start the HBase Shell
Run the following command to start the HBase Shell:
hbase shell
Step 2: Create a table
Create a table named ‘employee’ with a single column family ‘personal’ by running the following command:
create ’employee’, ‘personal’
Step 3: Insert data into table
Insert data into the table ‘employee’ with row key ‘1’ and column ‘personal:name’ with value ‘John Doe’ by running the following command:
put ’employee’, ‘1’, ‘personal:name’, ‘John Doe’
Step 4: Verify data
Verify the data by running the following command:
get ’employee’, ‘1’
The output of this command should be as follows:
COLUMN CELL
personal:name timestamp=1548644471000, value=John Doe
Inserting Data Using Java API
First, create a database connection using the DriverManager class. This class is part of the JDBC API and provides a mechanism for connecting to a database.
Next, use the createStatement() method of the Connection object to create a Statement object. This object will be used to execute SQL statements.
Next, create a SQL statement using the appropriate syntax. This statement will be used to insert data into the database.
Finally, execute the statement using the executeUpdate() method of the Statement object. This method will return an integer indicating the number of rows affected.
You can also use the PreparedStatement class to insert data into a database. This class allows you to parameterize your SQL statements, which can help prevent SQL injection attacks.
HBase – Update Data
To update data in HBase, the Put command can be used. This command will overwrite existing values within a row and will insert new values if they do not already exist. To update data in HBase, the following syntax is used:
Put ‘table_name’, ‘row_key’, ‘column_family:column_name’, ‘updated_value’
Updating Data using HBase Shell
First, open the HBase Shell.
To update data in HBase, you can use the ‘put’ command.
Syntax:
put ‘<table_name>’, ‘<row_key>’, ‘<column_family>:<column_name>’, ‘<value>’
For example, if you wanted to update the value in the row key ‘123’ in the table ‘sample_table’, column family ‘cf’ and column name ‘col1’, you would use the following command:
put ‘sample_table’, ‘123’, ‘cf:col1’, ‘updated_value’
Updating Data Using Java API
The Java API provides a collection of classes and interfaces that support the manipulation of data in an application. The Java API includes classes and methods that allow developers to create, update, delete, and query data.
To update data using the Java API, use the update methods of the appropriate data manipulation objects. These methods typically take a set of parameters that define the data to be updated. The exact parameters and methods used will depend on the type of data and the specific data manipulation object in use.
For example, to update an entry in an ArrayList, you would use the set() method. This method takes two parameters – the index of the entry to update and the new value to set. Similarly, to update a record in a database, you would use the update() method of the appropriate JDBC object.
To update a file, you would use the write() method of the appropriate File object. This method takes the file path and the new content to be written to the file.
Finally, to update a network connection, you would use the send() method of the appropriate Network object. This method takes the parameters for the data to be sent to the remote host.
HBase – Read Data
HBase allows users to read data from the tables using the Get and Scan commands. The Get command is used to retrieve a single row at a time, while the Scan command is used to retrieve multiple rows at a time. Both commands take a row key as the argument and return the complete row as the result.
Reading Data using HBase Shell
Step 1: Login to the HBase shell using the command “hbase shell”
Step 2: Create a table using the command “create ‘<tablename>’, ‘<columnfamilyname>'”
Step 3: Insert data into the table using the command “put ‘<tablename>’, ‘<rowkey>’, ‘<columnfamilyname>:<columnname>’, ‘<value>'”
Step 4: Retrieve the data using the command “get ‘<tablename>’, ‘<rowkey>'”
Reading Data Using Java API
Reading data using Java API is a simple process. The first step is to create an InputStream to read the data. This can be done by using the FileInputStream class, which takes a file path as an argument. Once the InputStream is created, the data can be read using a Scanner object. The Scanner can be used to read the data line by line, or to parse the data into primitive types such as integers and strings. Finally, the data can be manipulated as needed.
HBase – Delete Data
HBase provides two methods for deleting data:
1. Delete Column: This method can be used to delete a single column of data from a row in an HBase table. To delete a column, you must specify the row key, column family, and column qualifier.
2. Delete Row: This method can be used to delete an entire row of data from an HBase table. To delete a row, you must specify the row key.
In both cases, the delete operation is performed immediately, and the data is permanently removed from the table.
Deleting a Specific Cell in a Table
To delete a specific cell in a table, right-click on the cell and select “Delete Cell” from the drop-down menu. You can also select the cell and press the “Delete” key on your keyboard.
Deleting All Cells in a Table
To delete all cells in a table, select the table and press the Delete key. This will delete all cells, rows and columns. To delete all content in the cells, but not the cells themselves, select the table and click the Clear All button on the Home tab.
Deleting Data Using Java API in Hbase
To delete data from Hbase using Java API, you need to use the Delete class from the org.apache.hadoop.hbase.client package.
Using the Delete class, you can delete an entire row or a specific column from a row. To delete a row, you need to create an instance of the Delete class by passing the row key. To delete a specific column, you need to create an instance of the Delete class by passing the row key and the column family name, column name and timestamp.
Once you have created the Delete instance, you can call the delete() method on the instance to delete the row or the column.
Example
// Create the configuration object
Configuration config = HBaseConfiguration.create();
// Create the connection to HBase
Connection connection = ConnectionFactory.createConnection(config);
// Get the table reference
Table table = connection.getTable(TableName.valueOf(“tableName”));
// Delete the row with row key “row1”
Delete deleteRow = new Delete(“row1”);
table.delete(deleteRow);
// Delete the column with row key “row1” and column family “cf1”, column name “col1”
Delete deleteColumn = new Delete(“row1”).addColumn(“cf1”, “col1”);
table.delete(deleteColumn);
// Close the connection
connection.close();
HBase – Scan
HBase Scan is an operation used to read data from an HBase table. The scan can retrieve all rows from the table or a subset of rows from the table. It can also be used to retrieve specific columns from a row or a subset of columns from a row. The scan is performed by specifying a start and end row key for the scan and then applying additional filters if needed. The scan can be used to retrieve data from the table in ascending or descending order.
Scaning using HBase Shell
1. Log in to the HBase Shell
hbase shell
2. Create a table
create ‘table_name’, ‘column_family_name’
3. List the existing tables
list
4. Scan a table
scan ‘table_name’
Java API HBase Shell
The Java API for HBase Shell is used to access HBase from Java applications. It provides a command line interface for users to interact with HBase, allowing them to create, update, delete, and query HBase tables. It also includes a range of commands for managing and optimizing the cluster. This API can be used to scan and query data in HBase tables. It is possible to do single row or range scans, or to perform a full table scan. It also provides methods for setting various filters and limits on the scan.
HBase – Count & Truncate
To count the number of rows in an HBase table, you can use the ‘count’ command. To truncate a table in HBase, use the ‘truncate’ command. Both commands can be executed from the HBase shell.
HBase – Security
HBase is capable of operating in secure mode. This provides users with a more secure environment to store their data and perform operations. Secure mode is enabled by setting up Kerberos authentication, which requires each user to authenticate themselves with a Kerberos ticket. Additionally, access to HBase tables can be restricted to specific users or groups and relevant ACLs can be enforced. Other security measures, such as encryption of data at rest and in transit, and secure RPC, can be enabled to further enhance the security of HBase.
grant
GRANT SELECT, INSERT, UPDATE, DELETE ON database_name TO user@host_name;
revoke
REVOKE [permission] ON [object] FROM [user];
Example:
REVOKE SELECT ON Employees FROM John;
user_permission
The user_permission command is used to grant or deny permissions to a user on a computer or network. This command allows the user to set or modify the access rights of other users and groups. It can also be used to view the current permissions for a user or group.