HBase tutorial: Get started using Apache HBase with Windows-based Hadoop in HDInsight

Learn how to create HBase clusters in HDInsight, create HBase tables, and query the tables by using Apache Hive. For general HBase information, see HDInsight HBase overview.


Linux is the only operating system used on HDInsight version 3.4 or greater. For more information, see HDInsight Deprecation on Windows. The information in this document is specific to Windows-based HDInsight clusters. For information on Linux-based clusters, see HBase tutorial: Get started using Apache HBase in HDInsight.

Before you begin


HDInsight clusters billing is pro-rated per minute, whether you are using them or not. Please be sure to delete your cluster after you have finished using it. For information on deleting a cluster, see How to delete an HDInsight cluster.

Before you begin this HBase tutorial, you must have the following:

Access control requirements

If you use an Azure subscription where you are not the administrator or owner, such as a company-owned subscription, you must verify the following before you use the steps in this article:

  • To sign in to Azure, you need at least Contributor access to the Azure resource group. This resource group is used to create an Azure HDInsight cluster and other Azure resources.
  • Someone with at least Contributor access to the Azure subscription must have previously registered the provider for the resource you are using. Provider registration happens when a user with Contributor access to the subscription creates a resource for the first time on the subscription. It can also be accomplished without creating a resource by registering a provider by using REST.

For more information on working with access management, see the following articles:

Create HBase cluster


The steps in this article create an HDInsight cluster by using basic configuration settings. For information about other cluster configuration settings (such as using Azure virtual network or a metastore for Hive and Oozie), see Provision Hadoop clusters in HDInsight.

To create an HBase cluster by using the Azure portal

  1. Sign in to the Azure portal.
  2. Click New or + in the upper left corner, and then click Data + Analytics, HDInsight.
  3. Enter the following values:

    • Cluster Name - Enter a name to identify this cluster.
    • Cluster Type - Select HBase.
    • Cluster Operating System - Select Windows. For creating Linux-based HBase cluster, see HBase tutorial: Get started using Apache HBase with Hadoop in HDInsight (Linux).
    • Version - Select an HBase version.
    • Subscription - Select your Azure subscription used for creating this cluster.
    • Resource Group - Create a new Azure resource group or select an existing one. For more information, see Azure Resource Manager Overview
    • Credentials - For Windows based cluster, you can create a cluster user (a.k.a HTTP user, HTTP web service user) and a Remote Desktop user. Click Enable Remote Desktop to add the remote desktop user credentials. The next section requires RDP.
    • Data Source - create a new Azure storage account or select an existing Azure storage account to be used as the default file system for the cluster. The default storage account location determines the location of the cluster location. The default storage account and the cluster must co-locate in the same data center.
    • Node Pricing Tiers - Select the number of region servers for the HBase cluster


      For high availability of HBase services, you must create a cluster that contains at least three nodes. This ensures that, if one node goes down, the HBase data regions are available on other nodes.

      If you are learning HBase, always choose 1 for the cluster size, and delete the cluster after each use to reduce the cost.

    • Optional Configuration - Configure Azure virtual network, configure Script actions, and add additional storage accounts.
  4. Click Create.

After an HBase cluster is deleted, you can create another HBase cluster by using the same default storage account and the default blob container. The new cluster will pick up the HBase tables you created in the original cluster. To avoid inconsistencies, we recommend that you disable the HBase tables before you delete the cluster.

Create tables and insert data

Currently, there are two way to access HBase. This section covers using the HBase shell. The next section covers using the .NET SDK.

For most people, data appears in the tabular format:

HDInsight hbase tabular data

In HBase which is an implementation of BigTable, the same data looks like:

HDInsight hbase bigtable data

It'll make more sense after you finish the next procedure.

To use the HBase shell

  1. Use RDP to connect to your HBase cluster in HDInsight. For the RDP instructions, see Manage Hadoop clusters in HDInsight using the Azure Portal.
  2. Within your RDP session, click the Hadoop Command Line shortcut located on the desktop.
  3. Open the HBase shell:

     cd %HBASE_HOME%\bin
     hbase shell
  4. Create an HBase with two column families:

     create 'Contacts', 'Personal', 'Office'
  5. Insert some data:

     put 'Contacts', '1000', 'Personal:Name', 'John Dole'
     put 'Contacts', '1000', 'Personal:Phone', '1-425-000-0001'
     put 'Contacts', '1000', 'Office:Phone', '1-425-000-0002'
     put 'Contacts', '1000', 'Office:Address', '1111 San Gabriel Dr.'
     scan 'Contacts'

    HDInsight hadoop hbase shell

  6. Get a single row

     get 'Contacts', '1000'

    You'll see the same results as using the scan command because there is only one row.

    For more information about the Hbase table schema, see Introduction to HBase Schema Design. For more HBase commands, see Apache HBase reference guide.

  7. Exit the shell


To bulk load data into the contacts HBase table

HBase includes several methods of loading data into tables. For more information, see Bulk loading.

A sample data file has been uploaded to a public blob container, wasbs://hbasecontacts@hditutorialdata.blob.core.windows.net/contacts.txt. The content of the data file is:

8396    Calvin Raji        230-555-0191    230-555-0191    5415 San Gabriel Dr.
16600    Karen Wu        646-555-0113    230-555-0192    9265 La Paz
4324    Karl Xie        508-555-0163    230-555-0193    4912 La Vuelta
16891    Jonn Jackson    674-555-0110    230-555-0194    40 Ellis St.
3273    Miguel Miller    397-555-0155    230-555-0195    6696 Anchor Drive
3588    Osa Agbonile    592-555-0152    230-555-0196    1873 Lion Circle
10272    Julia Lee        870-555-0110    230-555-0197    3148 Rose Street
4868    Jose Hayes        599-555-0171    230-555-0198    793 Crawford Street
4761    Caleb Alexander    670-555-0141    230-555-0199    4775 Kentucky Dr.
16443    Terry Chander    998-555-0171    230-555-0200    771 Northridge Drive

You can create a text file and upload the file to your own storage account if you want. For the instructions, see Upload data for Hadoop jobs in HDInsight.


This procedure uses the Contacts HBase table you created in the last procedure.

  1. Within your RDP session, click the Hadoop Command Line shortcut located on the desktop.
  2. Change directory:

     cd %HBASE_HOME%\bin
  3. Run the following command to transform the data file to StoreFiles and store at a relative path specified by Dimporttsv.bulk.output:

     hbase org.apache.hadoop.hbase.mapreduce.ImportTsv -Dimporttsv.columns="HBASE_ROW_KEY,Personal:Name, Personal:Phone, Office:Phone, Office:Address" -Dimporttsv.bulk.output="/example/data/storeDataFileOutput" Contacts wasbs://hbasecontacts@hditutorialdata.blob.core.windows.net/contacts.txt
  4. Run the following command to upload the data from /example/data/storeDataFileOutput to the HBase table:

     hbase org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles /example/data/storeDataFileOutput Contacts
  5. You can open the HBase shell, and use the scan command to list the table content.

Use Hive to query HBase tables

You can query data stored in HBase by using Hive. This section creates a Hive table that maps to the HBase table and uses it to query the data in your HBase table.

To open the cluster dashboard

  1. Browse to https://.azurehdinsight.net/.
  2. Enter the Hadoop user account user name and password. The default user name is admin and the password is what you entered during the creation process. A new browser tab opens.
  3. Click Hive Editor at the top of the page. The Hive Editor looks like this:

    HDInsight cluster dashboard.

To run Hive queries

  1. Enter the following HiveQL script into Hive Editor and click Submit to create a Hive Table that maps to the HBase table. Make sure that you created the sample table referenced earlier in this tutorial by using the HBase shell before you run this statement.

     CREATE EXTERNAL TABLE hbasecontacts(rowkey STRING, name STRING, homephone STRING, officephone STRING, officeaddress STRING)
     STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
     WITH SERDEPROPERTIES ('hbase.columns.mapping' = ':key,Personal:Name,Personal:Phone,Office:Phone,Office:Address')
     TBLPROPERTIES ('hbase.table.name' = 'Contacts');

    Wait until the Status updates to Completed.

  2. Enter the following HiveQL script into Hive Editor, and then click Submit. The Hive query queries the data in the HBase table:

      SELECT count(*) FROM hbasecontacts;
  3. To retrieve the results of the Hive query, click the View Details link in the Job Session window when the job finishes running. There will be only one job output file because you put one record into the HBase table.

To browse the output file

  1. In the Query Console, click File Browser.
  2. Click the Azure storage account that is used as the default file system for the HBase cluster.
  3. Click the HBase cluster name. The default Azure storage account container uses the cluster name.
  4. Click User, and then click Admin. (This is the Hadoop user name.)
  5. Click the job name with the Last Modified time that matches the time when the SELECT Hive query ran.
  6. Click stdout. Save the file and open the file with Notepad. There will be one output file.

    HDInsight HBase Hive Editor File Browser

Use the .NET HBase REST API client library

You must download the HBase REST API client library for .NET from GitHub and build the project so that you can use the HBase .NET SDK. The following procedure includes the instructions for this task.

  1. Create a new C# Visual Studio Windows Desktop Console application.
  2. Open the NuGet Package Manager Console by clicking Tools > NuGet Package Manager > Package Manager Console.
  3. Run the following NuGet command in the console:

     Install-Package Microsoft.HBase.Client
  4. Add the following using statements at the top of the file:

     using Microsoft.HBase.Client;
     using org.apache.hadoop.hbase.rest.protobuf.generated;
  5. Replace the Main function with the following:

     static void Main(string[] args)
         string clusterURL = "https://<yourHBaseClusterName>.azurehdinsight.net";
         string hadoopUsername= "<yourHadoopUsername>";
         string hadoopUserPassword = "<yourHadoopUserPassword>";
         string hbaseTableName = "sampleHbaseTable";
         // Create a new instance of an HBase client.
         ClusterCredentials creds = new ClusterCredentials(new Uri(clusterURL), hadoopUsername, hadoopUserPassword);
         HBaseClient hbaseClient = new HBaseClient(creds);
         // Retrieve the cluster version.
         var version = hbaseClient.GetVersion();
         Console.WriteLine("The HBase cluster version is " + version);
         // Create a new HBase table.
         TableSchema testTableSchema = new TableSchema();
         testTableSchema.name = hbaseTableName;
         testTableSchema.columns.Add(new ColumnSchema() { name = "d" });
         testTableSchema.columns.Add(new ColumnSchema() { name = "f" });
         // Insert data into the HBase table.
         string testKey = "content";
         string testValue = "the force is strong in this column";
         CellSet cellSet = new CellSet();
         CellSet.Row cellSetRow = new CellSet.Row { key = Encoding.UTF8.GetBytes(testKey) };
         Cell value = new Cell { column = Encoding.UTF8.GetBytes("d:starwars"), data = Encoding.UTF8.GetBytes(testValue) };
         hbaseClient.StoreCells(hbaseTableName, cellSet);
         // Retrieve a cell by its key.
         cellSet = hbaseClient.GetCells(hbaseTableName, testKey);
         Console.WriteLine("The data with the key '" + testKey + "' is: " + Encoding.UTF8.GetString(cellSet.rows[0].values[0].data));
         // with the previous insert, it should yield: "the force is strong in this column"
         //Scan over rows in a table. Assume the table has integer keys and you want data between keys 25 and 35.
         Scanner scanSettings = new Scanner()
             batch = 10,
             startRow = BitConverter.GetBytes(25),
             endRow = BitConverter.GetBytes(35)
         ScannerInformation scannerInfo = hbaseClient.CreateScanner(hbaseTableName, scanSettings);
         CellSet next = null;
         Console.WriteLine("Scan results");
         while ((next = hbaseClient.ScannerGetNext(scannerInfo)) != null)
             foreach (CellSet.Row row in next.rows)
                 Console.WriteLine(row.key + " : " + Encoding.UTF8.GetString(row.values[0].data));
         Console.WriteLine("Press ENTER to continue ...");
  6. Set the first three variables in the Main function.
  7. Press F5 to run the application.

Check cluster status

HBase in HDInsight ships with a Web UI for monitoring clusters. Using the Web UI, you can request statistics or information about regions.

To open the Web UI, you must RDP into the cluster, and then click the HMaster Info Web UI shortcut on your desktop, or use the following URL in a web browser:


In a high availability cluster, you'll find a link to the current active HBase master node that is hosting the Web UI.

Delete the cluster

To avoid inconsistencies, we recommend that you disable the HBase tables before you delete the cluster.


HDInsight clusters billing is pro-rated per minute, whether you are using them or not. Please be sure to delete your cluster after you have finished using it. For information on deleting a cluster, see How to delete an HDInsight cluster.

What's next?

In this HBase tutorial for HDInsight, you learned how to create an HBase cluster and how to create tables and view the data in those tables from the HBase shell. You also learned how use a Hive query on data in HBase tables and how to use the HBase C# REST APIs to create an HBase table and retrieve data from the table.

For more information, see: