Communities
A collaborative platform to connect and grow with like-minded Informaticans across the globe
Product Communities
Connect and collaborate with Informatica experts and champions
Discussions
Have a question? Start a Discussion and get immediate answers you are looking for
User Groups
Customer-organized groups that meet online and in-person. Join today to network, share ideas, and get tips on how to get the most out of Informatica
Get Started
Community Guidelines
Knowledge Center
Troubleshooting documents, product guides, how to videos, best practices, and more
Knowledge Base
One-stop self-service portal for solutions, FAQs, Whitepapers, How Tos, Videos, and more
Support TV
Video channel for step-by-step instructions to use our products, best practices, troubleshooting tips, and much more
Documentation
Information library of the latest product documents
Velocity (Best Practices)
Best practices and use cases from the Implementation team
Learn
Rich resources to help you leverage full capabilities of our products
Trainings
Role-based training programs for the best ROI
Certifications
Get certified on Informatica products. Free, Foundation, or Professional
Product Learning Paths
Free and unlimited modules based on your expertise level and journey
Resources
Library of content to help you leverage the best of Informatica products
Tech Tuesdays Webinars
Most popular webinars on product architecture, best practices, and more
Product Availability Matrix
Product Availability Matrix statements of Informatica products
SupportFlash
Monthly support newsletter
Support Documents
Informatica Support Guide and Statements, Quick Start Guides, and Cloud Product Description Schedule
Product Lifecycle
End of Life statements of Informatica products
Ideas
Events
Change Request Tracking
Marketplace
English
  • Data Integration Connectors
  • All Products

Table of Contents

Search

  1. Preface
  2. Introduction to Hive Connector
  3. Hive connections
  4. Mappings and mapping tasks with Hive Connector
  5. Migrating a mapping
  6. Data type reference
  7. Troubleshooting

Hive Connector

Hive Connector

Back Next

Hive connection properties

Hive connection properties

To use Hive Connector in a
mapping
 task, you must create a connection in
Data Integration
.
When you set up a Hive connection, you must configure the connection properties.
The following table describes the Hive connection properties:
Connection property
Description
Authentication Type
You can select one of the following authentication types:
  • Kerberos. Select
    Kerberos
     for a Kerberos cluster.
  • LDAP. Select
    LDAP
     for an LDAP-enabled cluster.
    LDAP is not applicable to mappings in advanced mode.
  • None. Select
    None
     for a Hadoop cluster that is not secure or not LDAP-enabled.
JDBC URL
*
The JDBC URL to connect to Hive.
Specify the following format based on your requirement:
  • To view and import tables from a single database, use the following format:
    jdbc:hive2://<host>:<port>/<database name>
  • To view and import tables from multiple databases, do not enter the database name. Use the following JDBC URL format:
    jdbc:hive2://<host>:<port>/
    After the port number, enter a slash.
  • To access Hive on a Hadoop cluster enabled for TLS, specify the details in the JDBC URL in the following format:
    jdbc:hive2://<host>:<port>/<database name>;ssl=true;sslTrustStore=<TrustStore_path>;trustStorePassword=<TrustStore_password>
    ,
    where the truststore path is the directory path of the truststore file that contains the TLS certificate on the agent machine.
JDBC Driver
*
The JDBC driver class to connect to Hive.
Username
The user name to connect to Hive in LDAP or None mode.
Password
The password to connect to Hive in LDAP or None mode.
Principal Name
The principal name to connect to Hive through Kerberos authentication.
Impersonation Name
The user name of the user that the Secure Agent impersonates to run mappings on a Hadoop cluster. You can configure user impersonation to enable different users to run mappings or connect to Hive. The impersonation name is required for the Hadoop connection if the Hadoop cluster uses Kerberos authentication.
Keytab Location
The path and file name to the Keytab file for Kerberos login.
Configuration Files Path
*
The directory that contains the Hadoop configuration files for the client.
Copy the site.xml files from the Hadoop cluster and add them to a folder in the Linux box. Specify the path in this field before you use the connection in a mapping to access Hive on a Hadoop cluster:
  • For mappings, you require the core-site.xml, hdfs-site.xml, and hive-site.xml files.
  • For mappings in advanced mode, you require the core-site.xml, hdfs-site.xml, hive-site.xml, mapred-site.xml, and yarn-site.xml files.
DFS URI
*
The URI to access the Distributed File System (DFS), such as Amazon S3, Microsoft Azure Data Lake Storage, and HDFS.
For mappings in advanced mode that run on the
advanced cluster
, Azure Data Lake Storage Gen2 is supported on the Azure HDinsight cluster.
Based on the DFS you want to access, specify the required storage and bucket name.
For example, for HDFS, refer to the value of the
fs.defaultFS
 property in the
core-site.xml
 file of the Hadoop cluster and enter the same value in the
DFS URI
 field.
DFS Staging Directory
The staging directory in the Hadoop cluster where the Secure Agent stages the data. You must have full permissions for the DFS staging directory.
Specify a transparent encrypted folder as the staging directory.
Hive Staging Database
The Hive database where external or temporary tables are created. You must have full permissions for the Hive staging database.
Additional Properties
Applies to mappings in advanced mode.
The additional properties required to access the DFS.
Configure the property as follows:
<DFS property name>=<value>;<DFS property name>=<value>
For example:
To access the Amazon S3 file system, specify the access key, secret key, and the Amazon S3 property name, each separated by a semicolon: 
fs.s3a.<bucket_name>.access.key=<access key value>;
fs.s3a.<bucket_name>.secret.key=<secret key value>;
fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem;
To access the Azure Data Lake Storage Gen2 file system, specify the authentication type, authentication provider, client ID, client secret, and the client endpoint, each separated with a semicolon: 
fs.azure.account.auth.type=<Authentication type>;
fs.azure.account.oauth.provider.type=<Authentication_provider>;
fs.azure.account.oauth2.client.id=<Client_ID>;
fs.azure.account.oauth2.client.secret=<Client-secret>;
fs.azure.account.oauth2.client.endpoint=<ADLS Gen2 endpoint>
*
 These fields are mandatory parameters.
0 COMMENTS
We’d like to hear from you!