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 Engineering Integration 10.5.4
  • All Products

Table of Contents

Search

  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

User Guide

User Guide

Back Next

Hive Connection Properties

Hive Connection Properties

Use the Hive connection to access Hive data. A Hive connection is a database type connection. You can create and manage a Hive connection in the Administrator tool, Analyst tool, or the Developer tool. Hive connection properties are case sensitive unless otherwise noted.
The order of the connection properties might vary depending on the tool where you view them.
The following table describes Hive connection properties:
Property
Description
Name
The name of the connection. The name is not case sensitive and must be unique within the domain. You can change this property after you create the connection. The name cannot exceed 128 characters, contain spaces, or contain the following special characters:
~ ` ! $ % ^ & * ( ) - + = { [ } ] | \ : ; " ' < , > . ? /
ID
String that the Data Integration Service uses to identify the connection. The ID is not case sensitive. It must be 255 characters or less and must be unique in the domain. You cannot change this property after you create the connection. Default value is the connection name.
Description
The description of the connection. The description cannot exceed 4000 characters.
Location
The domain where you want to create the connection. Not valid for the Analyst tool.
Type
The connection type. Select Hive.
LDAP username
LDAP user name of the user that the Data Integration Service impersonates to run mappings on a Hadoop cluster. The user name depends on the JDBC connection string that you specify in the Metadata Connection String or Data Access Connection String for the native environment.
If the Hadoop cluster uses Kerberos authentication, the principal name for the JDBC connection string and the user name must be the same. Otherwise, the user name depends on the behavior of the JDBC driver. With Hive JDBC driver, you can specify a user name in many ways and the user name can become a part of the JDBC URL.
If the Hadoop cluster does not use Kerberos authentication, the user name depends on the behavior of the JDBC driver.
If you do not specify a user name, the Hadoop cluster authenticates jobs based on the following criteria:
  • The Hadoop cluster does not use Kerberos authentication. It authenticates jobs based on the operating system profile user name of the machine that runs the Data Integration Service.
  • The Hadoop cluster uses Kerberos authentication. It authenticates jobs based on the SPN of the Data Integration Service. LDAP username will be ignored.
Password
Password for the LDAP username.
Environment SQL
SQL commands to set the Hadoop environment. In native environment type, the Data Integration Service executes the environment SQL each time it creates a connection to a Hive metastore. If you use the Hive connection to run profiles on a Hadoop cluster, the Data Integration Service executes the environment SQL at the beginning of each Hive session.
The following rules and guidelines apply to the usage of environment SQL in both connection modes:
  • Use the environment SQL to specify Hive queries.
  • Use the environment SQL to set the classpath for Hive user-defined functions and then use environment SQL or PreSQL to specify the Hive user-defined functions. You cannot use PreSQL in the data object properties to specify the classpath. If you use Hive user-defined functions, you must copy the .jar files to the following directory:
    <Informatica installation directory>/services/shared/hadoop/<Hadoop distribution name>/extras/hive-auxjars
  • You can use environment SQL to define Hadoop or Hive parameters that you want to use in the PreSQL commands or in custom queries.
  • If you use multiple values for the Environment SQL property, ensure that there is no space between the values.
SQL Identifier Character
The type of character used to identify special characters and reserved SQL keywords, such as WHERE. The Data Integration Service places the selected character around special characters and reserved SQL keywords. The Data Integration Service also uses this character for the
Support mixed-case identifiers
 property.

Properties to Access Hive as Source or Target

The following table describes the connection properties that you configure to access Hive as a source or target:
Property
Description
JDBC Driver Class Name
Name of the Hive JDBC driver class. If you leave this option blank, the Developer tool uses the default Apache Hive JDBC driver shipped with the distribution. If the default Apache Hive JDBC driver does not fit your requirements, you can override the Apache Hive JDBC driver with a third-party Hive JDBC driver by specifying the driver class name.
Metadata Connection String
The JDBC connection URI used to access the metadata from the Hadoop server.
You can use PowerExchange for Hive to communicate with a HiveServer service or HiveServer2 service. To connect to HiveServer, specify the connection string in the following format: 
jdbc:hive2://<hostname>:<port>/<db>
Where
  • <hostname> is name or IP address of the machine on which HiveServer2 runs.
  • <port> is the port number on which HiveServer2 listens.
  • <db> is the database name to which you want to connect. If you do not provide the database name, the Data Integration Service uses the default database details.
To connect to HiveServer2, use the connection string format that Apache Hive implements for that specific Hadoop Distribution. For more information about Apache Hive connection string formats, see the Apache Hive documentation.
For user impersonation, you must add
hive.server2.proxy.user=<xyz>
 to the JDBC connection URI. If you do not configure user impersonation, the current user's credentials are used connect to the HiveServer2.
If the Hadoop cluster uses SSL or TLS authentication, you must add
ssl=true
 to the JDBC connection URI. For example:
jdbc:hive2://<hostname>:<port>/<db>;ssl=true
If you use self-signed certificate for SSL or TLS authentication, ensure that the certificate file is available on the client machine and the Data Integration Service machine. For more information, see the
Data Engineering Integration Guide
.
Bypass Hive JDBC Server
JDBC driver mode. Select the check box to use the embedded JDBC driver mode.
To use the JDBC embedded mode, perform the following tasks:
  • Verify that Hive client and Informatica services are installed on the same machine.
  • Configure the Hive connection properties to run mappings on a Hadoop cluster.
If you choose the non-embedded mode, you must configure the Data Access Connection String.
Informatica recommends that you use the JDBC embedded mode.
Fine Grained Authorization
When you select the option to observe fine grained authorization in a Hive source, the mapping observes the following:
  • Row and column level restrictions. Applies to Hadoop clusters where Sentry or Ranger security modes are enabled.
  • Data masking rules. Applies to masking rules set on columns containing sensitive data by Dynamic Data Masking.
If you do not select the option, the Blaze and Spark engines ignore the restrictions and masking rules, and results include restricted or sensitive data.
Data Access Connection String
The connection string to access data from the Hadoop data store. To connect to HiveServer, specify the non-embedded JDBC mode connection string in the following format: 
jdbc:hive2://<hostname>:<port>/<db>
Where
  • <hostname> is name or IP address of the machine on which HiveServer2 runs.
  • <port> is the port number on which HiveServer2 listens.
  • <db> is the database to which you want to connect. If you do not provide the database name, the Data Integration Service uses the default database details.
To connect to HiveServer2, use the connection string format that Apache Hive implements for the specific Hadoop Distribution. For more information about Apache Hive connection string formats, see the Apache Hive documentation.
For user impersonation, you must add
hive.server2.proxy.user=<xyz>
 to the JDBC connection URI. If you do not configure user impersonation, the current user's credentials are used connect to the HiveServer2.
If the Hadoop cluster uses SSL or TLS authentication, you must add
ssl=true
 to the JDBC connection URI. For example:
jdbc:hive2://<hostname>:<port>/<db>;ssl=true
If you use self-signed certificate for SSL or TLS authentication, ensure that the certificate file is available on the client machine and the Data Integration Service machine. For more information, see the
Data Engineering Integration Guide
.
Hive Staging Directory on HDFS
HDFS directory for Hive staging tables. You must grant execute permission to the Hadoop impersonation user and the mapping impersonation users.
This option is applicable and required when you write data to a Hive target in the native environment.
Hive Staging Database Name
Namespace for Hive staging tables.
The Hive Staging Database Name is automatically updated from the Data Access Connection String. If you want to override the default name, you need to configure the Hive Staging Database Name in the Hive connection.
This option is applicable when you run a mapping in the native environment to write data to a Hive target.
If you run the mapping on the Blaze or Spark engine, you do not need to configure the Hive staging database name in the Hive connection. The Data Integration Service uses the value that you configure in the Hadoop connection.
0 COMMENTS
We’d like to hear from you!