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  • Data Engineering Integration 10.2.2 HotFix 1
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Table of Contents

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  1. Preface
  2. Introduction to Big Data Management Administration
  3. Authentication
  4. Running Mappings on a Cluster with Kerberos Authentication
  5. Authorization
  6. Cluster Configuration
  7. Cloud Provisioning Configuration
  8. Data Integration Service Processing
  9. Connections
  10. Multiple Blaze Instances on a Cluster
  11. Monitoring REST API

Big Data Management Administrator Guide

Big Data Management Administrator Guide

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Hadoop Integration

Hadoop Integration

Big Data Management can connect to clusters that run different Hadoop distributions. Hadoop is an open-source software framework that enables distributed processing of large data sets across clusters of machines. You might also need to use third-party software clients to set up and manage your Hadoop cluster.
Big Data Management can connect to the supported data source in the Hadoop environment, such as HDFS, HBase, or Hive, and push job processing to the Hadoop cluster. To enable high performance access to files across the cluster, you can connect to an HDFS source. You can also connect to a Hive source, which is a data warehouse that connects to HDFS.
It can also connect to NoSQL databases such as HBase, which is a database comprising key-value pairs on Hadoop that performs operations in real-time. The Data Integration Service can push mapping jobs to the Spark or Blaze engine, and it can push profile jobs to the Blaze engine in the Hadoop environment.
Big Data Management supports more than one version of some Hadoop distributions. By default, the cluster configuration wizard populates the latest supported version.
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