Hortonworks Data Platform

Data Integration Services with HDP

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Hortonworks Data Platform (HDP) and any of its components are not anticipated to be combined with any hardware, software or data, except as expressly recommended in this documentation.

2013-05-28

Abstract

The Hortonworks Data Platform, powered by Apache Hadoop, is a massively scalable and 100% open source platform for storing, processing and analyzing large volumes of data. It is designed to deal with data from many sources and formats in a very quick, easy and cost-effective manner. The Hortonworks Data Platform consists of the essential set of Apache Hadoop projects including MapReduce, Hadoop Distributed File System (HDFS), HCatalog, Pig, Hive, HBase, Zookeeper and Ambari. Hortonworks is the major contributor of code and patches to many of these projects. These projects have been integrated and tested as part of the Hortonworks Data Platform release process and installation and configuration tools have also been included.

Unlike other providers of platforms built using Apache Hadoop, Hortonworks contributes 100% of our code back to the Apache Software Foundation. The Hortonworks Data Platform is Apache-licensed and completely open source. We sell only expert technical support, training and partner-enablement services. All of our technology is, and will remain free and open source.

Please visit the Hortonworks Data Platform page for more information on Hortonworks technology. For more information on Hortonworks services, please visit either the Support or Training page. Feel free to Contact Us directly to discuss your specific needs.

Contents

1. Using Data Integration Services Powered by Talend

1. Prerequisites

2. Instructions

2.1. Deploying Talend Open Studio
2.2. Writing Talend job for data import
2.3. Modifying the job to perform data analysis

2. Using HDP for Metadata Services (HCatalog)

1. Using HCatalog

2. Using WebHCat

2.1. Technical Update: WebHCat Standard Parameters

3. Using Apache Hive

4. Using HDP for Workflow and Scheduling (Oozie)

5. Using Apache Sqoop

1. Apache Sqoop Connectors

2. Sqoop Import Table Commands

3. Netezza Connector

3.1. Extra Arguments
3.2. Direct Mode
3.3. Null String Handling

4. Sqoop-HCatalog Integration

4.1. HCatalog Background
4.2. Exposing HCatalog Tables to Sqoop
4.3. Automatic Table Creation
4.4. Delimited Text Formats and Field and Line Delimiter Characters
4.5. HCatalog Table Requirements
4.6. Support for Partitioning
4.7. Schema Mapping
4.8. Support for HCatalog Data Types
4.9. Providing Hive and HCatalog Libraries for the Sqoop Job
4.10. Examples

6. Installing and Configuring Flume in HDP

1. Understand Flume

1.1. Flume Components

2. Install Flume

2.1. Prerequisites
2.2. Installation
2.3. Users
2.4. Directories

3. Configure Flume

4. HDP and Flume

4.1. Sources
4.2. Channels
4.3. Sinks

5. A Simple Example

7. Using Cascading

List of Tables

5.1. Supported Netezza Extra Arguments
5.2. Supported Export Control Arguments
5.3. Supported Import Control Arguments

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