HDP Data Services

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Hortonworks Data Platform

HDP Data Services

Copyright © 2012-2015 Hortonworks, Inc.

Except where otherwise noted, this document is licensed under Creative Commons Attribution ShareAlike 4.0 License

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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 YARN, 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 Apache Hive

Hive Documentation

Features Overview

Temporary Tables
Cost-Based SQL Optimization
Optimized Row Columnar (ORC) Format
Streaming Data Ingestion
Query Vectorization
Comparing Beeline to the Hive CLI

Moving Data into Hive

Moving Data from HDFS to Hive Using an External Table
Using Sqoop to Move Data into Hive
Incrementally Updating a Hive Table Using Sqoop and an External Table

Hive JDBC and ODBC Drivers

Configuring HiveServer2 for LDAP and for LDAP over SSL

Troubleshooting Hive

2. SQL Compliance

INSERT ... VALUES, UPDATE, and DELETE SQL Statements
SQL Standard-based Authorization with GRANT And REVOKE SQL Statements
Transactions
Subqueries
Common Table Expressions
Quoted Identifiers in Column Names
CHAR Data Type Support

3. Running Pig with the Tez Execution Engine

4. Using HDP for Metadata Services (HCatalog)

Using HCatalog
Using WebHCat
Security for WebHCat

5. Using Apache HBase

Cell-level Access Control Lists (ACLs)
Column Family Encryption

6. Using HDP for Workflow and Scheduling (Oozie)

7. Using Apache Sqoop

Apache Sqoop Connectors
Sqoop Import Table Commands
Netezza Connector
Sqoop-HCatalog Integration
Controlling Transaction Isolation
Automatic Table Creation
Delimited Text Formats and Field and Line Delimiter Characters
HCatalog Table Requirements
Support for Partitioning
Schema Mapping
Support for HCatalog Data Types
Providing Hive and HCatalog Libraries for the Sqoop Job
Examples

List of Figures

1.1. Example: Moving .CSV Data into Hive
1.2. Using Sqoop to Move Data into Hive
1.3. Data Ingestion Lifecycle
1.4. Dataset after the UNION ALL Command Is Run
1.5. Dataset in the View

List of Tables

1.1. CBO Configuration Parameters
1.2. Beeline Modes of Operation
1.3. HiveServer2 Transport Modes
1.4. Authentication Schemes with TCP Transport Mode
1.5. Most Common Methods to Move Data into Hive
1.6. Sqoop Command Options for Importing Data into Hive
2.1. Configuration Parameters for Standard SQL Authorization
2.2. HiveServer2 Command-Line Options
2.3. Hive Compaction Types
2.4. Hive Transaction Configuration Parameters
2.5. Trailing Whitespace Characters on Various Databases