15.10 - Using the DataConnector Operator to Write Files and Tables in Hadoop - Parallel Transporter

Teradata Parallel Transporter User Guide

prodname
Parallel Transporter
vrm_release
15.10
category
User Guide
featnum
B035-2445-035K

In addition to writing flat files and interfacing with access modules, the DataConnector operator also has the ability to write to Hadoop files and tables. The following table briefly describes and compares the two interfaces which the DataConnector operator can use to move data from the data stream to Hadoop files and tables.

 

Interface

Description

HDFS API

Provides access to Hadoop files via the Hadoop Distributed File System Application Programming Interface, or HDFS API. The HDFS is a POSIX-compatible file system with some minor restrictions. It does not support updating files and it only supports writing files in truncate mode or append mode. The Hadoop Software is written in Java and the HDFS API is a Java JNI interface that exposes all the expected standard posix file system interfaces for reading and writing HDFS files directly by a C/C++ program. The Data Connector Producer and Consumer operators have been updated to directly access the HDFS file system using the HDFS API. All standard Data Connector file system features are supported.

"TDCH-TPT

Provides access to Hadoop files and tables via the Teradata Connector for Hadoop, or TDCH. TDCH utilizes the MapReduce framework's distributed nature to transfer large amounts of data in parallel from Hadoop files and tables to the DataConnector operator. The TDCH-TPT interface gives TPT users the ability to read and write HDFS files, Hive tables, and Hcat tables in various Hadoop-specific formats. Because this interface relies on TDCH to read and write data, many of the traditional DataConnector attributes are unsupported.

For information, see the section “Processing Hadoop Files and Tables” in Teradata Parallel Transporter Reference.

Note: GZIP and ZIP files are not supported with Hadoop/HDFS.

Note: HDFS processing can be activated simply by adding the following attribute to a Data Connector Consumer or Producer:

HadoopHost = 'default’