Ambari Views Guide
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

2015-12-21

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 Ambari Views
2. Preparing Ambari Server for Views
3. Running Ambari Server Standalone
Prerequisites
Standalone Server Setup
Reverse Proxy
4. Configuring Views for Kerberos
5. Using the Tez View
Configuring Your Cluster for Tez View
Creating or Editing the Tez View Instance
User Permissions for Tez Views
Kerberos Setup for Tez Views
Using the Tez View
Understanding Directed Acyclic Graphs (DAGs), Vertices, and Tasks
Identifying the Tez DAG for Your Job
Understanding How Your Tez Job Is Executed
Identifying Causes of Failed Jobs
Viewing All Failed Tasks
Using Counters to Identify the Cause of Slow-Performing Jobs
6. Using the Pig View
Configuring Your Cluster
Setup HDFS Proxy User
Setup WebHCat Proxy User
Setup HDFS User Directory
Creating the Pig View Instance
Getting Correct Configuration Values for Manually-Deployed Clusters
User Permissions for Pig Views
Kerberos Setup for Pig Views
Using the Pig View
Writing Pig Scripts
Viewing Pig Script Execution History
User-Defined Functions (UDFs) Tab
7. Using the Capacity Scheduler View
Configuring your Cluster for the Capacity Scheduler View
Creating a Capacity Scheduler View Instance
User Permissions for Capacity Scheduler Views
Using the Capacity Scheduler View
Setting up Queues
Configuring Queues
Configuring Cluster Scheduler Settings
Applying the Configuration Changes
Troubleshooting
8. Using the Hive View
Configuring Your Cluster
Setup HDFS Proxy User
Setup HDFS User Directory
Creating the Hive View Instance
Settings and Cluster Configuration
User Permissions for Hive Views
Kerberos Setup for Hive Views
Using the Hive View
Query Tab
Saved Queries Tab
History Tab
UDF Tab
Troubleshooting
9. Using the Slider View
Deploying the Slider View
10. Using the Files View
Configuring Your Cluster
Creating and Configuring a Files View Instance
Kerberos Settings
Cluster Configuration: Local
Cluster Configuration: Custom
Troubleshooting