Apache Ambari Views
Also available as:
PDF
loading table of contents...

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.

2018-06-13

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. Understanding Ambari Views
Views Terminology
Understanding Views Development, Persona, Versions, and Deployment
2. Administering Ambari Views
Preparing Ambari Server for Views
Running Ambari Server Standalone
Prerequisites For Standalone Ambari Servers
Setting Up Standalone Ambari Server Compared with Setting Up Operational Ambari Server
Running Standalone Ambari Server Instances Behind a Reverse Proxy
Configuring View Instances
Creating View Instances
Migrating View Instance Data
Creating View URLs
Setting View Permissions
Configuring Views for Kerberos
Migrating Hue Artifacts to Ambari Views
Requirements for Hue-to-Views Migration
Creating a HueToAmbari View Instance
Migrate Hue Artifacts to an Ambari View
Configuring Specific Views
Configuring Capacity Scheduler View
Configuring Files View
Configuring Falcon View
Configuring Hive View
Configuring Pig View
Configuring Slider View
Configuring SmartSense View
Configuring Storm View
Configuring Tez View
Configuring Workflow Manager View
3. Using YARN Queue Manager View
Setting up Queues
Configuring Queues
Enabling Preemption
Setting YARN Queue Priorities
Configuring Cluster Scheduler Settings
Applying the Configuration Changes
4. Using Files View
5. Using Falcon View
6. Using Hive View 2.0
Query Tab
Visual Explain Plan
Jobs Tab
Tables Tab
Creating Tables
Uploading Tables
Saved Queries Tab
UDFs Tab
Settings Tab
7. Using Pig View
Writing Pig Scripts
Viewing Pig Script Execution History
User-Defined Functions (UDFs) Tab
8. Using Slider View
9. Using SmartSense View
10. Using Storm View
Monitoring Storm Cluster Status: the Cluster Summary Page
Monitoring Topology Status: the Topology Summary Page
Looking Up Configuration Values: the Component Summary Page
11. Using Tez View
Understanding Directed Acyclic Graphs (DAGs), Vertices, and Tasks
Searching and Identifying Hive Queries
Analyzing the Details of Hive Queries
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
12. Using Workflow Manager View

List of Figures

2.1. Configuring Views with your HDP Cluster
2.2. Default Hive View Settings
2.3. Default Hive View Cluster Configuration
2.4. HDFS Service Page in Ambari
2.5. Using the Filter to Search Advanced hdfs-site Settings
2.6. Granting User Permissions to Hive Views
2.7. Pig View Details and Settings
2.8. Pig View Cluster Configuration
2.9. HDFS Service Page in Ambari
2.10. Using the Filter to Search Advanced hdfs-site Settings
2.11. Granting User Permissions to Pig View
2.12. Kerberos Settings for Pig View
2.13. Tez View Create Instance Page
2.14. Tez View Instance Page
2.15. Granting User Permissions to Tez View
2.16. Workflow Manager Kerberos Configuration for Oozie
2.17. wfm-oozie-proxy-user.png
6.1. Views Menu of Ambari
6.2. Links to Hive-Related Views in Ambari
6.3. Query Editor
6.4. Database and Table Pane
6.5. SQL in Query Editor with Resulting Visual Explan Plan
6.6. Details of a Map Join Node
6.7. Jobs Tab of Hive View 2.0
6.8. Table Manager
6.9. Example of Information in the DDL Subtab
6.10. Example of Storage Information Subtab
6.11. Example of Detailed Information Subtab
6.12. Example of Statistics Subtab
6.13. Example of Creating a Table Form
6.14. Saved Queries Tab
6.15. UDF Tab
6.16. Settings Tab with Example Key and Value for One Property
7.1. Pig Script Running in Pig View
7.2. Pig View Script History Tab
7.3. Pig View UDFs Tab
11.1. Views Menu of Ambari
11.2. SQL Query Execution in Hive
11.3. Hive Queries Tab Showing Unfiltered Results
11.4. Details for a Successful Query with Links to Application and DAG Windows
11.5. Total Timeline and Log Details of a Submitted Query
11.6. Configurations Tab
11.7. All DAGs View (Truncated Screenshot)
11.8. Tez View Column Selector Dialog Box
11.9. View Tab in Tez View
11.10. DAG Details Window
11.11. Tez View All Tasks Tab
11.12. Tez View DAG-Level Counters Tab
11.13. Tez View Vertex Swimlane Tab
11.14. Tez View Vertex Details Subtab
11.15. Tez View Vertex-Level Counters Tab
11.16. Tez View Task-Level Counters Tab

List of Examples

2.1. Substitute #USER#