Posted by Virgil , 22 April 2013 - 06:46 AM
It’s a good thing BIRT is not your traditional data processing application!
Eclipse BIRT was built with data source extensibility in mind. BIRT does this by leveraging the Eclipse Data Tools Project (DTP) and more specifically, the Open Data Access (ODA) framework. This framework allows new data sources, like recent big data sources, to be easily added to BIRT as needed. This post walks through creating a connection to Hadoop in order to visualize the data within BIRT.
Using HQL to query Hadoop data
BIRT provides an out-of-the-box driver that allows access to Hadoop Data through Hive using Hive Query Language (HQL). Hive is a data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis. To retrieve data from Hadoop, you write a query in Hive
Query Language (HQL). HQL supports many of the same keywords as SQL, for example
SELECT, WHERE, GROUP BY, ORDER BY, JOIN, and UNION.
A Hive query is executed by a series of automatically generated MapReduce jobs.
Alternatively, you can use the TRANSFORM statement to specify scripts that translate into
MapReduce functions in Hadoop. These scripts can be written in virtually any programming language. For example, the following HQL query specifies the script file mytest.py, written in the Python programming language.
SELECT TRANSFORM (userid, movieid, rating, unixtime) USING 'python mytest.py' AS (userid, movieid, rating, weekday) FROM u_data
Creating an HQL query in BIRT
To create a new query, select Hive Datasource from the New Data Source wizard
and enter the connection properties, as shown in the figure below.
Next, choose Manage Drivers and add the Hive client JAR files. You
only need to do this once.
Now, you can create a data set by writing an HQL query. If your query uses TRANSFORM
statements that reference script files, use the Add File Statement property to add files to the
Hadoop distributed cache. Type a semicolon-separated list of Add File commands. This property can be overridden by the data source or data set, using property binding or script. Type the HQL query in the query text area of the data set editor as shown below.
Complex HQL Subquery Example
Get JSON Object Example
Regular Expression Example
HQL Hints Example
Getting the Important Data to Stand Out
You can create multiple data sets using the same steps above, even joining data sets within BIRT. Once you have your big data connections and queries defined, you can start using the data to define your report within BIRT. At this point, you can simply drag your data sets onto the report canvas and start formatting.
But, being able to store more data brings its own new sets of challenges. The more data collected typically means more data that needs to be analyzed and displayed. This means, the important data really needs to stand out. BIRT supports this with several out-of-the-box features.
With the Highlighting feature in BIRT, you can set up formatting rules that are based on expressions. You can create simple to quite complex expressions in order to highlight the data. Highlighting can be added to grids, tables, columns, rows, data elements, labels, charts, and images.
The Visibility feature allows you to use expressions to decide which areas of BIRT are visible. This is quite useful for allowing certain groups of people to see only their data but can also be used to hide whole areas based on the data discovered. Visibility can also be applied to grids, tables, columns, rows, data elements, labels, charts, and images, but you can also have seperate visibility rules based on the final output, like PDF, HTML, etc.
Try it Yourself
The Hive/Hadoop data source has been available since BIRT 3.7 and can be downloaded as part of the Eclipse BIRT Designer from eclipse.org/birt or BIRT Exchange.
Posted by Virgil , 14 March 2012 - 02:11 PM
There are 3 BIRT Sessions in this years EclipseCon conference program:
What is BIRT? Quick Jumpstart (presented by Virgil Dodson)
This session introduces BIRT and looks at how you can leverage BIRT to quickly create data-driven reports, web pages, and compelling information visualizations using its visual drag-and-drop design environment. This session provides a great orientation to the BIRT project and technology and how it might benefit your applications.
Extending BIRT with Plug-ins (presented by Michael Williams)
This session will show off several new plug-ins created by the community from a recent BIRT plug-in contest and also show step-by-step use of the ODA wizard to create a new BIRT data source and show where to find current plug-ins in the source code to use as a starting point for creating your own BIRT plug-ins faster. Attendees will leave this talk with an understanding of BIRT plug-ins and the various ways to extend BIRT.
Introduction to BIRT (by John Ward)
This tutorial will walk users through the BIRT environment and guide them through building their first few reports using the BIRT reporting tool
BIRT and Big Data
Pick up a whitepaper in the BIRT Exchange booth with step-by-step instructions on how to connect, access and display Hadoop data using HIVE Query Language (HQL) within BIRT-based applications.
Contests and Prizes
There will be lots of random giveaways to booth visitors, and we’ll announce a developer contest where we’ll be awarding three (3) new iPads.
Visualizing Big Data with Hadoop and BIRT
BIRT DZone RefCard Updated for BIRT 3.7
BIRT and Big Data at EclipseCon 2012
Announcing BIRT Style Contest
BIRT Techies Needed
BIRT Sessions at EclipseCon 2011
BIRT Roadshow Now More Technical
BPM and BI Webinar Replay Available
BPMS plus BIRT equals Better Business Decision Making
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