Corporate Overview

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					Central Data Exchange
Environmental Information Exchange Network




   Exchange Network Enhancements

                By David Fladung

                 April 19, 2006
                           Agenda

• CDX Overview
• Open Source Utilization
• Data Transformation (Mapper)
• Business Process Execution Language (BPEL)
• Rich User Interface (RUI) client
• Geographic Data Interaction
CDX Overview
CDX Overview
                    Open Source Utilization

• CDX utilizes about 50 open source products/frameworks
   • JBoss (Wind River Node application server)
   • PostgreSQL (Wind River Node database)
   • Struts (Model View Controller [MVC])
   • Hibernate (Object Relational Mapping [ORM])
   • Axis (WS engine and libraries)
   • Maven (build and release management)
   • AspectJ (quality of service)
   • StAX (streaming parsing of large XML)
   • Velocity (templating/mapping)
   • Quartz (job scheduling)
   • ActiveBPEL (business process management)
Open Source Utilization




                          Yellow – current open source implementation
                          Grey – potential for open source implementation
                          White – not applicable
                    Open Source Utilization

• Advantages
    • Low Total Cost of Ownership (TCO)
    • Rich user community
    • Adequate documentation
    • Proven performance
    • Promotes rapid development
    • Easy to integrate
• Disadvantages
    • Potential that product may no longer be supported
    • Advanced support may require cost
                     Data Transformation

• Convert from one data format to another
    • XML
    • Flat file (i.e. delimited)
    • Database
• Handle large file sizes
    • Use streaming approach rather than in memory
• Provide a robust and reusable interface
    • Standard configuration files
    • Standard APIs
    • Reusable across multiple tiers
                     Data Transformation

• TRI OUT – flat file to XML
• NC Node – database to XML for Beaches and NEI data
• Puerto Rico Node – flat file to XML for AQS data
• Wind River Node – database to XML for AQS
• Geo Toolkit for Region 5 – XML to XML for Geo data
• EnviroFlash – flat file to unstructured email (text)
• TRIME (XML to database)
• Water Sentinel (database to XML, XML to database)
• GLNPO (database to Excel, database to XML)
Data Transformation




                      Yellow – current use of mapper implementation
                      White – not applicable
                     Data Transformation

• Architecture
    • Mapping engine
        • Run the transformation process
        • Built on the Velocity open source project
    • Configuration files
        • Mapping instructions
        • Location of the data sources and data targets
        • Conditional logic, custom methods
    • Custom Java methods - provides the custom transformation
    such as data formatting.
    • Pluggable readers
    • Pluggable writers
                       Data Transformation

• Mapping steps
   • Logical mapping
        • The process of analyzing the data source and the data
        target and creating the document that specifies the relations
        between the source and target fields.
        • If the data source is relational database, this process
        includes developing the query to extract the data from the
        database.
   • Physical mapping - the process of creating the configuration
   files to implement the logical mapping specifications.
   • Custom methods (if needed)
                                       Data Transformation

• Database to XML (Puerto Rico Node)
   ## Database Query
   #set ($sqlQuery = "select distinct TRANSACTION_TYPE, ACTION_CODE, STATE_CODE, COUNTY_CODE, SITE_ID from ${tableName}RA
   where ACTION_CODE = 'D' and TRANSACTION_TYPE = 'RA'")
   ## Set Reader properties
   #set ($tmp = $MapperEngine.setMapReaderProperty('SQL_COMMA ND', $sqlQuery ) )
   #set ($tmp = $MapperEngine.setMapReaderProperty('E NCODING', 'XML_ENCODING') )
   ## Loop for each record in result set
   #foreach($row in $MapperEngine.get Iterator())
   ## Write XML
   <aqs:ActionRawDataDelete>
            <aqs:SiteIdentifierDetails>
   ## Use value from record as a variable
        <aqs:StateCode>$!row.S TA TE_CODE</aqs:StateCode>
        <aqs:CountyCode>$PRFunctions.get NumberDigitStr($!row.COUNTY_CODE , 3)</aqs:CountyCode>
        <aqs:SiteNumber>$PRFunctions.getNumberDigitStr($!row.S ITE_ID , 4)</aqs:SiteNumber>
      </aqs:SiteIdentifierDetails>
   ## Call subsequent execution
   #set( $config = $MapperEngine.createMapperConfiguration() )
   #set ($tmp = $!config.ContextConfig.put( 'SITE_ID', $!row.SITE_ID ))
   #set ($tmp = $!config.ContextConfig.put( 'tableName', $tableName ))
   #set ($tmp = $!config.ContextConfig.put( 'subs', 'PRMonitorDeleteRAMap' ))
   $MapperEngine.subExecute('MapperServices/PR/PRDB ReadConfig. vm', 'MapperServices/PR/PRMonitorDeleteRAMap. vm', $config)
   </aqs:ActionRawDataDelete>
   #end
                                          Data Transformation

• Flat file to unstructured text through custom Java (EnviroFlash)
   ## Column names for delimited text file
   $MapperEngine.setMapReaderProperty('COL_NAMES_LIS T',['CITY ','COUNTY ','S TA TE','UV_INDE X', 'UV_A LERT'])
   ## Delimiter
   $MapperEngine.setMapReaderProperty('DELIMITER','\|')
   ## Loop for all records in text file
   #foreach($row in $MapperEngine.get Iterator())
   #if($templateCallback.isCitySubscribedTo($row.S TA TE, $row.CITY, $row.COUNTY))
   ## Use values from record as variable
   #set( $config = $MapperEngine.createMapperConfiguration() )
   #set ($tmp = $!config.ContextConfig.put( 'CITY', $row.CITY ) )
   #set ($tmp = $!config.ContextConfig.put( 'COUNTY', $row.COUNTY ) )
   #set ($tmp = $!config.ContextConfig.put( 'STATE', $row.STATE ) )
   #set ($tmp = $!config.ContextConfig.put( 'UV_INDE X', $row.UV_INDE X ) )
   #set ($tmp = $!config.ContextConfig.put( 'UV_ALERT', $row.UV_ALERT ) )
   #set ($tmp = $!config.ContextConfig.put( 'subscriberURL', $subscriberURL ) )
   #set ($tmp = $!config.ContextConfig.put( 'environmentName', $environment Name ) )
   #set ($tmp = $MapperEngine.subExecute('gov/epa/cdx/enviroflash/uv/templates/writeUVMailConfig. vm',
   'gov/epa/cdx/enviroflash/uv/templates/writeUVMailMap. vm', $config) )
   #set ($outMail = $!MapperEngine.getObjectCacheMap().get ('OUT_MAIL') )
   #set ($tmp = $templateCallback.sendEmail($outMail, $row.STATE, $row.CITY, $row.COUNTY, $row.UV_ALERT) )
   #end
   #end
                        Data Transformation

• Advantages
    • Provides an ability to concentrate mapping logic within the
    configuration file and custom methods.
    • Provides ability to handle several data source types.
    • Provides an ability to decouple readers and writers.
    • Provides streaming capabilities to handle large size files (tested
    against 680 MB).
    • Provides an ability to use custom Java methods.
    • Does not require license fee.
    • Requires minimum coding.
    • Superior performance compared to commercial tools (XAware,
    BEA Liquid Data) - 30 times faster on large data sets.
    • Uses streaming approach for low memory overhead.
                             BPEL

• BPEL is a standard for orchestrating Web Services.
    • XML based description of a business process
    • Contains references to supporting WSDL files
    • Portable between BPEL engines
• BPEL allows for a formal specification of business processes.
• BPEL meshes well with Service Oriented Architectures (SOA).
• BPEL provides several useful constructs
    • Transaction context management
    • Synchronous and asynchronous web service invocation and
    response
    • Conditional branching
    • Parallel flow activities
    • Fault handling and exception invocation
BPEL
                              BPEL

• BPEL within CDX
    • Motivations
        • Can it simplify the design of existing dataflows?
        • Can it reduce the cost of dataflow development?
        • Can it speed up the process of integrating CDX Web and
        Node applications?
        • Can it provide better visibility into existing flows?
    • Goals
        • Identify a target platform.
        • Demonstrate feasibility of deployment/integration.
        • Demonstrate ability to reuse existing CDX services.
        • Determine if BPEL allows for quick development of dataflow
        components.
                               BPEL

• Prototype specifics
    • Exposed generic CDX services (Java) as Web Services
        • XML validation
        • Retrieval of transaction/document metadata
        • Created a CDX Services project to host the web services
    • Model existing National Emissions Inventory (NEI) dataflow.
    • Enhance CDX infrastructure to support use of BPEL
    orchestration.
    • Configure a production-like environment to host the services.
        • Deploy ActiveBPEL engine (deployed within Tomcat)
        • Set up persistence of processes (Oracle DMBS)
BPEL
BPEL
BPEL
BPEL
                               BPEL

• Findings
    • BPEL prototype demonstrates feasibility in the EPA
    environment.
    • Appears that cost savings could be realized for future flows as
    the CDX service suite increases, however, it is not yet clear what
    the savings are.
    • Learning curve is not insignificant
    • Tools have not yet reached full maturity.
                             RUI Client

• Guidelines
    • Provide more features/capabilities than a web application is
    capable of delivering.
    • Provide flexible configuration for interaction with multiple
    Nodes.
    • Support all existing Exchange Network Web Services and
    dataflows.
    • Provide pluggable transformation/visualization for multiple
    dataflows (Mapper, XML binding).
    • Use NAAS for authentication/authorization.
RUI Client
RUI Client
RUI Client
RUI Client
                            RUI Client

• Current capabilities
    • Supports submit, download, and transaction history search
    • Supports configurable data transformation
    • Supports NAAS authentication/authorization
• Future capabilities
    • Support query and data visualization
    • Add ability to sign/encrypt documents (CROMERR)
                  Geographic Data Interaction

• Some dataflows have geographic data (e.g. FRS)
    • Provide the capability to visualize data
    • Provide the capability to update the data
• API’s exist for addressing geographic data
    • Google Maps
    • ESRI products suite
• CDX approach
    • Integrate Google Maps API into CDX web applications
    • Provide end to end solution for querying and updating data

				
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