red hat jboss data services platform: overview & · pdf filered hat jboss data services...
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Red Hat JBoss Data Services Platform:
Overview & Roadmap
Ken Johnson Director, Product Management Red HatJune 12, 2013
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Agenda
Data Virtualization
● What it is
● How can you benefit
JBoss Data Services Product Overview
Demo
Roadmap/Future Direction
Wrap-up, Q&A
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Data Virtualization: Overview
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Data Virtualization – Overview
Data Virtualization Process● Accessing data from disparate systems (databases,
files, services, applications, etc.)● Integrating and transforming the data, creating
canonical abstraction● Exposing information
● as a single-source● through a variety of data access methods to support different
tools and applications● access is in “real-time” from original sources
● Hide transformation and connectivity details from information consumers
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Data Virtualization – Simplistic View
Data Virtualization
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Data Virtualization – What it is Not
Time consuming – difficult/costly
No re-use of data logic
Any changes break the application
Hard CodedReplication/ETL
Data not fresh
Costly – additional licenses
More copies of data = more silos
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Data Virtualization – Benefits
Why Data Virtualization?● Quickly derive value from your data assets
● Present it to your users in the form they want through the tools they use.
● Build a flexible, agile information infrastructure that lets you quickly respond to change
● Complements existing technologies and approaches (SOA, ETL, EAI)
● Gain control of your information sprawl
Data Virtualization
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Data Virtualization – Common Use Cases
Architectural/Technical● Data Layer/Data Hub
● SOA/Data Services
● Virtual data mart/Data warehouse extension
● MDM augmentation
● Cloud data integration
Business Driven● Customer service, Single view
● Compliance, governance
● Analytics, Business Intelligence
● Mergers and Acquisitions
● Mobile enablement
● Operational Dashboards
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Red Hat JBoss Data Services
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Red Hat JBoss Data Services Platform
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Usage pattern: Connect and Compose
● Connect to sources, integrate, federate, transform data
● Create foundational data views
xml
databases
warehouses
spreadsheets
services
<sale/> <value/></ sale >
files
applications
…
Existing sources and silos of data
Integrated set of standard data views
Finance, HR
Inventory, Logistics
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Usage pattern: Compose and Consume
● Provide consistent information in the form required by different information-consuming BI/analysis applications, processes, services.
● Ensure complete and consistent information through all delivery modes/formats.
Forms: Relational Tables/Views Star schema Procedures Schema-compliant XML
Access Modes: JDBC, ODBC SOAP, REST Services POJO XML over HTTP
<WSDL><WSDL>(contract)
<WSDL><WSDL>(contract)
<WSDL><WSDL>(contract)
Custom Apps
Business Process
Packaged Apps
Reports, Dashboards
Analytics
O/R M
app
ing
JD
BC
/OD
BC
SO
AP
/RE
ST
Finance, HR
Inventory, Logistics
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Red Hat JBoss Data Services Platform
• Turn the data you have into the information you want.
• Standards-based read/write access to heterogeneous data stores in real time.
• Speeds application development by simplifying access to distributed data.
• Transforms data structure and semantics through data virtualization.
• Consolidates data into a “single view” without the need for more data.
• Centralized access control, auditing through robust security infrastructure.
• Creates services that provision data to business process in your SOA.
• Enterprise-proven – flexible, scalable, high-performance.
JBoss Enterprise Data Services
Data Service Data ServiceData View
SQL WebServices
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System view and work flow
Tooling VDB Engine Server
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System view and work flow - Tooling
Tooling VDB Engine Server
Users create data models based on metadata:
●Imported from data sources●Supplied via DDL●Provided by Engine●Specified by user
Models are packaged in a Virtual Database (VDB)
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System view and work flow - VDB
Tooling VDB Engine Server
Virtual Databases (VDBs) are deployment archives similar to .WAR.
VDBs contain●Source metadata and models●View metadata and models●System metadata●Connection information, which is bound to sources at deployment time
VDBs are deployed to the query engine (Teiid).
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System view and work flow
Tooling VDB Engine Server
Teiid Query Engine is core data virtualization functionality: Federating relational query engine. Rule and cost based optimizer, advanced query planner, caching, hint processing.
Query Engine hosts VDBs, binds to data sources, performs query execution and results processing.
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System view and work flow
Tooling VDB Engine Server
The server runtime environment is JBoss EAP. The Teiid Query engine is hosted in EAP and uses key container-provided services:● Transaction manager● JAAS security framework● Container managed data sources● EAP management infrastructure● EAP deployment
The Server: exposes views/services to consumers and managed connections and connection pools for data sources.
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Caching/Materialization for Performance
● Multiple levels of caching to meet performance requirements and manage load on source systems.
● Fully automatic to fully user controlled.
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Repository/Governance
S-RAMP: SOA Repository Artifact Model and Protocol
● OASIS specification that defines: ● a common data model for repositories, as well as ● an interaction protocol to facilitate the use of common
tooling and sharing data.● S-RAMP repository capabilities:
● Store and retrieve content and metadata● Classification of artifacts (e.g. XSD, WSDL, VDB, ...)● ATOM API
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Repository/Governance
Core Models storing standard metadata and the file content itself
Derived Models are read only and data is derived from the content
XPath2 based QL
Content extractors/derivers
Clients interact via:
● ATOM/REST
● Java via S-RAMP client
● S-RAMP browser (web-based)
● Maven
● VDB (query/read)
ATOM BINDING (REST)
Derived Models
(Read Only)
Core Model Documents
JCR Storage (Modeshape + Infinispan)
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Demo
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Demo Scenario
Text with no bullets
● Bullets layer one● Bullets layer two
● Bullets layer three
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Product Roadmap and
Future Direction
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Data Services Roadmap: JBoss DS Platform v5 -> JBoss DS Platform v6
Current: DS-P v5 Next: DS-P v6
● Simplify packaging: bundle with EAP rather than SOA● EAP 5 base --> EAP 6 base● Honor customer investment, provide SOA-P to existing users● Timing of EDS-P v6:
● Alpha: July 2013● Beta: Aug 2013● GA: Q4 2013
JBoss DS Platform v5
BPEL Rules
EAP v5
JBoss ESB
Dev Studio
+SOA
+Datatools
JON+
EDSPlugins
+SOA
Plugins
Managed
UDDI
jBPM3
Dev Studio
+DataTools
JBoss DS Platform v6
JDBC/ODBC
EAP v6
JON+
EDSPlugins
Managed
ReposData Virt/Teiid
ReposData Virt/Teiid
JDBC/ODBC
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Select Upcoming New Features
● DDL Based View Definitions
● VDB import/reuse
● VDB deployment updates
● Native Queries
● OData Support
● Source temp tables
● Source security domains
You can access these features in Teiid community releases
● Procedure Exception Handling
● NoSQL sources
● OBJECTTABLE
● JSON Production
● Column masking
● Teiid Designer 8.x
● Dashboard Builder
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DDL-based Dynamic View Creation
● Unique among data virtualization technologies/vendors
● Programmatic configuration
● In Teiid 7.7/EDS 5.x, DDL could only specify integration between multiple physical sources.
● In Teiid 8/EDS 6, DDL can be used to specify view definitions.
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DDL based Dynamic View Creation
<?xml version="1.0" encoding="UTF8" standalone="yes"?><vdb name="twitter" version="1"> <model name="twitter"> <source name="twitter" translatorname="ws" connectionjndiname="java:/twitterDS"/> </model>
<model name="twitterview" type="VIRTUAL"> <metadata type="DDL"><![CDATA[ CREATE VIRTUAL PROCEDURE getTweets(query varchar) RETURNS (created_on varchar(25), from_user varchar(25), source varchar(25), text varchar(140)) AS select tweet.* from
(call twitter.invokeHTTP(action => 'GET', endpoint =>querystring('',query as "q"))) w,
XMLTABLE('results' passing JSONTOXML('myxml', w.result) columns created_on string PATH 'created_at', from_user string PATH 'from_user', source string PATH 'source', text string PATH 'text') tweet;
CREATE VIEW Tweet AS select * FROM twitterview.getTweets; ]]> </metadata> </model></vdb>
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DDL Support
● Creation of Views
● Creation of Virtual Procedures
● Creation of Functions
● Like SQL/MED, but more feature rich
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VDB Import/Reuse Feature
VDB 1
VDB2
RDBMS
Flat FileFlat FileFlat File
ClientApplication
Services
VDB1
VDB2
combined
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VDB Import/Reuse
VDB 1
VDB2
RDBMS
Flat FileFlat FileFlat File
ClientApplication
Services
combined
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VDB Imports/Reuse
● Enables and promotes enterprise wide canonical data model
● Hides the complexity from application developers
● Improves performance
● Treats it as single source
● Materialized/cached data from individual VDBs is shared with others in combined VDB
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Native Query Support
Allow pre-defined or “canned” queries to be passed to sources directly. Take advantage of source-specific behavior.
Two Forms
● Source Table metadata
● Native() procedure
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Native Query Support
Source Table Metadata● Specified as metadata property on source table:
● nativequery="select c from g"
● Produces source query with inline view:
● "SELECT c FROM (select c from g) as x"
Native() Procedure● Allow ad-hoc native SQL to be passed to source. Metadata structure
defined at execution.
● SELECT x.* FROM (call pm1.native('select * from g1')) w,
ARRAYTABLE(w.tuple COLUMNS "e1" integer , "e2" string) AS x
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OData Support
OData (OASIS Open Data Protocol)https://www.oasisopen.org/committees/tc_home.php?wg_abbrev=odata
Objective: OASIS OData TC works to simplify the querying and sharing of data across disparate applications and multiple stakeholders for re-use in the enterprise, Cloud, and mobile devices. A REST-based protocol, OData builds on HTTP, AtomPub, and JSON using URIs to address and access data feed resources. It enables information to be accessed from a variety of sources including (but not limited to) relational databases, file systems, content management systems, and traditional Web sites.
Data Services v6 supports Odata in two ways:
● Connect to and access Odata sources
● Act as an Odata server to client applications
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Dashboard Builder
New component/application from the Polymita acquisition
● Generalized beyond BPM and BAM use cases
● Planned for inclusion in Data Services v6
● Provides the ability to create dashboards for visualizing data
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Dashboard Builder
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Product
Interoperability
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Data Services and BRMS:Reasoning: with Business Rules
● Capture and codify key decision-making logic in business rules
● Facilitate collaboration between business analysts and IT
● Process information actively
Rule sets possibilities: Pricing Fraud detection Regulatory compliance Productivity/Efficiency Control systems Product configuration...
Insurance Rules:
Age
Sex
Health
Occupation
Lifestyle
= $ Price
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Data Services and BRMS:Reasoning: with Business Rules
● Expose virtual data views through JDBC and Hibernate.
● Rule engine accesses Hibernate session to retrieve records and turn them into facts over which the engine can reason.
Hib
ernate
JDB
C
Finance, HR
Inventory, Logistics
Facts
Results
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Data Services and JBoss Data Grid:Distributed cache as a data source
● Treat JBoss Data Grid as a data source
● Combine that with other data using standard product principles
databases
warehouses
services
applications
Existing sources and silos of data
Integrated set of standard data views
Inventory, Customers
JBoss Data Grid
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Wrap-up
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Red Hat JBoss Data Services – Business Value
✔Increased ROA
✔Greater agility, faster time to solution
✔Improved organizational performance
✔Better control of information
Improved utilization of data assetsDerive more value from existing investments
Complements existing systems
Better/faster than hand codingFaster, less costly than batch data movement
Data virtualization provides loose coupling
Right data at the right time to the right peopleDecision support, BI with a complete view of
information
Powerful security, Auditing, Data FirewallAvoid data silo proliferation
Central data access and policy, Compliance
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Red Hat JBoss Middleware
MIDDLEWARE
Foundation
Dev
elop
men
t Too
ls
Accelerate
Man
agem
ent T
ools
Data Virtualization
Application Integration
Integrate
Business Process Management
User Interaction
Automate
JBoss EAP JBoss Web Server JBoss Data Grid
JBoss Data Services
JBoss Fuse JBoss A-MQ Jboss SOA
JBoss BRMS
JBoss Portal JBossDeveloper Studio
JBossOperations Network
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Related Sessions
Wednesday
10:40 - Mainframe & Database Legacy Modernization
3:40 - Red Hat Storage & Big Data
4:50 - Get Mobile-ready Fast with Red Hat JBoss Data Services Platform
4:50 - Town Hall Discussion: Big Data & Traditional Databases
Thursday
10:40 - When Big Data Goes Beyond Hadoop
3:40 - Hadoop on Red Hat Storage Server: A Reference Architecture
Friday
9:45 - Interoperability Results from SAP & Red Hat Collaboration
9:45 - Design Business Intelligence Appliances Using Red Hat Technologies
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Q&A
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