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Waldemar Kot

Waldemar Kot,
Principal Systems Engineer at Oracle

About the speaker: Waldek is passionate about Java and middleware technologies. Waldek joined Oracle Polska as Principal Systems Engineer in 2008, following Oracle’s acquisition of BEA Systems. At Oracle his role is to advise customers in Eastern Europe about middleware technologies they use in application development and systems integration projects and solutions related to SOA, EDA and BPM. Waldek has extensive knowledge and experience with Java, J2EE/Java EE and Spring, but is also interested in technologies related to modern telecommunication, like IMS (IP Multimedia Subsystem), SIP, SIP Servlet or telecom web services. Waldek is also active participant of the ever-growing Java community in Poland and proud member of the Warszawa Java User Group.


Topic: Asynchronous, Concurrent and Distributed Processing in Java EE -
Examples Using Oracle Middleware Technologies: WebLogic Server,
EclipseLink/TopLink JPA i Coherence.

Language: Polish

Abstract: Ability to divide a bigger computing task into highly independent,
concurrently executing fragments, allows shortening of the response time and
better utilization of the server resporces. This is particularly true for
today’s multi-CPU and multi-core machines. It is also a common need to
initiate asynchronous processing with little to no relation to user
generated requests. Java EE specification is mostly centered around
request/response paradigm. Also, direct use of the threading mechanisms
exposed by the Java SE layer is not recommended. Contrary to (unfortunately)
common belief, it does not mean however that the server-side Java EE
applications cannot utilize asynchronous and concurrent processing. One of
the possibilities for the programmer is to use the Work Manager and Timer
APIs, both of which have been provided by the leading J2EE/Java EE
application servers for some time now. The APIs will also be part of the
next version of the Java Enterprise Edition – Java EE 6.

Processing can also be distributed, i.e. many machines can cooperate within
a grid. The grid can span both machines executing specified business logic
and machines storing data in a distributed manner (data grid). The latter
increases performance of data accesses, by means of concurrency and ability
to buffer parts of the database into the memory. At the same time, the grid
maintains high level of reliability by its various built-in clustering and
persistence mechanisms.

An interesting idea is to marry the standardization and simplicity of
application development using the Java Persistence API (JPA) with the
scalability and distributed processing power of the data grids.
During the seminar you will see some practical examples of the above
technologies to build more advanced server-side Java EE applications. During
the demonstrations we will use Oracle middleware technologies.