Episode 13 - Getting started with ADO.NET REST data service
ado dot net getting started tomcat demonstrates how to bring up the grid and bring up the data service framework using the getting started sample, then how to see what is happening in the grid. This first video uses tomcat and the second video uses the admin console. Download the sample from the main blog page.
ADO.NET REST Data Services Getting Started
Episode 12 - ADO.NET REST Data Service
These videos demonstrate how to set up an eXtreme Scale Data Service, and see it run with a web browser sample. Create a grid using the REST getting started steps, install and configure tomcat, and deploy the war file. The result is a working ADO.Net REST Data Service talking to an eXtreme Scale grid, ready to be a data service for any ADO.Net client applications.
eXtreme Scale Scale ADO.NET Data Services - Part 1
IBM eXtreme Scale ADO.NET Data Service Howto - Part 2
Episode 11 - Version 7 overview, memory density, ADO.NET REST Data Service
Overview of what's new in WebSphere eXtreme Scale V7.0: IBM WebSphere eXtreme Scale V7.0 ships
Memory density improvements in V7.0: Memory density improvements in WebSphere eXtreme Scale V7.0
How to lower back-end costs considerably using IBM WebSphere eXtreme Scale: Saving money on backend systems with WebSphere eXtreme Scale
Description of WebSphere eXtreme Scale chargeable units. What are they? Understanding how WebSphere... [More]
Episode 10 - Impact wrap-up, routing, patterns and optimistic locking
Recap of what happened at IBM Impact 2009 in regards to eXtreme Scale: IBM Impact wrap up on IBM WebSphere eXtreme Scale
How eXtreme Scale routing works for clients: Under the cover: How does client partition routing work in IBM WebSphere eXtreme Scale
How and why to use the numInitialContainers deployment policy attribute when starting large grids: Starting large grids with numInitialContainers
Overview of optimistic locking: Under... [More]
Episode 9 - IBM Impact 2009 session overview, classifying styles of XTP and hub and spoke replication, Write-behind developerWorks article
Overview of eXtreme Transaction Processing (XTP): What is XTP (eXtreme Transaction Processing)? Step 1: Classifying transactional systems
How to choose between class 1 and 2 XTP systems: Class 1 and Class 2 XTP systems, how to choose between them and the advantages of class 2 systems
Hub and spoke replicated transactional systems with eXtreme Scale: Hub and spoke replicated... [More]
Episode 8 - Eliminating parallel queries, performance testing, write-behind error handling, reverse indexes and Impact 2009 preview
Techniques for eliminating parallel, grid-wide queries: Best practises for eliminating parallel queries
Discussion on why warming-up a JVM is important when performance testing: How to warm up JVMs correctly before measuring performance
How to handle write-behind errors: Handling write behind errors correctly in applications
Using reverse indexes for fast lookups: Reverse... [More]
Episode 7 - PureQuery loaders, stored procedure caching, stateful singletons and large query sets.
Using IBM Data Studio PureQuery to create a general purpose loader: Using IBM DataStudio PureQuery runtime with IBM WebSphere eXtreme Scale
Using maps and loaders to cache stored procedure results: Creating an elastic service for a stored procedure call using IBM WebSphere eXtreme Scale
Techniques for caching query results in blocks for pagination support: Storing query results in pages or blocks rather than a single... [More]
Episode 6 - Embedded vs. external grid, 2PC, HTTP Session replication, and choosing partitions.
How to choose whether to embed the grid in application processes or run in separate processes: Run the grid in the application JVMs or separately?
Why eXtreme Scale doesn't provide 2-phase commit protocol (2PC): Does IBM WebSphere eXtreme Scale support 2PC?
Using eXtreme Scale for HTTP Session replication: HTTP Session replication with IBM WebSphere eXtreme Scale
Best practice for choosing the number of... [More]
Episode 5 - Trial overview, heap based evcition, removeAll(), near cache and write-behind with sync replicas.
An overview of the eXtreme Scale trial, including it's capabilities and limitations: Trial version of IBM WebSphere eXtreme Scale
Using heap level based eviction with a traditional eviction strategy: Heap level triggered eviction in IBM WebSphere eXtreme Scale
Using removeAll() as a high performance alternative to remove(): removeAll instead of remove in IBM WebSphere eXtreme Scale
The near... [More]
Episode 4 - Clearing a map, Spring integration, and zones.
How to efficiently clear the contents of a map: How to quickly empty a Map in IBM WebSphere eXtreme Scale
Overview of eXtreme Scale Spring integration features: Spring Integration features in IBM WebSphere eXtreme Scale
How to use eXtreme Scale zones to control primary and replica placement: Zones, what are they and how does IBM WebSphere eXtreme Scale use them
Episode 3 - JPALoaders, database synchronization, WAS integration, and JPA vs. ObjectGrid APIs.
How to use JPALoaders for automatically integrating with relational databases: Automatic database integration with IBM WebSphere eXtreme Scale
How to deal with third party or legacy applications changing a database directly without updating the cache: Handling stale data in IBM WebSphere eXtreme Scale
How WebSphere eXtreme Scale integrates with WebSphere Application Server: Integration of IBM WebSphere eXtreme Scale with... [More]
Episode 2 - L2 cache for JPA, write-behind and high availability.
Using eXtreme Scale for a L2 cache for OpenJPA or Hibernate: OpenJPA/Hibernate L2 cache with WebSphere eXtreme Scale
Write-behind database synchronization overview and use cases
Write behind: What is it and how does it work?
WebSphere eXtreme Scale and Databases with more on write behind
Achieving high availability with eXtreme Scale: High Availability: Data availability in WebSphere eXtreme Scale
Episode 1 - Preloading, duplicate data, dynamic map creation, and putAll().
Data preloading techniques; Loader plug-ins vs. Client loaders: Best ways to preload data
Duplicating data over all partitions and denormalization: Normalization and reference data
ObjectMap.putAll behaviors: Put verb mechanics explanation
Dynamic map creation