WebSphere eXtreme Scale can be installed using three different methods v Trial

Websphere extreme scale can be installed using three

This preview shows page 362 - 365 out of 568 pages.

WebSphere eXtreme Scale can be installed using three different methods: v Trial install v Stand-alone deployment v WebSphere Application Server integrated deployment Scalable data model in eXtreme Scale The Microsoft Northwind sample uses the Order Detail table to establish a many-to-many association between Orders and Products. Object to relational mapping specifications (ORMs) such as the ADO.NET Entity Framework and Java Persistence API (JPA) can map the tables and relationships using entities. However, this architecture does not scale. Everything must be located on the same machine, or an expensive cluster of machines to perform well. 350 IBM WebSphere eXtreme Scale: Administration Guide April 2012
Image of page 362
To create a scalable version of the sample, the entities must be modeled so each entity or group of related entities can be partitioned based off a single key. By creating partitions on a single key, requests can be spread out among multiple, independent servers. To achieve this configuration, the entities have been divided into two trees: the Customer and Order tree and the Product and Category tree. In this model, each tree can be partitioned independently and therefore can grow at different rates, increasing scalability. Customers CustomerID CompanyName ContactName ContactTitle Address City Region OrderID CustomerID EmployeeID OrderDate RequiredDate ShippedDate ShipVia OrderID ProductID UnitPrice Quantity Discount CategoryID CategoryName Description Picture ProductID ProductName SupplierID CategoryID QuantityPerUnit Orders Order Details Categories Products Figure 45. Microsoft SQL Server Northwind sample schema diagram Chapter 6. Configuring 351
Image of page 363
For example, both Order and Product have unique, separate integers as keys. In fact, the Order and Product tables are really independent of each other. For example, consider the effect of the size of a catalog, the number of products you sell, with the total number of orders. Intuitively, it might seem that having many products implies also having many orders, but this is not necessarily the case. If this were true, you could easily increase sales by just adding more products to your catalog. Orders and products have their own independent tables. You can further extend this concept so that orders and products each have their own separate, data grids. With independent data grids, you can control the number of partitions and servers, in addition to the size of each data grid separately so that your application can scale. If you double the size of your catalog, you must double OrderDetail order (key) * orderDetails 1 <<Root Entity> Customer String String String String String int customerId (key) companyName contactName city country version Order int Date String String int String orderId (key) orderDate shipCity shipCountry version customer_customerId (key) orders 1 customer (key) * int String float short double int String String productId (key) categoryId discount quantity unitPrice version order_customer_customerID (key) order_orderId (key) Figure 46. Customer and Order entity schema diagram
Image of page 364
Image of page 365

You've reached the end of your free preview.

Want to read all 568 pages?

  • Fall '19
  • Grid Computing, IBM Corporation, Client-server, IBM WebSphere Application Server, IBM WebSphere Application Server Community Edition

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture