Red Hat, Inc.

Galder Zamarreño

Manik Surtani

Brian Edward Stansberry

A transaction sticky load balance policy allows a remote client to choose a target server node from a server cluster to provide a transaction service. The load balance policy directs invocations of business methods within a transaction to the same target server node. The remote client receives the load balance policy from a proxy, which is downloaded to the remote client from one of the server nodes in the server cluster. The remote client selects a target server node according to the load balance policy. The remote client then invokes the business methods within a transaction on the target server node via the proxy. The target server node can execute all of the business methods within the transaction on a Java virtual machine. The business methods can be implemented with Enterprise JavaBeans (EJBs).

Transaction sticky load balance policies

A node in a data grid receives a client request to store an object in a database, the request including the object. The node divides the object into a plurality of key value pairs and links the plurality of key value pairs. The node then stores the plurality of key value pairs in the data grid.

Performing object relational mapping for a data grid

A proxy server for a data grid receives an object and a client request to store the object in a database using a first database protocol, wherein the request and the object have a first format that complies with the first database protocol. The first proxy server translates at least one of the object or the request into a second format that complies with a second protocol used by the data grid. A node of the data grid then processes the request to store the object on the data grid.

Data grid supporting multiple protocols

A system and method for locating a data entry in a server cluster using a hash function and hash codes that can be implemented on any platform, system, or in any language. In one embodiment, a client hashes a key corresponding to a data entry to be accessed from the server cluster. The hashing is performed with a hash function that is used by a cluster of servers to provide a distributed data repository. The client further compares the hash result with hash codes of the servers to identify one of the servers as a key holder that stores the data entry. The client then requests the key holder for access to the data entry.

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Neuchatel, Switzerland

Galder Zamarreño