Bea Systems, Inc.

Oracle International Corporation

Salesforce Com, Inc.

Dean Bernard Jacobs

Eric M Halpern

Seth John White

Adam Messinger

Rob Woollen

Anno Langen

Ananthan Bala Srinivasan

Prasad Peddada

Simon Y Wong

Eric David Bezar

Rahul Srivastava

Doug Chasman

Naresh Revanuru

Reto Kramer

Sam Pullara

William John Gallagher

Matthew Shinn

Robert Woollen

Rob Woolen

Anno R Langen

Multiple application server instances can be arranged in a cluster that implements a distributed EJB timer system. A high availability database can store EJB timer info. The EJB timer jobs can be distributed among the application server instances of the cluster that implement the distributed EJB timer system. In case of a failure of an application server instance, the EJB timer info can be used to reassign the EJB timer jobs associated with the failed application server instance.

EJB cluster timer

The efficiency and versatility for the implementation of formulas in an on-demand database is improved. Workflow field formulas are triggered by actions in a workflow, to produce values in fields. Resulting values are protected by preventing a subsequent reevaluation of the workflow field formula from taking place when values of input fields used in the workflow field formula change.

Implementing workflow field formulas

Servers in a network cluster can each store a copy of a data item in local cache, providing read access to these copies through read-only entity beans. The original data item in the database can be updated through a read/write entity bean one of the cluster servers. That cluster server has access to an invalidation target, which contains identification information relating to copies of the data item stored on servers in the cluster. Once the read/write bean updates the data item in the database, an invalidate request can be sent or multicast to all cluster members, or to any read-only bean or server contained in the invalidation target. Each server or read-only bean receiving the request knows to drop any copy of the data item in local cache, and can request a current copy of the data item from the database.

System and method for providing a cache that stores entity beans and employs data invalidation

The efficiency and versatility for the implementation of formulas in an on-demand database is improved. Formulas are categorized. Based at least partly on the categorization, formulas are evaluated synchronously or asynchronously. An asynchronous evaluation may be performed if a certain set of criteria is not satisfied. Asynchronous evaluations may be performed using a queue. During an asynchronous update of an object, a counter field and/or an estimate field may be used respectively for indicating the consistency of values of the object and a time when the values were consistent. The versatility of formulas is enhanced by using a formula to create a default value for a custom field when it is created and to determine whether an action is to be performed, and is enhanced by having an action define when a formula is to be updated.

Implementing formulas for custom fields in an on-demand database

A clustered enterprise distributed processing system. The distributed processing system includes a first and a second computer coupled to a communication medium. The first computer includes a virtual machine (JVM) and kernel software layer for transferring messages, including a remote virtual machine (RJVM). The second computer includes a JVM and a kernel software layer having a RJVM. Messages are passed from a RJVM to the JVM in one computer to the JVM and RJVM in the second computer. Messages may be forwarded through an intermediate server or rerouted after a network reconfiguration. Each computer includes a Smart stub having a replica handler, including a load balancing software component and a failover software component. Each computer includes a duplicated service naming tree for storing a pool of Smart stubs at a node.

Smart stub or enterprise java bean in a distributed processing system

A system for managing a message store in a network includes an object acting as a message store. In one embodiment, the message store is for Java Message Service. A lead server is selected from several servers. The lead server uses a distributed consensus algorithm to select a host server. The selected host server hosts the message store, providing sole access to the message store. The other servers are notified of the new host by messaging. In one embodiment, servers can send messages to the message store on the host and pick up any messages from the message store.

System and method for exactly once message store communication

A session replication system provides real-time data replication without unnecessarily slowing down the user experience. A system in accordance with the present invention may utilize a primary server to serve requests from a network client, as well as a secondary server to replicate the session information. When a request is received on the session, an attempt may be made to serve the request on the primary server. If the primary is unable to receive or respond to the request, the request may be served on the secondary server or on a new primary server. If the secondary server receives the request, the secondary server may become the new primary server. If a new primary server is selected, the new primary may request the session information from the secondary server.

Hardware load-balancing apparatus for session replication

A system for managing objects in a clustered network includes a file system containing at least one copy of a data object. The system can include several clustered servers in communication with the file system. A distributed consensus algorithm is used to select a host server. The selected host server can contain a copy of the data object, such as in local cache, providing access to the local copy to any other server in the cluster. Any change made to an item hosted by the host server can also be updated in the file system. If the host server becomes unable to host the object, a new host can be chosen using the distributed consensus algorithm. The other servers are then notified of the new host by multicast messaging.

Exactly once cache framework

A timer master can assign scheduled jobs to other application servers of a cluster. Leases for the timer master can be started in a lease table. The timer master can store job info for the scheduled jobs in a database. In case of a crash of the application server, another application server of the cluster can be assigned the time master and use the job information to assign scheduled jobs.

Job scheduler

A mechanism for making changes consistently across an application server domain or a cluster. Server configuration consistency is absolutely necessary for cluster deployments. The invention allows changes to the configuration repository and to the application deployment process to be managed via a Data Replication Service (DRS). The former requires that the configuration repository be version aware, while the latter breaks down the application deployment process into two phases&#x2014;one for data distribution and processing as far as possible, and the second to expose the changes through the Java Naming and Directory Interface (JNDI).

System and method for using a data replication service to manage a configuration repository

Data can be replicated over a network using a one or two phase method. For the one phase method, a master server containing an original copy of the data sends a version number for the current state of the data to each slave on the network so that each slave can request a delta from the master. The delta that is requested contains the data necessary to update the slave to the appropriate version of the data. For the two phase method, the master server sends a packet of information to each slave. The packet of information can be committed by the slaves if each slave is able to process the commit.

Data replication protocol

A system and a method for scheduling disk writes for use with an application server, transactional system, or other server. The disk scheduler and method is independent of the underlying operating system and the disk hardware. This allows it to be used without porting to the various settings in which application server might be deployed. In some embodiments, a high-performance, transactional filestore is also provided to minimize the latency of small, synchronous writes to disk. The implementation uses a log-structured file system combined with disk scheduling. By relaxing the requirement that log records be physically contiguous, every modification to the disk can be scheduled.

System and method for scheduling disk writes in an application server of transactional environment

A method for managing objects in a clustered network includes a file system containing at least one copy of a data object. The method can involve several clustered servers in communication with the file system. A distributed consensus algorithm is used to select a host server. The selected host server can contain a copy of the data object, such as in local cache, providing access to the local copy to any other server in the cluster. Any change made to an item hosted by the host server can also be updated in the file system. If the host server becomes unable to host the object, a new host can be chosen using the distributed consensus algorithm. The other servers are then notified of the new host by multicast messaging.

Exactly once data framework method

A clustered enterprise Java&#x2122; distributed processing system is provided. The distributed processing system includes a first and a second computer coupled to a communication medium. The first computer includes a Java&#x2122; virtual machine (JVM) and kernel software layer for transferring messages, including a remote Java&#x2122; virtual machine (RJVM). The second computer includes a JVM and a kernel software layer having a RJVM. Messages are passed from a RJVM to the JVM in one computer to the JVM and RJVM in the second computer. Messages may be forwarded through an intermediate server or rerouted after a network reconfiguration. Each computer includes a Smart stub having a replica handler, including a load balancing software component and a failover software component. Each computer includes a duplicated service naming tree for storing a pool of Smart stubs at a node. The computers may be programmed in a stateless, stateless factory, or a stateful programming model. The clustered enterprise Java&#x2122; distributed processing system allows for enhanced scalability and fault tolerance.

Growing community of inventors

Berkeley, CA, United States of America

Dean Bernard Jacobs