Abstract: Systems and methods can support flow control in a distributed data grid. The distributed data grid includes a plurality of server nodes that are interconnected with one or more communication channels. The distributed data grid can provide a flow control mechanism, which controls the execution of the tasks in an underlying layer in the distributed data grid. Then, the system allows the client to interact with the flow control mechanism in the distributed data grid, and use the flow control mechanism to configure and execute one or more tasks that are received from the client.

Abstract: A system and method is described for use with a data grid cluster, which uses cluster quorum to prevent split brain scenario. The data grid cluster includes a plurality of cluster nodes, each of which runs a cluster service. Each cluster service collects and maintains statistics regarding communication flow between its cluster node and the other cluster nodes in the data grid cluster. The statistics are used to determine a status associated with other cluster nodes in the data grid cluster whenever a disconnect event happens. The data grid cluster is associated with a quorum policy, which is defined in a cache configuration file, and which specifies a time period that a cluster node will wait before making a decision on whether or not to evict one or more cluster nodes from the data grid cluster.

Abstract: A system and method is described for use with a data grid cluster to support death detection. A network ring is formed by connecting a plurality of process nodes in the data grid, wherein each node in the network ring watches another node. A death of a first process node in the network ring can be detected by a second process node, when the second process node notices that its connection to the first process node has closed. The first process node then informs other process cluster nodes in the network ring that the first node is dead. In accordance with an embodiment, machine level death detection can also be supported in the data grid cluster by using an Internet Protocol (IP) monitor.

Abstract: A system and method can support memory allocation control in a distributed data grid. The system can designate a process, such as a logical process, to handle a request that is received from a client for storing data in a data storage using an elastic data structure with one or more journal files. Then, a resource manager associated with the data storage can suspend the process when the elastic data structure appears to be logically full. Furthermore, the resource manager can resume the suspended process associated with the client, after the resource manager has reclaimed sufficient memory from the elastic data structure.

Abstract: A system and method can support persistence in a distributed data grid, such as persistent store versioning and integrity. A resolver in the distributed data grid can receive a plurality of identifiers from one or more members of the distributed data grid, wherein each said identifier is associated with a persisted partition in a persistent storage for the distributed data grid. Then, the resolver can select an identifier for each partition, wherein each selected identifier is associated with a most recent valid version of a partition. Furthermore, the resolver can determine a member in the distributed data grid that is responsible for recovering said partition from a persisted partition associated with the selected identifier.

Abstract: A system and method can support metadata compression in a distributed data grid. The system can store a plurality of keys in compact data structure (such as a radix tree) in a heap, wherein each said key is associated with an entry in a journal off-heap. Furthermore, the system can look up the tree for a key, wherein the key is associated with a journal ticket that represents a virtual address of an entry in the journal. Then, the system can use the journal ticket to manage the entry in the journal that is associated with said key.

Abstract: A system and method can support data interoperability in a distributed data grid. The system can provide an acceptor in the distributed data grid, wherein the acceptor is associated with a cache that is based on the distributed data grid. Furthermore, the acceptor can receive incoming data from a first client, which can be a non-native client that is associated with a client application. Additionally, the system allows a second client, which can be a native client associated with the distributed cache, to share the received incoming data with the first client.

Abstract: A system and method can support persistence in a distributed data grid. A plurality of members in the distributed data grid can persist a plurality of partitions associated with one or more cache services in persistent storage. Furthermore, a coordinator, which may be a member in the distributed data grid, can synchronize a view of partition ownership among the plurality of members in the distributed data grid, and form a distributed consensus on which partition can be recovered from which member in the distributed data grid.

Abstract: A system and method can support persistence in a distributed data grid, such as providing a persistent snapshot of a running system. The system allows one or more cache services to run on a plurality of cluster members in the distributed data grid. Furthermore, the system can collect a catalogue of state information associated with said one or more cache services from the plurality of cluster members in the distributed data grid, and create a snapshot for said one or more cache services running on the distributed data grid.

Abstract: A system and method is described for use with a data grid cluster, which uses cluster quorum to prevent split brain scenario. The data grid cluster includes a plurality of cluster nodes, each of which runs a cluster service. Each cluster service collects and maintains statistics regarding communication flow between its cluster node and the other cluster nodes in the data grid cluster. The statistics are used to determine a status associated with other cluster nodes in the data grid cluster whenever a disconnect event happens. The data grid cluster is associated with a quorum policy, which is defined in a cache configuration file, and which specifies a time period that a cluster node will wait before making a decision on whether or not to evict one or more cluster nodes from the data grid cluster.

Abstract: A system and method can support transient partition consistency in a distributed data grid. A cluster node in the distributed data grid can maintain a storage data structure and an index data structure. The storage data structure can store data in one or more partitions maintained on the cluster node, and the index data structure contains a plurality of indexes, wherein each index supports indexing at least one data grid operation on the one or more partitions. Furthermore, the distributed data grid ensures consistency between the storage data structure and the index data structure for the data stored in the one or more partitions maintained on the cluster node.

Abstract: A system and method can provide partition persistent state consistency in a distributed data grid. The distributed data grid can provide a plurality of copies of a partition on a plurality of cluster nodes in the distributed data grid, wherein the plurality of cluster nodes includes a primary owner node and one or more backup nodes for the partition. The primary owner node can propagate one or more modifications of the partition from the primary owner node to the one or more backup nodes. The distributed data grid can ensure consistency among the plurality copies of the partition on the plurality of cluster nodes in the distributed data grid.

Abstract: A query explain plan is described for use with a distributed data system in order to help developers and IT experts to detect bottlenecks and to determine which queries are to blame for a slow running system. In accordance with an embodiment, the distributed data grid utilizes a facility to provide a distributed explain plan. This distributed explain plan provides visibility into how a query was answered by each node in the cluster. For example, one node may have applied the filters of the query in one sequence, while another node may have used a different sequence. Additionally, the distributed query explain plan can provide execution tracing, rendering information about the execution time of each step, total execution time and the like.

Abstract: A system and method can support guaranteed multi-point message delivery in a distributed data grid. A messaging facility in the distributed data grid can receive an incoming message that is adaptive to be delivered to a plurality of nodes in the distributed data grid. The messaging facility can deliver the incoming message to the plurality of nodes according to an order in a list. Furthermore, a node in the plurality of nodes operates to skip a next node in the list to deliver the incoming message, when the next node is dead or unavailable.

Abstract: A system and method can support transient partition consistency in a distributed data grid. A cluster node in the distributed data grid can maintain a storage data structure and an index data structure. The storage data structure can store data in one or more partitions maintained on the cluster node, and the index data structure contains a plurality of indexes, wherein each index supports indexing at least one data grid operation on the one or more partitions.

Abstract: A system and method can provide partition persistent state consistency in a distributed data grid. The distributed data grid can provide a plurality of copies of a partition on a plurality of cluster nodes in the distributed data grid, wherein the plurality of cluster nodes includes a primary owner node and one or more backup nodes for the partition. The primary owner node can propagate one or more modifications of the partition from the primary owner node to the one or more backup nodes. The distributed data grid can ensure consistency among the plurality copies of the partition on the plurality of cluster nodes in the distributed data grid.

Abstract: A computer is programmed to automatically have multiple sessions update a common counter which is shared therebetween, when interpreting a given method so that system-wide statistics are collected for each method. The single counter is commonly accessed for updating by the respective interpreters in the multiple sessions which are executing the method. The computer is further programmed to asynchronously compile the method (regardless of the state of the multiple sessions), to obtain compiled software in the form of executable machine instructions. Specifically, asynchronous compilation starts dynamically, whenever a method's common multi-session counter satisfies a predetermined condition. Finally, each session is informed when compilation is completed so that the next time the method needs to be run, it is not interpreted and instead the compiled software is executed. The compiled software is kept in a shared memory which is accessible to each session.

Abstract: A query explain plan is described for use with a distributed data system in order to help developers and IT experts to detect bottlenecks and to determine which queries are to blame for a slow running system. In accordance with an embodiment, the distributed data grid utilizes a facility to provide a distributed explain plan. This distributed explain plan provides visibility into how a query was answered by each node in the cluster. For example, one node may have applied the filters of the query in one sequence, while another node may have used a different sequence. Additionally, the distributed query explain plan can provide execution tracing, rendering information about the execution time of each step, total execution time and the like.

Abstract: A system and method can provide a server-side event model in a distributed data grid with a plurality of cluster nodes storing data partitions distributed throughout the cluster, each cluster node being responsible for a set of partitions. The system can map one or more event interceptors to an event dispatcher placed in the cluster. The one or more event interceptors can handle at least one event dispatched from the event dispatcher, wherein the at least one event is associated with an operation in the distributed data grid. The system can defer completion of the operation in the distributed data grid pending completion of the handling of the at least one event by said one or more event interceptors.

Abstract: A system and method can handle storage events in a distributed data grid. The distributed data grid cluster includes a plurality of cluster nodes storing data partitions distributed throughout the cluster, each cluster node being responsible for a set of partitions. A service thread, executing on at least one of said cluster nodes in the distributed data grid, is responsible for handling one or more storage events. The service thread can use a worker thread to accomplish synchronous event handling without blocking the service thread.