Red Hat, Inc.

Manik Surtani

Jason Greene

Bela Ban

Mircea Markus

Brian Edward Stansberry

Galder Zamarreño

Vladimire Blagojevic

Adrian Cole

An example method includes: identifying, by a new node, an address of a shared data store comprising information on a current membership in a peer-to-peer system, wherein the shared data store is shared by a plurality of nodes that are current members of the peer-to-peer system, wherein the shared data store is a container for storing data in a storage cloud; sending, by the new node, a first message comprising an address of the new node to the shared data store; requesting, by the new node, at least one membership data structure from the shared data store; receiving, by the new node, a second message comprising the at least one membership data structure; generating, by the new node, a new membership data structure comprising the address of the new node and the plurality of addresses for the plurality of nodes identified in the at least one membership data structure; sending, by the new node, a third message comprising the new membership data structure to the shared data store; and joining, by the new node, the peer-to-peer system, wherein the joining comprises using the new membership data structure to identify nodes of the plurality of nodes to receive a plurality of messages from the new node.

Using a shared data store for peer discovery

After acquiring a network address, a computing device accesses a shared data store and writes the network address to the shared data store. The computing device additionally reads a plurality of network addresses from the shared data store, wherein the plurality of network addresses are for a plurality of nodes that are members of a peer-to-peer system. The computing device then joins the peer-to-peer system based on communicating with the plurality of nodes using the plurality of network addresses.

A node a data grid receives a prepare request identifying data to lock for a first transaction. The prepare request indicates a locking order that is different from a locking order indicated by a prior prepare request of a second transaction using the same data. The node identifies keys that correspond to the data. The keys are co-located on the node. The node ranks the keys to define an order for acquiring locks for the data based on key identifiers that correspond to the keys. The defined order matches a locking order used by the second transaction. The node acquires locks for the data using the defined order.

Lock reordering for optimistic locking of data on a single node to avoid transaction deadlock

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 transaction originator node identifies multiple data elements distributed at multiple enlisted nodes to lock for a transaction managed by the transaction originator node. The transaction originator node determines which of the enlisted nodes is a first enlisted node in a lock order for the transaction and sends an update request to the first enlisted node in the lock order to lock a data element residing at the first enlisted node. The transaction originator node sends update requests to remaining enlisted nodes in the lock order to cache the update requests until the remaining enlisted nodes receive a message to perform a lock.

Incremental optimistic locking of data distributed on multiple nodes to avoid transaction deadlock

An apparatus and a method for accessing data at a server node of a data grid system with distributed cache is described. The server receives a request to access a logical tree structure of cache nodes at a tree structure interface module of the server. The tree structure interface operates on a flat map structure of the cache nodes corresponding to the logical tree structure, transparent to the request. Each cache node is defined and operated on using a two-dimensional coordinate including a fully qualified name and a type.

Representing a tree structure on a flat structure

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

An apparatus and a method for providing amortized lock access in a data container is described. Each access from each thread of a process in a memory to each object of a data container in the memory is recorded in a queue of the data container. A queue manager determines whether the recorded number of accesses in the queue has reached a predetermined threshold. The queue manager executes a lock algorithm and an eviction algorithm on all objects in the data container when the recorded number of accesses in the queue has reached the predetermined threshold. The lock algorithm is configured to lock objects in the data container while the eviction algorithm is performed on the data container. The eviction algorithm is configured to evict one or more objects from the data container pursuant to the eviction algorithm.

Lock amortization in a data counter

A client computing system identifies a start of a multi-operational transaction pertaining to access of data stored in caches being managed by nodes residing in Java Virtual Machines in an in-memory data grid. The client computing system stores transaction context data indicating the start of the multi-operational transaction and identifies an application request to perform an operation pertaining to the multi-operational transaction. The application request is from an application that resides outside of the Java Virtual Machines of the nodes. The client computing system determines the transaction context of the operation based on the transaction context data and sends an operation request over a network to a managing node in the in-memory data grid to manage the multi-operational transaction. The operation request includes header data based on the transaction context data.

Multi-operational transactional access of in-memory data grids in a client-server environment

A method and apparatus for using a tree-structured cluster as a library for a computing grid. In one embodiment, a request for computation is received at a cache node of the cluster. The computation requires data from an other cache node of the cluster, and not present in the cache node receiving the request. The other cache nodes of the cluster are polled for the required data. An instance of the required data stored in the other cache node of the cluster is replicated to the cache node receiving the computation request.

Grid computing space

A method and apparatus for replicating instances of cache nodes in a cluster is described. In one embodiment, the number of available cache nodes in the cluster is determined. Available cache nodes from the cluster are selected based on a parameter. An instance of a cache node is replicated to only one of the selected cache nodes in the cluster.

Replicating cache nodes in a cluster

An apparatus and a method for forming a concurrent linked hash map is described. Doubly linked nodes of a linked list are formed in a data container of a networked memory. A hash table is generated from the doubly linked nodes. A parent node is located in the hash table to update a reference of a node in the data container. The parent node is processed in a forward direction of the linked list.

Concurrent linked hashed maps

An apparatus and a method operating on data at a server node of a data grid system with distributed cache. Data is copied to a network cloud of storage services remotely coupled to a server node with an asynchronous input output interface. The asynchronous input output interface is configured to asynchronously communicate with the network cloud of storage services. Confirmation that the data has been copied on the network cloud of storage services is received at the server node.

Non-blocking input output based storage

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.

Portable hash-based key location mechanism

An apparatus and a method for operating on data at a cache node of a data grid system is described. An asynchronous future-based interface of a computer system receives a request to operate on a cache node of a cluster. An acknowledgment is sent back upon receipt of the request prior to operating on the cache node. The cache node is then operated on based on the request. The operation is replicated to other cache nodes in the cluster. An acknowledgment that the operation has been completed in the cluster is sent back.

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London, United Kingdom

Manik Surtani