Abstract: A method for RDMA optimized high availability for in-memory storing of data includes receiving RDMA key-value store write requests in a network adapter of a primary computing server directed to writing data to an in-memory key-value store of the primary computing server and performing RDMA write operations of the data by the network adapter of the primary computing server responsive to the RDMA key-value store write requests. The method also includes replicating the RDMA key-value store write requests to a network adapter of a secondary computing server, by the network adapter of the primary computing server. Finally, the method includes providing address translation data for the in-memory key-value store of the primary computing server from the network adapter of the primary computing server to the network adapter of the secondary computing server.

Abstract: An infrastructure for servicing remote direct memory access (RDMA) requests without the need to pin memory and/or register memory for access by only a single RDMA adapter. Rather, RDMA requests can be coherently serviced from memory accessible to multiple adapters, and that memory can be flexibly managed (such as by swapping it out of main memory or moving it around within main memory). This coherent servicing of RDMA requests is achieved through the use of a coherent attached bus connecting the RDMA adapters to main memory that owns the address space.

Abstract: As disclosed herein, a method for conducting mapping and reducing operations includes receiving a plurality of data records and aggregating data records having a common value for a selected field within the data records to provide aggregated data records for each common value, storing the aggregated data records on a shared storage subsystem, and accessing the aggregated data records on the shared storage subsystem. The method further comprises accumulating information for the aggregated data records to provide accumulated information, and using the accumulated information.

Abstract: As disclosed herein, a system for conducting mapping and reducing operations includes a shared storage subsystem that is connected to one or more mapping servers and one or more reducing servers via a high-speed data link and communication protocol. Each mapping server receives a multitude of data records, aggregates the data records having a particular value, and sorts and stores the resulting aggregated data records on the shared storage subsystem. Each reducing server accesses the shared storage subsystem and accumulates information on the aggregated data records for a particular common value. In many instances, the access rates to the shared storage subsystem achieved by the mapping servers and the reducing servers approach that of accessing a local attached storage device. A computer program product and method corresponding to the system for conducting mapping and reducing operations are also disclosed herein.

Abstract: Embodiments of the present invention provide methods, systems, and computer program products for transferring data in a MapReduce framework. In one embodiment, MapReduce jobs are performed such that data spills are stored by mapper systems in memory and are transferred to reducer systems via one-sided RDMA transfers, which can reduce CPU overhead of mapper systems and the latency of data transfer to reducer systems.

Abstract: An infrastructure for servicing remote direct memory access (RDMA) requests without the need to pin memory and/or register memory for access by only a single RDMA adapter. Rather, RDMA requests can be coherently serviced from memory accessible to multiple adapters, and that memory can be flexibly managed (such as by swapping it out of main memory or moving it around within main memory). This coherent servicing of RDMA requests is achieved through the use of a coherent attached bus connecting the RDMA adapters to main memory that owns the address space.

Abstract: A method for RDMA optimized high availability for in-memory storing of data includes receiving RDMA key-value store write requests in a network adapter of a primary computing server directed to writing data to an in-memory key-value store of the primary computing server and performing RDMA write operations of the data by the network adapter of the primary computing server responsive to the RDMA key-value store write requests. The method also includes replicating the RDMA key-value store write requests to a network adapter of a secondary computing server, by the network adapter of the primary computing server. Finally, the method includes providing address translation data for the in-memory key-value store of the primary computing server from the network adapter of the primary computing server to the network adapter of the secondary computing server.

Abstract: An instruction from a controller is received at an application executing using a processor, the controller being a Software Defined Network (SDN) controller operating in an SDN. A determination is made, using the processor, that the instruction applies to an identifier located in a data packet, the data packet passing through a shared port, the shared port being shared by the controller and a concurrently operating second controller in the SDN. A period of effectiveness of the instruction is initialized. A command is sent to a switch to apply a network setting configured by the controller to handle the data packet, where the shared port is located at the switch in the SDN.

Abstract: A method for RDMA optimized high availability for in-memory storing of data includes receiving RDMA key-value store write requests in a network adapter of a primary computing server directed to writing data to an in-memory key-value store of the primary computing server and performing RDMA write operations of the data by the network adapter of the primary computing server responsive to the RDMA key-value store write requests. The method also includes replicating the RDMA key-value store write requests to a network adapter of a secondary computing server, by the network adapter of the primary computing server. Finally, the method includes providing address translation data for the in-memory key-value store of the primary computing server from the network adapter of the primary computing server to the network adapter of the secondary computing server.

Abstract: A method for RDMA optimized high availability for in-memory storing of data includes receiving RDMA key-value store write requests in a network adapter of a primary computing server directed to writing data to an in-memory key-value store of the primary computing server and performing RDMA write operations of the data by the network adapter of the primary computing server responsive to the RDMA key-value store write requests. The method also includes replicating the RDMA key-value store write requests to a network adapter of a secondary computing server, by the network adapter of the primary computing server. Finally, the method includes providing address translation data for the in-memory key-value store of the primary computing server from the network adapter of the primary computing server to the network adapter of the secondary computing server.

Abstract: An instruction from a controller is received at an application executing using a processor, the controller being a Software Defined Network (SDN) controller operating in an SDN. A determination is made, using the processor, that the instruction applies to an identifier located in a data packet, the data packet passing through a shared port, the shared port being shared by the controller and a concurrently operating second controller in the SDN. A period of effectiveness of the instruction is initialized. A command is sent to a switch to apply a network setting configured by the controller to handle the data packet, where the shared port is located at the switch in the SDN.

Abstract: A method and system of selecting and migrating relevant data from among data associated with a workload of a virtual machine and stored in source storage cache memory in a dynamic computing environment is described. The method includes selecting one or more policies, the one or more policies including a size policy defining a default maximum size for the relevant data. The method also includes selecting the relevant data from among the data based on the one or more policies in a default mode, and migrating the relevant data from the source storage cache memory to target storage cache memory.

Abstract: A method and system of selecting and migrating relevant data from among data associated with a workload of a virtual machine and stored in source storage cache memory in a dynamic computing environment is described. The method includes selecting one or more policies, the one or more policies including a size policy defining a default maximum size for the relevant data. The method also includes selecting the relevant data from among the data based on the one or more policies in a default mode, and migrating the relevant data from the source storage cache memory to target storage cache memory.

Abstract: According to one exemplary embodiment, a method for remote direct memory access failover is provided. The method may include determining an RDMA operation will be performed. The method may include determining an available node. The method may include sending a data element to the available node based on the RDMA operation being an insert. The method may include receiving a pointer in response to sending the insert, whereby the pointer corresponds to a memory range. The method may include storing the pointer. The method may include retrieving the pointer based on the RDMA operation being an update, a read, or a delete. The method may include sending the pointer, the data element to the available node based on the RDMA operation being an update. The method may include sending the pointer and the RDMA operation to the available node based on the RDMA operation being a read or a delete.

Abstract: Embodiments of the present invention provide methods, systems, and computer program products for transferring data in a MapReduce framework. In one embodiment, MapReduce jobs are performed such that data spills are stored by mapper systems in memory and are transferred to reducer systems via one-sided RDMA transfers, which can reduce CPU overhead of mapper systems and the latency of data transfer to reducer systems.

Abstract: A method for RDMA optimized high availability for in-memory storing of data includes receiving RDMA key-value store write requests in a network adapter of a primary computing server directed to writing data to an in-memory key-value store of the primary computing server and performing RDMA write operations of the data by the network adapter of the primary computing server responsive to the RDMA key-value store write requests. The method also includes replicating the RDMA key-value store write requests to a network adapter of a secondary computing server, by the network adapter of the primary computing server. Finally, the method includes providing address translation data for the in-memory key-value store of the primary computing server from the network adapter of the primary computing server to the network adapter of the secondary computing server.

Abstract: A method for RDMA optimized high availability for in-memory storing of data includes receiving RDMA key-value store write requests in a network adapter of a primary computing server directed to writing data to an in-memory key-value store of the primary computing server and performing RDMA write operations of the data by the network adapter of the primary computing server responsive to the RDMA key-value store write requests. The method also includes replicating the RDMA key-value store write requests to a network adapter of a secondary computing server, by the network adapter of the primary computing server. Finally, the method includes providing address translation data for the in-memory key-value store of the primary computing server from the network adapter of the primary computing server to the network adapter of the secondary computing server.

Abstract: As disclosed herein, a system for conducting mapping and reducing operations includes a shared storage subsystem that is connected to one or more mapping servers and one or more reducing servers via a high-speed data link and communication protocol. Each mapping server receives a multitude of data records, aggregates the data records having a particular value, and sorts and stores the resulting aggregated data records on the shared storage subsystem. Each reducing server accesses the shared storage subsystem and accumulates information on the aggregated data records for a particular common value. In many instances, the access rates to the shared storage subsystem achieved by the mapping servers and the reducing servers approach that of accessing a local attached storage device. A computer program product and method corresponding to the system for conducting mapping and reducing operations are also disclosed herein.

Abstract: As disclosed herein, a method for conducting mapping and reducing operations includes receiving a plurality of data records and aggregating data records having a common value for a selected field within the data records to provide aggregated data records for each common value, storing the aggregated data records on a shared storage subsystem, and accessing the aggregated data records on the shared storage subsystem. The method further comprises accumulating information for the aggregated data records to provide accumulated information, and using the accumulated information.

Abstract: A method and system of selecting and migrating relevant data from among data associated with a workload of a virtual machine and stored in source storage cache memory in a dynamic computing environment is described. The method includes selecting one or more policies, the one or more policies including a size policy defining a default maximum size for the relevant data. The method also includes selecting the relevant data from among the data based on the one or more policies in a default mode, and migrating the relevant data from the source storage cache memory to target storage cache memory.