Abstract: Systems, methods, and software described herein facilitate the allocation of large scale processing jobs to host computing systems. In one example, a method of allocating job processes to a plurality of host computing systems in a large scale processing environment includes identifying a job process for the large scale processing environment, and obtaining accommodation data for a plurality of host computing systems in the large scale processing environment. The method further provides identifying a host computing system in the plurality of host computing systems for the job process based on the accommodation data, and initiating a virtual node on the host computing system for the job process.

Abstract: Disclosed herein provides enhancements for generating large scale processing framework (LSPF) images for deployment in processing environments. In one implementation a method of preparing LSPF service images for large scale data processing environments includes identifying a first LSPF service image, and identifying metadata that defines runtime requirements for deploying the LSPF service in data processing environments. The method further provides generating scripts for deploying the LSPF service based on the metadata, and generating a second LSPF service image for the LSPF service, wherein the second LSPF service image includes the scripts.

Abstract: Systems, methods, and software described herein facilitate the management of virtual clusters in a large-scale processing environment. In one implementation, a method of operating a control node includes receiving a request to configure a virtual cluster with one or more data processing nodes, and identifying a tenant associated with the request. The method further provides identifying a namespace for the tenant, and identifying internet protocol (IP) addresses for the one or more data processing nodes. The method also includes generating namespace to IP address pairs for the one or more data processing nodes based on the namespace and the IP addresses, and configuring a domain name system (DNS) for the virtual cluster with the namespace to IP address pairs.

Abstract: Systems, methods, and software described herein provide accelerated input and output of data in a work process. In one example, a method of operating a support process within a computing system for providing accelerated input and output for a work process includes monitoring for a file mapping attempt initiated by the work process. The method further includes, in response to the file mapping attempt, identifying a first region in memory already allocated to a cache service, and associating the first region in memory with the work process.

Abstract: Systems, methods, and software described herein facilitate accelerated input and output operations with respect to virtualized environments. In an implementation, upon being notified of a guest read process initiated by a guest element running in a virtual machine to read data into a location in guest memory associated with the guest element, a computing system identifies a location in host memory associated with the location in the guest memory and initiates a host read process to read the data into the location in the host memory that corresponds to the location in the guest memory.

Abstract: Systems, methods, and software described herein provide for enhancements to large scale data processing architectures. In one implementation, a service architecture for large scale data processing includes a host computing system, and a virtual machine executing on the host computing system. The service architecture further includes a plurality of application containers executing on the virtual machine, wherein each of the application containers comprises a large scale processing node running one or more java virtual machines.

Abstract: Described herein are systems, methods, and software for translating data requests in a data processing cluster. In one example, a method of operating a cache service to interface between a virtual machine cluster and job data associated with a job executed by the virtual machine cluster includes identifying a request initiated by the virtual machine cluster to access at least a portion of the job data in accordance with a first distributed object access protocol. The method further includes in response to the request, accessing at least the portion of the job data in accordance with a second distributed object access protocol, and presenting at least the portion of the job data to the virtual machine cluster in accordance with the first distributed object access protocol.

Abstract: Described herein are systems, methods, and software for translating data requests in a data processing cluster. In one example, a method of operating a cache service to interface between a virtual machine cluster and job data associated with a job executed by the virtual machine cluster includes identifying a request initiated by the virtual machine cluster to access at least a portion of the job data in accordance with a first distributed object access protocol. The method further includes in response to the request, accessing at least the portion of the job data in accordance with a second distributed object access protocol, and presenting at least the portion of the job data to the virtual machine cluster in accordance with the first distributed object access protocol.

Abstract: Systems, methods, and software described herein provide for enhancements to large scale data processing architectures. In one implementation, a service architecture for large scale data processing includes a host computing system, and a virtual machine executing on the host computing system. The service architecture further includes a plurality of application containers executing on the virtual machine, wherein each of the application containers comprises a large scale processing node running one or more java virtual machines.

Abstract: Systems, methods, and software described herein provide accelerated input and output of data in a work process. In one example, a method of operating a support process within a computing system for providing accelerated input and output for a work process includes monitoring for a file mapping attempt initiated by the work process. The method further includes, in response to the file mapping attempt, identifying a first region in memory already allocated to a cache service, and associating the first region in memory with the work process.

Abstract: Systems, methods, and software described herein to provide data to large-scale processing framework (LSPF) nodes in LSPF clusters. In one example, a method to provide data includes receiving an access request from a LSPF node to access data in accordance with a version of a distributed file system. The method further includes, responsive to the access request, accessing the data for the LSPF node in accordance with a different version of the distributed file system, and presenting the data to the LSPF node in accordance with the version of the distributed file system used by the LSPF node.

Abstract: Systems, methods, and software described herein provide accelerated input and output of data in a work process. In one example, a method of operating a support process within a computing system for providing accelerated input and output for a work process includes monitoring for a file mapping attempt initiated by the work process. The method further includes, in response to the file mapping attempt, identifying a first region in memory already allocated to a cache service, and associating the first region in memory with the work process.