Abstract: An example method of parsing data in a distributed computing system includes assigning a worker k to scan a data chunk k at a data storage node at which data chunk k is stored, each of one or more data chunks including a partial record, receiving, from each worker k, a number of instances of a context-varying symbol, a position in the data chunk k of a first instance of a context-dependent symbol after an even number of instances of the context-varying symbol, and a position in the data chunk k of a first instance of the context-dependent symbol after an odd number of instances of the context-varying symbol, for each data chunk that includes a partial record, computing an adjusted data chunk including data from a later data chunk to complete the partial record, parsing the adjusted data chunks and executing a query against the plurality of records.

Abstract: Embodiments of the present disclosure are directed a distributed storage system that supports query data. One embodiment provides, at a front-end node, a method comprising receiving a query regarding data stored in an object, obtaining information identifying data nodes at which blocks of the object are stored, sending, to a first data node, a query regarding data in a first block, and receiving results for the query regarding the data in the first block comprising an incomplete record. The method further comprises sending, to a second data node, a query regarding data in a second block comprising the incomplete record, the second block being stored on a different physical device than the first block, and receiving results for the query regarding the data in the second block. The method further comprises outputting the results for the queries regarding the data in the first block and the data in the second block.

Abstract: An example method of parsing data in a distributed computing system includes assigning a worker k to scan a data chunk k at a data storage node at which data chunk k is stored, each of one or more data chunks including a partial record, receiving, from each worker k, a number of instances of a context-varying symbol, a position in the data chunk k of a first instance of a context-dependent symbol after an even number of instances of the context-varying symbol, and a position in the data chunk k of a first instance of the context-dependent symbol after an odd number of instances of the context-varying symbol, for each data chunk that includes a partial record, computing an adjusted data chunk including data from a later data chunk to complete the partial record, parsing the adjusted data chunks and executing a query against the plurality of records.

Abstract: An example method of parsing data in a distributed computing system includes assigning a worker k to scan a data chunk k at a data storage node at which data chunk k is stored, each of one or more data chunks including a partial record, receiving, from each worker k, a number of instances of a context-varying symbol, a position in the data chunk k of a first instance of a context-dependent symbol after an even number of instances of the context-varying symbol, and a position in the data chunk k of a first instance of the context-dependent symbol after an odd number of instances of the context-varying symbol, for each data chunk that includes a partial record, computing an adjusted data chunk including data from a later data chunk to complete the partial record, parsing the adjusted data chunks and executing a query against the plurality of records.

Abstract: Examples are disclosed that relate to querying data in a distributed storage system. One example provides, at a front-end node, a method comprising receiving a query regarding data stored in an object, obtaining information identifying data nodes at which blocks of the object are stored, sending, to a first data node, a query regarding data in a first block, and receiving results for the query regarding the data in the first block comprising an incomplete record. The method further comprises sending, to a second data node, a query regarding data in a second block comprising the incomplete record, the second block being stored on a different physical device than the first block, and receiving results for the query regarding the data in the second block. The method further comprises outputting the results for the queries regarding the data in the first block and the data in the second block.

Abstract: One example provides, at a front-end node of a distributed storage system, a method comprising receiving a query regarding data stored in an object, obtaining information identifying data nodes at which blocks of the object are stored, sending, to a first data node, a query regarding data in a first block, and receiving results for the query regarding the data in the first block comprising an incomplete record. The method further comprises sending, to a second data node, a query regarding data in a second block comprising the incomplete record, the second block being stored on a different physical device than the first block, and receiving results for the query regarding the data in the second block. The method further comprises outputting the results for the queries regarding the data in the first block and the data in the second block.

Abstract: An example method of parsing data in a distributed computing system includes assigning a worker k to scan a data chunk k at a data storage node at which data chunk k is stored, each of one or more data chunks including a partial record, receiving, from each worker k, a number of instances of a context-varying symbol, a position in the data chunk k of a first instance of a context-dependent symbol after an even number of instances of the context-varying symbol, and a position in the data chunk k of a first instance of the context-dependent symbol after an odd number of instances of the context-varying symbol, for each data chunk that includes a partial record, computing an adjusted data chunk including data from a later data chunk to complete the partial record, parsing the adjusted data chunks and executing a query against the plurality of records.

Abstract: Examples are disclosed that relate to querying data in a distributed storage system. One example provides, at a front-end node, a method comprising receiving a query regarding data stored in an object, obtaining information identifying data nodes at which blocks of the object are stored, sending, to a first data node, a query regarding data in a first block, and receiving results for the query regarding the data in the first block comprising an incomplete record. The method further comprises sending, to a second data node, a query regarding data in a second block comprising the incomplete record, the second block being stored on a different physical device than the first block, and receiving results for the query regarding the data in the second block. The method further comprises outputting the results for the queries regarding the data in the first block and the data in the second block.

Abstract: Target data is allocated into caches of a shared-memory multiprocessor system during a runtime environment. The target data includes a plurality of data items that are allocated onto separate cache lines. Each data item is allocated on a separate cache line regardless of the size of the cache line of the system. The data items become members of a wrapper types when data items are value types. The runtime environment maintains a set of wrapper types of various sizes that are of typical cache line sizes. Garbage data is inserted into the cache line in cases where data items are reference types and data is stored on a managed heap. The allocation also configures garbage collectors in the runtime environment not to slide multiple data items onto the same cache line. Other examples are included where a developer can augment the runtime environment to be aware of cache line sizes.

Abstract: Target data is allocated into caches of a shared-memory multiprocessor system during a runtime environment. The target data includes a plurality of data items that are allocated onto separate cache lines. Each data item is allocated on a separate cache line regardless of the size of the cache line of the system. The data items become members of a wrapper types when data items are value types. The runtime environment maintains a set of wrapper types of various sizes that are of typical cache line sizes. Garbage data is inserted into the cache line in cases where data items are reference types and data is stored on a managed heap. The allocation also configures garbage collectors in the runtime environment not to slide multiple data items onto the same cache line. Other examples are included where a developer can augment the runtime environment to be aware of cache line sizes.

Abstract: Methods and computer program products are disclosed for providing QoS for Web applications via an internet service application programming interface “ISAPI”) filter running on an internet information server, wherein the ISAPI filter uses a traffic control application programming interface to manage bandwidth for individual HTTP requests. Responses to HTTP requests can be prioritized based on policies defined by the Web application developer, wherein policy decisions may be made based on many different parameters, such as, for example, the IP address of the Web browser making the request, the type of browser being used, HTTP “cookies,” the uniform resource locator being requested, an authenticated user ID, or any other information that is exposed from the Internet information server through server variables. The present invention accomplishes this with no modifications to the internet information server, and with very minimal changes to the Web application.

Abstract: In an implementation of an XML-based preprocessor, a programmed source file is parsed to generate a syntactic representation of the programmed source file. An XML (Extensible Markup Language) document is generated from the syntactic representation of the programmed source file, and a transform is applied to the XML document to generate a modified XML document from which an output file is generated in a format of the programmed source file.