Abstract: One or more user interactions, selected from a plurality of user interactions, and one or more visualization types, selected from a plurality of visualization types are received. Predetermined visualization data associated with displaying an interactive data analysis document is determined based at least in part on the selected user interactions and the selected visualization types. The predetermined visualization data is output.

Abstract: A system, method, and computer-readable medium are disclosed for analysis and characterization of manufacturing information such as process trees or genealogies using graph theory. More specifically, using graph theory to analyze manufacturing information of a manufacturing operation allows for deep analysis of relationships between batches or units in a process tree and their closeness or distance, to identify clusters associated with specific quality characteristics or problems, to identify common antecedents of specifically labeled batches (e.g., problem batches), and/or to detect overall desirable or undesirable characteristics of the process tree (e.g., centrality, etc.).

Abstract: Techniques to provide and use modularized XML namespaces are disclosed. In various embodiments, a resolution request associated with a first module is received. A resolution context associated with the first module is used to determine that a component made available by a second module is associated with the resolution request. Access to a shared instance of the component made available by the second module is provided.

Abstract: Disclosed are systems and methods for providing message compression instructions by communicating with a plurality of sender machines and a plurality of receiver machines and monitoring one or more messages from the plurality of sender machines. The disclosed systems and methods may also identify a part of the one or more messages that is frequently included in a plurality of the messages sent by the plurality of sender machines, dynamically determine compression instructions to compress this part of the message, and provide the compression instructions to at least one of the plurality of sender machines, such that the compression instructions reduce size of the messages having the part of the message associated with the compression instructions.

Abstract: Embodiments are directed to selecting a data transmission path, comprising receiving a query having attribute(s), extracting the attribute(s) from the query, performing a search in a dynamic data structure for target(s) associated with the attribute(s), identifying a first set of target(s), and transmitting a data item to each target of the first set. The method further comprises determining whether the dynamic data structure has transformed from a first state to second state, and when a transformation is determined, performing a second search in the dynamic data structure, identifying a second set of target(s), and transmitting the data item to each target of the second set. The transmitting comprises pushing, to a first target, an option to select the data item, and pushing, to a second target, an option to select the data item when the data item is not selected by the first target.

Abstract: Methods and systems for performing a query over joined tables in the context of inexact matching provide efficient search engine functionality. The systems and methods are used to perform an efficient query on a parent table and joined child tables. Search grams are determined based on the query and parent records and child records are scanned for the search grams. Gram scores are computed based on a degree of matching between the parent and child records and the search grams.

Abstract: Techniques to provide and deploy a business process are disclosed. A business process source filed stored in a memory is received. The business process source file, as stored in memory, is provided as an input to an in-memory compiler. A business process class file stored in the memory is received as output from the in-memory compiler. The business process class file, as stored in memory, is provided to a business process engine class loader.

Abstract: Described is an enterprise-based, contextual network system and method to keep employees connected with one another, as well as to external resources. Current media offers a great way to stay in touch with others but is not cohesive and contextual for businesses or generally productive for businesses. The enterprise media disclosed in this application presents a way for businesses to keep all of their employees and outside resources connected, but in a professional and efficient manner for the workplace. This enterprise media adapts to its users to create an interface that will help the user complete work, connect with others, and use various applications all in one place.

Abstract: Techniques to process service requests are described herein. In various embodiments, an identifier data associated with a service consumer with which a service request is associated is used to determine a subset comprising fewer than all members of a set of service instances. A selected service instance is selected from among the service instances in the subset to perform the service request.

Abstract: Steady state data distribution is provided between a client application, a leader machine, and a plurality of replica machines. The distribution comprises the leader machine receiving an operation request from the client application, the leader machine sending the prepare message to each of the plurality of replica machines, the replica machines recording in their logs information on the operation, the replica machines sending acknowledgement messages to the leader machine, and the leader machine sending commit command messages to the replica machines. A new quorum of the replica machines is created by using log information. Replica machines that become part of the new quorum are updated in an efficient manner.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: A log message is processed. The log message to be processed is received. One or more portions of the log message to be separately extracted are identified. A value is extracted from each identified portion. Extracting the value includes using an extraction rule. The extraction rule is associated with the identified portion.

Abstract: Techniques to provide and use modularized XML namespaces are disclosed. In various embodiments, a resolution request associated with a first module is received. A resolution context associated with the first module is used to determine that a component made available by a second module is associated with the resolution request. Access to a shared instance of the component made available by the second module is provided.

Abstract: Predictive systems for designing enterprise applications include memory structures that output predictions to a user. The predictive system may include an HTM structure that comprises a tree-shaped hierarchy of memory nodes, wherein each memory node has a learning and memory function, and is hierarchical in space and time that allows them to efficiently model the structure of the world. The memory nodes learn causes, predicts with probability values, and form beliefs based on the input data, where the learning algorithm stores likely sequence of patterns in the nodes. By combining memory of likely sequences with current input data, the nodes may predict the next event. The predictive system may employ an HHMM structure comprising states, wherein each state is itself an HHMM. The states of the HHMM generate sequences of observation symbols for making predictions.

Abstract: A system can receive raw log data from log-producing devices. The system can parse the raw log data to generate parsed log data, including extracting fields from the raw log data, generating structured query language (SQL) statements from the extracted fields, and inserting the SQL statements in a database. The system can summarize the parsed log data, including identifying one or more SQL statements based on fields of commonality and fields of uniqueness, and creating summarized data that include a new statement condensed from the identified SQL statements. The system can then generate a report based on the summarized data.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Methods, program products, and systems implementing adaptive data transmission are disclosed. A universal data collector can act as an intermediary between a log producer and a log processor. The universal data collector can be connected to the log producer through a first, reliable network. The universal data collector can be connected to the log processor through a second, less reliable network. The universal data collector can perform a multi-phase commit of data to ensure that the log data are saved by the log processor. The universal data collector can smooth the data transmission from the universal data collector to the log processor through a network, including adaptively buffering the log data according to available network bandwidth of the network.

Abstract: To retrieve a sequence of associated events in log data, a request expression is parsed to retrieve types of dependencies between events which are searched, and the constraints (e.g., keywords) which characterize each event. Based on the parsing results, query components can be formed, expressing the constraints for individual events and interrelations (e.g., time spans) between events. A resultant span query comprising the query components can then be run against an index of events, which encodes a mutual location of associated events in storage.