Abstract: An embodiment computes a plurality of similarity scores, each similarity score in the plurality of similarity scores measuring a similarity of task data of a first data transformation task to data of a stored data transformation in a plurality of stored data transformations, wherein each of the plurality of stored data transformations comprises a stored data transformation program, each stored data transformation program comprising a data transformation from a first data format to a second data format. An embodiment generates, from a first stored data transformation program in the plurality of stored data transformations, a generated data transformation program. An embodiment performs, by modifying a plurality of records described by the first data transformation task into a second plurality of records according to the generated data transformation program, the first data transformation task.

Abstract: Methods, computer program products, and/or systems are provided that perform the following operations: obtaining source schema metadata, wherein the source schema metadata is associated with fields of a source schema; obtaining target schema metadata with a target schema, wherein the target schema metadata is associated with fields of a target schema; determining, for each field of the source schema and each field of the target schema, a representation for each field based, at least in part, on the source schema metadata or the target schema metadata associated with each field; and providing the representation for each field of the source schema and each field of the target schema for use in generating data mappings between the source schema and the target schema.

Abstract: An embodiment computes a plurality of similarity scores, each similarity score in the plurality of similarity scores measuring a similarity of task data of a first data transformation task to data of a stored data transformation in a plurality of stored data transformations, wherein each of the plurality of stored data transformations comprises a stored data transformation program, each stored data transformation program comprising a data transformation from a first data format to a second data format. An embodiment generates, from a first stored data transformation program in the plurality of stored data transformations, a generated data transformation program. An embodiment performs, by modifying a plurality of records described by the first data transformation task into a second plurality of records according to the generated data transformation program, the first data transformation task.

Abstract: A method, computer program product, and computer system for transforming sets of source data having different formats into respective sets of target data having a same format. N source patterns are determined and respectively describe N different formats in which N sets of source data items are formatted, where N?1. A target format pattern is determined and describes a target format in which a target data items are formatted. N graphs are generated and respectively describe transformations of the N source patterns to the target pattern. Each graph includes multiple transformation paths. Each transformation path transforms the source pattern to the target pattern in a manner that maps source strings in the source pattern to each target string in the target pattern. A single transformation path is selected from the multiple transformation paths resulting in N single transformation paths having been selected.

Abstract: A computer implemented method, computer system, and computer program product for transforming mapped data fields of enterprise applications. A number of processor units receiving a matching from a source data field to a target data field. The set of processor units receiving a number of annotated examples of transformations from a source format to a target format. Based on the annotated examples, the set of processor units autogenerating a query language expression for transforming data items from the source format to the target format.

Abstract: Methods, computer program products, and/or systems are provided that perform the following operations: obtaining source schema metadata, wherein the source schema metadata is associated with fields of a source schema; obtaining target schema metadata with a target schema, wherein the target schema metadata is associated with fields of a target schema; determining, for each field of the source schema and each field of the target schema, a representation for each field based, at least in part, on the source schema metadata or the target schema metadata associated with each field; and providing the representation for each field of the source schema and each field of the target schema for use in generating data mappings between the source schema and the target schema.

Abstract: A high availability environment of resource adapters implements processes to manage and to distribute work among the adapters or adapter instances. An input resource, such as a file, is received and tasks are created to distribute the content to the different instances of the adapters that are configured in the cluster. A resource adapter instance switches to manage the creation of the task based on task-definitions of the adapter. The task-definitions are rules specified in the adapter on chunks of data. The tasks are created such that chunks of data are independently locked and processed without duplication. In order to distribute the work, the tasks are persisted into a table/xml on a persistent disk. The remaining instances interact with the table to access the tasks specified by the entries in the table, thus executing the tasks.

Abstract: A computer-implemented method for error standardization in a cloud based hybrid application integration environment. The method includes receiving at least one error schema definition for an error type from a software application, and mapping the received at least one error schema definition with a corresponding error schema definition of at least one architecture style. The method includes generating an error mapping object based on the mapping of the received at least one error schema definition and the corresponding error schema definition of the at least one architecture style. The method further includes receiving an error object from the software application, and generating a resolved error object, for the received error object, based on the generated error mapping object.

Abstract: A computer-implemented method for error standardization in a cloud based hybrid application integration environment. The method includes receiving at least one error schema definition for an error type from a software application, and mapping the received at least one error schema definition with a corresponding error schema definition of at least one architecture style. The method includes generating an error mapping object based on the mapping of the received at least one error schema definition and the corresponding error schema definition of the at least one architecture style. The method further includes receiving an error object from the software application, and generating a resolved error object, for the received error object, based on the generated error mapping object.

Abstract: In an approach to contextual search of electronic records, one or more computer processors receive a first search request from a user. The one or more computer processors send a plurality of first search results associated with the first search request to the user. The one or more computer processors receive one or more selected policies from the user, based, at least in part, on the plurality of search results. Responsive to receiving the one or more selected policies, the one or more computer processors apply the one or more selected policies to the plurality of first search results. The one or more computer processors generate a second search request based, at least in part, on the one or more applied selected policies. The one or more computer processors send a plurality of second search results associated with the second search request to the user.

Abstract: A high availability environment of resource adapters implements processes to manage and to distribute work among the adapters or adapter instances. An input resource, such as a file, is received and tasks are created to distribute the content to the different instances of the adapters that are configured in the cluster. A resource adapter instance switches to manage the creation of the task based on task-definitions of the adapter. The task-definitions are rules specified in the adapter on chunks of data. The tasks are created such that chunks of data are independently locked and processed without duplication. In order to distribute the work, the tasks are persisted into a table/xml on a persistent disk. The remaining instances interact with the table to access the tasks specified by the entries in the table, thus executing the tasks.

Abstract: A mashup system and method for providing contextual insights and notifications regarding a plurality of deployed applications deployed across a plurality of devices is provided.

Abstract: A high availability environment of resource adapters implements processes to manage and to distribute work among the adapters or adapter instances. An input resource, such as a file, is received and tasks are created to distribute the content to the different instances of the adapters that are configured in the cluster. A resource adapter instance switches to manage the creation of the task based on task-definitions of the adapter. The task-definitions are rules specified in the adapter on chunks of data. The tasks are created such that chunks of data are independently locked and processed without duplication. In order to distribute the work, the tasks are persisted into a table/xml on a persistent disk. The remaining instances interact with the table to access the tasks specified by the entries in the table, thus executing the tasks.

Abstract: A data processing system assigns stored documents within a distributed storage system (DSS) to various document categories to enable a target number of documents to be deleted. An intelligent storage management (ISM) utility identifies a data storage threshold value used to control data storage within the DSS. If a current storage usage exceeds the data storage threshold value, the ISM utility calculates, based on the current storage usage, a target number of documents that can be deleted from the DSS. The ISM utility utilizes a recursive process, which includes assigning stored documents to groups including a set of document categories based on data characteristics of the stored documents. The ISM utility further utilizes the recursive process to delete, based on an established ordering of the groups, all of the stored documents assigned to a subset of the groups in order to remove the target number of stored documents.

Abstract: A method assigns stored documents within a distributed storage system (DSS) to various document categories to enable a target number of documents to be deleted. An intelligent storage management (ISM) utility identifies a data storage threshold value used to control data storage within the DSS. If a current storage usage exceeds the data storage threshold value, the ISM utility calculates, based on the current storage usage, a target number of documents that can be deleted from the DSS. The ISM utility utilizes a recursive process, which includes assigning stored documents to groups including a set of document categories based on data characteristics of the stored documents. The ISM utility further utilizes the recursive process to delete, based on an established ordering of the groups, all of the stored documents assigned to a subset of the groups in order to remove the target number of stored documents.

Abstract: Determination and indication of operational performance of deployments in an expert integrated system that has multiple deployments, with each deployment having multiple patterns. The determination is based upon pipe analytics, with the pipe analytics being performed over a common subnet that includes both the analytics platform and the management nodes of each deployment of the multiple deployments.

Abstract: Determination and indication of operational performance of deployments in an expert integrated system that has multiple deployments, with each deployment having multiple patterns. The determination is based upon pipe analytics, with the pipe analytics being performed over a common subnet that includes both the analytics platform and the management nodes of each deployment of the multiple deployments.

Abstract: A data processing system assigns stored documents within a distributed storage system (DSS) to various document categories to enable a target number of documents to be deleted. An intelligent storage management (ISM) utility identifies a data storage threshold value used to control data storage within the DSS. If a current storage usage exceeds the data storage threshold value, the ISM utility calculates, based on the current storage usage, a target number of documents that can be deleted from the DSS. The ISM utility utilizes a recursive process, which includes assigning stored documents to groups including a set of document categories based on data characteristics of the stored documents. The ISM utility further utilizes the recursive process to delete, based on an established ordering of the groups, all of the stored documents assigned to a subset of the groups in order to remove the target number of stored documents.

Abstract: A method assigns stored documents within a distributed storage system (DSS) to various document categories to enable a target number of documents to be deleted. An intelligent storage management (ISM) utility identifies a data storage threshold value used to control data storage within the DSS. If a current storage usage exceeds the data storage threshold value, the ISM utility calculates, based on the current storage usage, a target number of documents that can be deleted from the DSS. The ISM utility utilizes a recursive process, which includes assigning stored documents to groups including a set of document categories based on data characteristics of the stored documents. The ISM utility further utilizes the recursive process to delete, based on an established ordering of the groups, all of the stored documents assigned to a subset of the groups in order to remove the target number of stored documents.

Abstract: Determination and indication of operational performance of deployments in an expert integrated system that has multiple deployments, with each deployment having multiple patterns. The determination is based upon pipe analytics, with the pipe analytics being performed over a common subnet that includes both the analytics platform and the management nodes of each deployment of the multiple deployments.