Abstract: Methods and arrangements for processing hierarchical data in a map-reduce framework. Hierarchical data is accepted, and a map-reduce job is performed on the hierarchical data. This performing of a map-reduce job includes determining a cost of partitioning the data, determining a cost of redefining the job and thereupon selectively performing at least one step taken from the group consisting of: partitioning the data and redefining the job.

Abstract: Database operation records are sequentially read from two or more log files. If the transaction identifier is new and the record is not an end-of-transaction record, an open transactions list entry is created. If the transaction identifier is new and the record is an end-of-transaction record, a transaction type list entry is created or updated. If the transaction identifier is not new and is not an end-of-transaction record, an open transactions list entry is updated. If the transaction identifier is not new and the record is an end-of-transaction record, a transaction type list entry is created or updated. When all log file records are read, analytical comparison between the information associated with two or more of the log files in data fields in the transaction type list entries is performed.

Abstract: Database operation records are sequentially read from two or more log files. If the transaction identifier is new and the record is not an end-of-transaction record, an open transactions list entry is created. If the transaction identifier is new and the record is an end-of-transaction record, a transaction type list entry is created or updated. If the transaction identifier is not new and is not an end-of-transaction record, an open transactions list entry is updated. If the transaction identifier is not new and the record is an end-of-transaction record, a transaction type list entry is created or updated. When all log file records are read, analytical comparison between the information associated with two or more of the log files in data fields in the transaction type list entries is performed.

Abstract: Identifying matching transactions. First and second log files contain operation records of transactions in a transaction workload, each file recording a respective execution of the transaction workload, the method comprising. A first record location in the first file and an associated window of a defined number of sequential second record locations in the second file are advanced one record location at a time. Whether each operation record of a complete transaction at a first record location has a matching operation record at one of the record locations in the associated window of second record locations is determined. If so, the complete transaction in the first file and the transaction that includes the matching operation records in the second file are identified as matching transactions.

Abstract: A predefined number of matches is identified between records in a first file and records in a second file. For the matches, determine the span of the actual range of record positions in the second file relative to the positions of the operation records in the first file within which all matches were found. If the actual span is smaller than the span of a current defined range of record positions by at least a first threshold value, decrease the span of the current defined range. If the actual span is within a second threshold value of the span of the current defined range, increase the span of the current defined range. If an amount above a third threshold value of operation records in the first file are not matched to operation records in the second file, increasing the span of the current defined range.

Abstract: A method for identifying matching transactions between two log files where each transaction includes one or more statements. Each log file record records the execution of a statement and includes a transaction identifier. Each record in turn in one log file is compared to an advancing window of records in the other log file. A first table contains associations of statements to transactions and transactions to statements for records in the window. If a match is found between a record in the one file and a record in the window, information associating partial transactions in the one file to potential transactions of the records in the window is added to a second table. If an end-of-transaction record is read from the one file, a best match is found between the ended transaction and the potential transactions based on information in the first and second tables.

Abstract: A method for identifying matching transactions between two log files where each transaction includes one or more statements. Each log file record records the execution of a statement and includes a transaction identifier. Each record in turn in one log file is compared to an advancing window of records in the other log file. A first table contains associations of statements to transactions and transactions to statements for records in the window. If a match is found between a record in the one file and a record in the window, information associating partial transactions in the one file to potential transactions of the records in the window is added to a second table. If an end-of-transaction record is read from the one file, a best match is found between the ended transaction and the potential transactions based on information in the first and second tables.

Abstract: A log file contains operation records, each operation record is of a certain type, and each operation record is associated with a transaction. A plurality of operation records is read from the log file into a record store. Records of the plurality of operation records of each operation record type are sampled at a predefined sampling rate. Operation records in the plurality of operations records are identified that are associated with completed transactions of which the sampled operation records are associated. The identified operation records are then extracted from the record store into a data store.

Abstract: A log file contains operation records, each operation record is of a certain type, and each operation record is associated with a transaction. A plurality of operation records is read from the log file into a record store. Records of the plurality of operation records of each operation record type are sampled at a predefined sampling rate. Operation records in the plurality of operations records are identified that are associated with completed transactions of which the sampled operation records are associated. The identified operation records are then extracted from the record store into a data store.

Abstract: A method, computer program product, and system for enabling parallel processing of an XML document without pre-parsing, utilizing metadata associated with the XML document and created at the same time as the XML document. The metadata is used to generate partitions of the XML document at the time of parallel processing, without requiring system-intensive pre-parsing.

Abstract: A method, computer program product, and system for enabling parallel processing of an XML document without pre-parsing, utilizing metadata associated with the XML document and created at the same time as the XML document. The metadata is used to generate partitions of the XML document at the time of parallel processing, without requiring system-intensive pre-parsing.

Abstract: Methods and arrangements for processing hierarchical data in a map-reduce framework. Hierarchical data is accepted, and a map-reduce job is performed on the hierarchical data. This performing of a map-reduce job includes determining a cost of partitioning the data, determining a cost of redefining the job and thereupon selectively performing at least one step taken from the group consisting of: partitioning the data and redefining the job.

Abstract: A method for identifying matching transactions between two log files where each transaction includes one or more statements. Each log file record records the execution of a statement and includes a transaction identifier. Each record in turn in one log file is compared to an advancing window of records in the other log file. A first table contains associations of statements to transactions and transactions to statements for records in the window. If a match is found between a record in the one file and a record in the window, information associating partial transactions in the one file to potential transactions of the records in the window is added to a second table. If an end-of-transaction record is read from the one file, a best match is found between the ended transaction and the potential transactions based on information in the first and second tables.

Abstract: A method for identifying matching transactions between two log files where each transaction includes one or more statements. Each log file record records the execution of a statement and includes a transaction identifier. Each record in turn in one log file is compared to an advancing window of records in the other log file. A first table contains associations of statements to transactions and transactions to statements for records in the window. If a match is found between a record in the one file and a record in the window, information associating partial transactions in the one file to potential transactions of the records in the window is added to a second table. If an end-of-transaction record is read from the one file, a best match is found between the ended transaction and the potential transactions based on information in the first and second tables.

Abstract: A method for receiving a declarative specification including a plurality of stages. Each stage specifies an atomic operation, a data input to the atomic operation, and a data output from the atomic operation. The data input is characterized by a data type. Links between at least two of the stages are generated to create a data integration workflow. The data integration workflow is compiled to generate computer code for execution on a parallel processing platform. The computer code configured to perform at least one of data preparation and data analysis.

Abstract: Methods and arrangements for extracting tuples from a streaming XML document. A query twig is applied to the XML document stream, tuples are extracted from the XML document stream based on the query twig, and a quantity of extracted tuples is limited via foregoing extraction of duplicate tuples extraction of tuples that do not satisfy query twig criteria.

Abstract: A method for receiving a declarative specification including a plurality of stages. Each stage specifies an atomic operation, a data input to the atomic operation, and a data output from the atomic operation. The data input is characterized by a data type. Links between at least two of the stages are generated to create a data integration workflow. The data integration workflow is compiled to generate computer code for execution on a parallel processing platform. The computer code configured to perform at least one of data preparation and data analysis.

Abstract: A resend operation of application-level messages by communicating control messages over a publish/subscribe channel. A sending module sends application-level original messages to recipients, and stores a copy of the original message in a store. A resend determination module determines, in the event of insufficient acknowledgement of the original message, whether the original message should be resent. If the original message should be resent, the resend determination module also publishes a control message that correlates to the original message. A resend module subscribes in a manner that results in the resend module receiving the control message, and uses the control message to determine that the corresponding original message should be resent, whereupon the original message may be resent using the copy of the original message in the store.

Abstract: Arrangements and methods for employing empirical evidence to estimate the performance of applications with very few data samples, in complex environments such as dynamic SDP environments, using one or more effective data-plotting models.

Abstract: Methods and arrangements for processing hierarchical data in a map-reduce framework. Hierarchical data is accepted, and a map-reduce job is performed on the hierarchical data. This performing of a map-reduce job includes determining a cost of partitioning the data, determining a cost of redefining the job and thereupon selectively performing at least one step taken from the group consisting of: partitioning the data and redefining the job.