Ab Initio Technology LLC

Thinking Machines Corporation

Ab Initio Software Corporation

Marshall Alan Isman

John Joyce

Jonah Egenolf

John L Richardson

Richard Alan Epstein

Sandrick Melbouci

Ian Schechter

Andrew Fiske Roberts

Ralf Haug

John Ralston

Justin Pniower

Craig W Stanfill

Bryan Phil Douros

Ephraim Meriwether Vishniac

Paul Bay

H Mark Bromley

Darren Miller

Frederic Wild

Andrew Blom

Sam Kendall

Timothy Wakeling

Ann M Wollrath

Adam Harris Weiss

Dusan Radivojevic

David S Wells

David Potter

Robert Parks

David L Satterfield

James P Tardiff

Eric L Rowe

David C Taylor

Philippe Printz

John MacLean

Paul Veiser

Mazin Woodrow Khader

Ann M Johnson

Richard Mellon

John M Baron

Laurence N Provost

Eric D Sharakan

David A Sheppard

David Stefanovic

A method includes accessing a schema that specifies relationships among datasets, computations on the datasets, or transformations of the datasets, selecting a dataset from among the datasets, and identifying, from the schema, other datasets that are related to the selected dataset. Attributes of the datasets are identified, and logical data representing the identified attributes and relationships among the attributes is generated. The logical data is provided to a development environment, which provides access to portions of the logical data representing the identified attributes. A specification that specifies at least one of the identified attributes in performing an operation is received from the development environment. Based on the specification and the relationships among the identified attributes represented by the logical data, a computer program is generated to perform the operation by accessing, from storage, at least one dataset having the at least one of the attributes specified in the specification.

Generation of optimized logic from a schema

A method implemented by a data processing system for enabling a system to pipeline or otherwise process data in conformance with specified criteria by providing a graphical user interface for selecting data to be processed, determining metadata of selected data, and, based on the metadata, automatically processing the selected data in conformance with the specified criteria.

Meta-data driven ingestion and data processing

A method for generating an executable application to transform and load data into a structured dataset includes receiving a metadata file that specifies values for parameters for structuring data feeds, received from a networked data source, into a structured database. The metadata file specifies logical rules for transforming the data feeds. The values of the parameters and the logical rules for transforming the plurality of the data feeds are validated to ensure logical consistency for each data feed. Data rules are generated that specify standards for transforming each data feed in accordance with the validated values of the parameters and logical rules. The executable application is generated that is configured to receive source data comprising a data feed from one or more data sources and transform the source data into structured data that satisfies the one or more standards for the structured data record in compliance with the data rules.

Publishing to a data warehouse

Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Generating rules for data processing values of data fields from semantic labels of the data fields

A method performed by a computer system including: accessing a specification that specifies a plurality of modules to be implemented by the computer program for processing the one or more values of the one or more fields in the structured data item; transforming the specification into the computer program that implements the plurality of modules, wherein the transforming includes: for each of one or more first modules of the plurality of modules: identifying one or more second modules of the plurality of modules that each receive input that is at least partly based on an output of the first module; and formatting an output data format of the first module such that the first module outputs only one or more values of one or more fields of the structured data item.

Transforming a specification into a persistent computer program

An approach to parallel access of data from a distributed filesystem provides parallel access to one or more named units (e.g., files) in the filesystem by creating multiple parallel data streams such that all the data of the desired units is partitioned over the multiple streams. In some examples, the multiple streams form multiple inputs to a parallel implementation of a computation system, such as a graph-based computation system, dataflow-based system, and/or a (e.g., relational) database system.

Parallel access to data in a distributed file system

A method for analyzing a computer program ecosystem includes performing a static analysis, including identifying static dependencies among elements of the ecosystem based on values of parameters in one or more parameter sets associated with the ecosystem, the elements of the ecosystem including the computer programs of the ecosystem and data resources associated with the computer programs. The method includes performing a runtime analysis, including identifying elements of the ecosystem that were utilized during execution of the ecosystem to process data records. The method includes performing a schedule analysis, including identifying a computer program of the ecosystem that has a schedule dependency from another computer program of the ecosystem. The method includes identifying a subset of the elements of the ecosystem as an ecosystem unit based on the results of the static, runtime, and schedule analyses. The method includes migrating the ecosystem unit, testing the ecosystem unit, or both.

Static and runtime analysis of computer program ecosystems

A method includes analyzing, by a processor, a first version of a computer program, the analyzing including identifying a first process included in the first version of the computer program, the first process configured to perform an operation on data having a first format; and by a processor, generating a second version of at least a portion of the computer program, including omitting the first process and including in the second version of the at least portion of the computer program one or more second processes configured to perform a second operation on data of a second format different from the first format, wherein the second operation is based on the first operation.

Format-specific data processing operations

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Newton, MA, United States of America

Marshall Alan Isman