Palantir Technologies Inc.

Paul Nepywoda

Robert Fink

Punyashloka Biswal

Andrew Colombi

Juan Tamayo

Mingyu Kim

Akshay Pundle

David Tolnay

Patrick Koenig

Yupeng Fu

Ashar Fuadi

A method comprises receiving, at a build service of a build server, an external dataset and an adaptor application module, the external dataset being in a specific format, the adaptor application module providing information relevant to a build pipeline maintained by the build service for building an output dataset based on the external dataset, the information including changes to the external dataset since a previous build of the output dataset is performed and a data schema used in the previous build, the build pipeline involving data only in one or more formats other than the specific format; incorporating the external dataset into the build pipeline without the external dataset being reformatted in accordance with requirements of the build service; receiving a request from the adaptor application module for specific information relating to a most recent data build run by the build service; providing a response to the adaptor application module.

Data analytic systems

A method is disclosed, comprising receiving, at a build service, an external dataset and an adaptor associated with the external dataset, the external dataset being in a format which is not managed by the build server. The method may also comprise querying the adaptor, by the build service, for information related to the external dataset. The method may also comprise receiving, at the build service, the information related to the external dataset; and causing, by the build service, the external dataset to be input into a build pipeline using the information related to the external dataset.

Techniques related to a domain-specific language for transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Domain-specific language for dataset transformations

Techniques related to a domain-specific language for dataset transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more dataset transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one dataset transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one dataset transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Growing community of inventors

Palo Alto, CA, United States of America

Paul Nepywoda