Abstract: The techniques described herein facilitate asynchronous execution of computationally expensive spreadsheet tasks and. In some embodiments, asynchronous calls to remote services for handling complex processing tasks such as, for example, complex calculations involving large data sets from one or more spreadsheets of a workbook are described. The handling can include generating a job including a data set from one or more spreadsheets and an instruction directing a remote service to asynchronously execute a computationally expensive spreadsheet task. Responsive to sending the remote service a request to perform the job, a persistent job identifier (ID) associated with the job is received by the spreadsheet application and embedded in (and/or otherwise associated with) at least one or more of the spreadsheets of the workbook. The job is then asynchronously executed by the remote service and the results are accessible from any client device having access to the workbook using the embedded or associated job ID.

Abstract: The techniques described herein facilitate asynchronous management of external or Big Data processing pipelines from within client-side (or local) spreadsheet applications, e.g., Microsoft Excel®. In an implementation, a method of operating a spreadsheet application service to facilitate management of big data pipelines from within a client-side spreadsheet application is disclosed. The method includes receiving a processing request initiated by a spreadsheet application. The processing request includes instructions for generating one or more big data pipelines between one or more external distributed computing systems. The method further includes translating the instruction into one or more scripts corresponding to the one or more external distributed computing systems, and executing the one or more scripts to direct the one or more external distributed computing systems to automatically generate the big data pipelines.

Abstract: The techniques described herein facilitate asynchronous management of external or Big Data processing pipelines from within client-side (or local) spreadsheet applications, e.g., Microsoft Excel®. In an implementation, a method of operating a spreadsheet application service to facilitate management of big data pipelines from within a client-side spreadsheet application is disclosed. The method includes receiving a processing request initiated by a spreadsheet application. The processing request includes instructions for generating one or more big data pipelines between one or more external distributed computing systems. The method further includes translating the instruction into one or more scripts corresponding to the one or more external distributed computing systems, and executing the one or more scripts to direct the one or more external distributed computing systems to automatically generate the big data pipelines.

Abstract: The techniques described herein facilitate asynchronous execution of computationally expensive spreadsheet tasks and. In some embodiments, asynchronous calls to remote services for handling complex processing tasks such as, for example, complex calculations involving large data sets from one or more spreadsheets of a workbook are described. The handling can include generating a job including a data set from one or more spreadsheets and an instruction directing a remote service to asynchronously execute a computationally expensive spreadsheet task. Responsive to sending the remote service a request to perform the job, a persistent job identifier (ID) associated with the job is received by the spreadsheet application and embedded in (and/or otherwise associated with) at least one or more of the spreadsheets of the workbook. The job is then asynchronously executed by the remote service and the results are accessible from any client device having access to the workbook using the embedded or associated job ID.