Platform Extension Framework (PXF): Enabling Parallel Query Processing Over Heterogeneous Data Sources In Greenplum

Authors: Venkatesh Raghavan, Alexander Denissov, Francisco Guerrero, Oliver Albertini, Divya Bhargov, Lisa Owen, Shivram Mani, Lav Jain

Abstract: With the explosion of data stores and cloud services, data now resides across many disparate systems and in a variety of formats. When multiple data sets exist in external systems, it is often neces- sary to perform a lengthy ETL (extract, transform, load) operation to get data into the database. But what if we only needed a small subset of the data? What if we only want to query the data to answer a specific question or to create a specific visualization? In this case, it’s often more efficient to join data sets remotely and return only the results, rather than negotiate the time and storage requirements of performing a rather expensive full data load operation. In this paper, we propose Greenplum Database Platform Exten- sion Framework (PXF) for accomplishing this task. PXF is an open source project that provides parallel, high throughput data access and federated query processing across heterogeneous data sources via built-in connectors that map a Greenplum external table defi- nition to an external data source. PXF’s architecture enables users to efficiently query large datasets from multiple external sources, without requiring those datasets be loaded into Greenplum.

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PXF Heterogenous Partitioning Diagram

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