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Arunesh Choudhary
Arunesh Choudhary

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04 - Foreign Data Wrappers

Foreign Data Wrappers

The PostgreSQL addition known as Foreign Data Wrappers (FDWs) enables the database to communicate with external data sources as if they were standard PostgreSQL tables. FDWs offer a way to access and query information held in distant databases or other non-database sources, such files, online services, or other DMSs.

An external data source can be connected to and tables or views that reflect the remote data defined when a Foreign Data Wrapper is installed and configured in PostgreSQL. Regular SQL commands may be used to query, join with local tables, and alter these virtual tables, which are referred to as foreign tables.

FDWs Crucial role in query processing

When using remote data sources, Foreign Data Wrappers (FDWs) are essential to PostgreSQL query processing.

How FDWs affect query processing is as follows:

Query Planning: The PostgreSQL query optimizer examines the query and creates an execution plan during query planning. While FDWs are present, the optimizer takes their capabilities and statistics into account while choosing the most effective plan.

Query Execution: To get the required data from the remote source while running a query using FDWs, the PostgreSQL execution engine communicates with the FDW. The FDW manages communication with the outside system and gives the execution engine the necessary data.

Data Retrieval: The FDW translates the activities that should be performed on the remote data source based on the query that was executed against the foreign table. In order to process the necessary data, it transmits it to the PostgreSQL execution engine.

Parallel Query Execution: PostgreSQL allows for the parallel execution of queries, and FDWs may use this feature when appropriate. In order to speed up data retrieval, PostgreSQL can split the query burden among many processes if the FDW and the remote data source enable parallel execution.

Data Integration and Joins: FDWs make it possible to seamlessly combine local PostgreSQL data with distant data. The query optimizer can make join operations between foreign tables and local tables more efficient by using the FDW's cost estimation and available information.

Closing Remarks

FDWs offer an expandable and adaptable method for incorporating external data sources into PostgreSQL's query processing. FDWs offer effective query planning and execution by utilizing statistics, join capabilities, and pushdown optimization. This allows for easy access to remote data while maximizing speed.

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