基于PostgreSQL的海量准实时数据服务平台访问方案

大数据服务平台在电网系统中具有重要的应用价值.海量准实时数据平台作为电网重要数据中心，存储了大量有价值的数据，其存储的数据多为非结构化数据，无法直接通过SQL语句获取.为了最大限度挖掘数据价值，需要在平台中集成SQL访问实时数据的功能.为此，本文基于PostgresSQL Foreign Data Wrapper （Postgres_fdw）开发了SQL引擎.通过分析PostgresSQL的功能特点以及已有UAPI接口的不足，针对原有大数据平台框架，采用分层策略，基于Postgres_fdw开发了SQL引擎，并提出了针对海量平台中实时数据库的外部表空间估算方案和SQL解析方案，以此实现数据平台运用SQL的方式获取底层海量平台数据的功能.现场功能和性能测试，验证了该引擎的有效性.

PostgreSQL-Based Big Data Access Scheme of Massive Quasi-Real-Time Data Service Platform

Big data services platform has important applications in the power distribution system. Massive quasi-real-time data service platform is a key data center in power grid, and a lot of valuable data is stored in the platform. The data in platform is unstructured, and cannot be selected by SQL statement. To maximize mining the data value, platform needs to integrate function that the accesses to real-time data, for this develop SQL engine based on PostgresSQL foreign data wrapper (Postgres_fdw). The SQL engine proposes a foreign table space estimation scheme and SQL resolution scheme for real-time databases in massive platforms. This access scheme provided good support for big data platform to get data from the underlying massive data service platform with an SQL way. Field function and performance tests validated the effectiveness of the engine.