Alibaba Cloud Certified Associate (ACA) Practice Test 2025 – Complete All-in-One Guide for Exam Success!

Creating a gin index for multiple fields is considered a best practice in the context of ApsaraDB for PolarDB when querying based on multiple fields. This type of index is designed to optimize searches across multiple columns, particularly when dealing with queries that involve more complex data types or full-text search scenarios. Gin (Generalized Inverted Index) indexes help improve the performance of queries that involve array values or nested data structures, making them particularly suitable for handling scenarios where multiple fields must be evaluated together.

By using a gin index, the database can efficiently search through multiple attributes, reducing the need for scanning large volumes of data and consequently speeding up query response times. This can lead to significantly enhanced performance in applications that require rapid access to data based on multiple criteria. Moreover, using a combined index approach enables the database engine to better utilize resources, leading to optimal performance for read operations.

The other options have their use cases but may not provide the same level of performance or efficiency as a gin index for queries involving multiple fields. For instance, creating a single index for all fields combined may not leverage the specific strengths of the data, while separate indexes for each field could lead to inefficient query processing, as the database may have to evaluate multiple indexes rather than leveraging a