For information about basic search SDKs of Industry Algorithm Edition, see Demo code for implementing the search feature.
The drop-down suggestion feature is a basic feature of OpenSearch. This feature provides recommended search queries for you to select when you enter a search query. You may find the expected search query before you enter the full content of the search query. This helps you obtain the expected search results as soon as possible. For more information, see Demo code for implementing the drop-down suggestion feature.
The query analysis feature can be used to understand the search intent in OpenSearch. This feature performs various intelligent analysis on a search query, rewrites the search query, and then submits the search query to the search engine. Then, the search engine retrieves and sorts data based on the search query. For more information, see Demo code for implementing the query analysis feature.
In traditional search scenarios, the purpose is to retrieve the most matched results in the shortest period of time. Therefore, the number of documents that can be contained in results is limited. For example, the results of a search can contain up to 5,000 documents. However, in some scenarios, you may need more results for analysis. In this case, you can use scroll searches to obtain more search results. For more information, see Demo code for implementing scroll queries and Demo code for implementing iterative scroll queries.