[Feature Summary] Enhancement and optimization OLTP algorithm & api

[DanGuge]

Feature Description (功能描述)

Background

HugeGraph provides interfaces for querying through RESTful APIs. However, in the current RESTful API corresponding to the OLTP algorithms, both the algorithms and functionalities are not yet fully complete and require further expansion. There is also room for optimization in the execution of the algorithm. Therefore, in this feature implementation, we have set the following objectives:

• Provide more comprehensive query result information and details about algorithm execution
• Enhance algorithm execution efficiency through techniques such as pruning and parallelization

In the existing HugeGraph framework, the OLTP algorithm corresponds to the following interfaces, all of which will be subject to modification:

OLTP APIs
Kout Get
Kout Post
Kneighbor Get
Kneighbor Post
Sameneighbors Get
Sameneighbors Post
Jaccard Similarity Get
Jaccard Similarity Post
Shortest Path Get
All Shortest Paths Get
Weighted Shortest Path Get
Single Source Shortest Path Get
Multi Node Shortest Path Post
Paths Get
Paths Post
Customized Paths Post
Template Paths Post
Crosspoints Get
Customized Crosspoints Post
Rings Get
Rays Get
Fusiform Similarity Post

Tasks

• [x] Enhance all OLTP algorithm APIs by adding statistical information, including the number of traversed vertices, edges, and execution time #2262
• [x] Enable support for returning partial/complete information of vertices and edges in all OLTP algorithm APIs #2262
• [x] Provide support for filtering vertex and edge properties in OLTP algorithm APIs, reducing unnecessary graph searches through pruning code link
• [x] Integrate DFS query mode into the Kout algorithm code link
• [ ] Implement support for batch processing and concurrent execution using multiple threads
• [ ] Add the related doc in website