Abstract: A method and system for managing an execution plan in a graph database includes: acquiring a graph query language, analyzing the graph query language by using a scanner to generate a predefined Token, and parsing the predefined Token into a data structure by using a parser to obtain an abstract syntax tree; next, processing the abstract syntax tree by using a planner to generate an execution plan, registering a mapping table to store variables in the execution plan and corresponding variable values, and optimizing the execution plan by using an optimizer, where the execution plan includes customized execution operators and customized topologies; and finally, traversing and scheduling the execution plan by using a scheduler, to output an obtained execution result. The present disclosure modularizes the execution operators, improves reusability, and reduces the development cost. The execution plan is scheduled by using an asynchronous notification mechanism, to reduce blocking.

Abstract: Disclosed are a method and system for verifying a resulting behavior of a graph query language. A lexical parser and a preset lexical rule are added to a BDD test framework, to construct an improved BDD test framework; a first Gherkin text in a graph query language standard is migrated to be a second Gherkin text in a graph query language; a first parsing result of the second Gherkin text is acquired from the improved BDD test framework; a first return result from a graph database is acquired, a comparison result between the first parsing result and the first return result is acquired, wherein the graph query language meets the graph query language standard if the first parsing result and the first return result are the same. The present disclosure solves the problem that the BDD test framework cannot recognize complex Gherkin texts, thereby facilitating development of graph databases.

Abstract: A method and system for managing an execution plan in a graph database includes: acquiring a graph query language, analyzing the graph query language by using a scanner to generate a predefined Token, and parsing the predefined Token into a data structure by using a parser to obtain an abstract syntax tree; next, processing the abstract syntax tree by using a planner to generate an execution plan, registering a mapping table to store variables in the execution plan and corresponding variable values, and optimizing the execution plan by using an optimizer, where the execution plan includes customized execution operators and customized topologies; and finally, traversing and scheduling the execution plan by using a scheduler, to output an obtained execution result. The present disclosure modularizes the execution operators, improves reusability, and reduces the development cost. The execution plan is scheduled by using an asynchronous notification mechanism, to reduce blocking.

Abstract: Disclosed are a method and system for verifying a resulting behavior of a graph query language. A lexical parser and a preset lexical rule are added to a BDD test framework, to construct an improved BDD test framework; a first Gherkin text in a graph query language standard is migrated to be a second Gherkin text in a graph query language; a first parsing result of the second Gherkin text is acquired from the improved BDD test framework; a first return result from a graph database is acquired, a comparison result between the first parsing result and the first return result is acquired, wherein the graph query language meets the graph query language standard if the first parsing result and the first return result are the same. The present disclosure solves the problem that the BDD test framework cannot recognize complex Gherkin texts, thereby facilitating development of graph databases.