提速三倍？不止！悦数图数据库 v5.0 技术特性抢先看！

作为杭州悦数的最新产品，悦数图数据库 v5.0 不仅是全球首家，更是目前唯一一家支持 ISO/IEC 39075:GQL 国际图查询语言标准的分布式图数据库。它使用属性图模型，集中管理和存储用户数据，并且可以使用经过市场认证的 MATCH 语句以及其他丰富的类 SQL 语句，轻松完成查询属性图。

不同于兼容或适配 GQL 的技术路线，悦数图数据库在数据库核心和底层架构进行了重构，全面拥抱  GQL。同之前版本的悦数图数据库相似，属性图的  schema 仍然是用户创建或修改，并由数据库管理的。

以下是一个使用 GQL 编写的 DDL 查询示例，该查询尝试创建一个包含一组节点类型（如 City、Country、Continent 等）和边类型（如 CITY_IS_PART_OF_COUNTRY、COUNTRY_IS_PART_OF_CONTINENT 等）的图类型。每个节点或边类型都有其类型名称（如 City）、一组可选标签（如 City、Place）和一组可选属性（如 id、name、url）。

CREATE GRAPHTYPE IF NOT EXISTS ldbc_type AS {  
    NODE City(LABELS City&Place {id INT64 PRIMARY KEY, name STRING, url STRING}),  
    NODE Country(LABELS Country&Place {id INT64 PRIMARY KEY, name STRING, url STRING}),  
    NODE Continent(LABELS Continent&Place {id INT64 PRIMARY KEY, name STRING, url STRING}),  
    ...  
    EDGE CITY_IS_PART_OF_COUNTRY (City)-[:IS_PART_OF]->(Country),  
    EDGE COUNTRY_IS_PART_OF_CONTINENT (Country)-[:IS_PART_OF]->(Continent),  
    EDGE UNIVERSITY_IS_LOCATED_IN_CITY (University)-[:IS_LOCATED_IN]->(City),  
}

CREATE GRAPH IF NOT EXISTS LDBC TYPE ldbc_type

MATCH  
 (person:Person)-[:KNOWS]->(friend:Person),  
 (message:Message)-[:HAS_CREATOR]->(friend)  
ORDER BY person.id DESC,  
 message.id ASC  
LIMIT 
 20  
RETURN
 friend.id AS personId, 
 friend.firstName AS personFirstName, 
 friend.lastName AS personLastName,  
 message.id AS postOrCommentId

一个三节点集群

64 核 Intel 8352Y CPU，2.20GHz，

256GB DRAM

2TB SSDs

比例因子（SF）为 100

printf("hello USE ldbc
MATCH 
  (p:Person{id:2}),
  (friend:Person{firstName:"Kyle"})
WHERE 
  p<>friend
MATCH 
  path1 = ANY SHORTEST PATH (p)-[:KNOWS]-{1,3}(friend)
RETURN 
  min(length(path1)) AS distance,
  friend GROUP BY friend
NEXT 
USE ldbc
ORDER BY
  distance ASC,
  friend.lastName ASC,
  friend.id ASC
LIMIT
  20
MATCH
  (friend)-[:IS_LOCATED_IN]->(friendCity:City)
OPTIONAL MATCH
  (friend)-[studyAt:STUDY_AT]->(uni:University)-[:IS_LOCATED_IN]->(uniCity:City)
RETURN 
  collect(CASE WHEN NOT uni.name IS NULL THEN RECORD 
      {uniName:uni.name,
      studyAtClassYear:studyAt.classYear, 
      uniCityName:uniCity.name} END
    ) AS unis,
  friend,
  friendCity,
  distance GROUP BY friend,
  friendCity,
  distance
NEXT 
USE ldbc
OPTIONAL MATCH
  (friend)-[workAt:WORK_AT]->(company:Company)-[:IS_LOCATED_IN]->(companyCountry:Country)
RETURN
  collect(CASE WHEN NOT company.name is null THEN RECORD 
      {companyName:company.name,
      workAtWorkFrom:workAt.workFrom,
      companyCountryName:companyCountry.name} END
    ) AS companies,
  friend,
  unis,
  friendCity,
  distance GROUP BY friend,
  unis,
  friendCity,
  distance
NEXT
USE ldbc
ORDER BY
  distance ASC,
  friend.lastName ASC,
  friend.id ASC
LIMIT 20
RETURN
  friend.id AS friendId,
  friend.lastName AS friendLastName,
  distance AS distanceFromPerson,
  friend.birthday AS friendBirthday,
  friend.creationDate AS friendCreationDate,
  friend.gender AS friendGender,
  friend.browserUsed AS friendBrowserUsed,
  friend.locationIP AS friendLocationIp,
  friend.email AS friendEmails,
  friend.speaks AS friendLanguages,
  friendCity.name AS friendCityName,
  unis AS friendUniversities,
  companies AS friendCompanies
world!");