这里有三个有效的 sqlite 风格的实现（一旦使用 sqlite，不强制的列类型是可以接受的，只使用整数主键来充当 rowid）：
在所有情况下，sqlite 外键 PRAGMA 设置为 true：PRAGMA foreign_keys = 1;
简单的实现 - 每个源/级别都有一个固定表（受外键约束）
以下设计/实现为每种类型的数据库和级别使用一个表。表使用外键相互引用以确保正确性。例如，mongo collection 不能是 mysql database 的子级。仅在connection 级别，所有数据库类型共享同一个表，但如果预期每种connection 的属性不同，则可能会有所不同。
create table databasetype(name primary key) without rowid;
insert into databasetype values ('mysql'),('elasticsearch'),('mongo'),('sqlserver');
create table datatype(name primary key) without rowid;
insert into datatype values ('int'),('str'); -- you can differentiate varchar if you will
create table connection(id integer, hostname, databasetype, primary key(id), foreign key(databasetype) references databasetype(name));
create table mysqldatabase(id integer, connectionid, name, primary key(id), foreign key(connectionid) references connection(id));
create table mysqltable(id integer, databaseid, name, primary key(id), foreign key(databaseid) references mysqldatabase(id));
create table mysqlfield(id integer, tableid, name, datatype, datalength, primary key(id), foreign key(tableid) references mysqltable(id), foreign key(datatype) references datatype(name));
create table elasticsearchindex(id integer, connectionid, name, primary key(id), foreign key(connectionid) references connection(id));
create table elasticsearchfield(id integer, indexid, name, datatype, datalength, primary key(id), foreign key(indexid) references mysqltable(id), foreign key(datatype) references datatype(name));
create table mongodatabase(id integer, connectionid, name, primary key(id), foreign key(connectionid) references connection(id));
create table mongocollection(id integer, databaseid, name, primary key(id), foreign key(databaseid) references mongodatabase(id));
create table mongofield(id integer, collectionid, name, datatype, datalength, primary key(id), foreign key(collectionid) references mongocollection(id), foreign key(datatype) references datatype(name));
create table sqlserverdatabase(id integer, connectionid, name, primary key(id), foreign key(connectionid) references connection(id));
create table sqlserverschema(id integer, databaseid, name, primary key(id), foreign key(databaseid) references sqlserverdatabase(id));
create table sqlservertable(id integer, schemaid, name, primary key(id), foreign key(schemaid) references sqlserverschema(id));
create table sqlserverfield(id integer, tableid, name, datatype, datalength, primary key(id), foreign key(tableid) references sqlservertable(id), foreign key(datatype) references datatype(name));
加载代表第一个表的数据：
insert into connection(hostname, databasetype) values ('remote:1234', 'mysql');
insert into mysqldatabase(connectionid, name) select id, 'sales' from connection where hostname='remote:1234';
insert into mysqltable(databaseid, name) select id, 'user' from mysqltable where name='sales';
insert into mysqlfield(tableid, name, datatype, datalength) select id, 'name', 'str', 80 from mysqldatabase where name='product';
insert into mysqlfield(tableid, name, datatype) select id, 'age', 'i32' from mysqldatabase where name='product';
尝试对数据进行无效操作：
insert into mysqlfield(tableid, name, datatype) values (2, 'newfield', 'qubit');
-- Error: FOREIGN KEY constraint failed
为了漂亮地打印整个树，有必要手动连接所有涉及的表。
类似图的实现 - 一个表代表树，另一个代表层次结构（受触发器约束）
这里element 表用于表示树中的每个元素/节点。它的level 列明确地将每个元素分类为database、table 等。这里使用sqlite 的rowid 作为主键，但很容易将其更改为常规id。
在之前的实现中，使用外键来确保模型的正确性。现在触发器用于这项工作。他们决定哪个父级别接受哪个子级别，因为它允许用于相应的 dbtype - 这些规则在 element_type 表中指定。
最后，exra 表element_properties 用于允许将额外属性附加到任何元素，例如字段类型。
create table db_type(name primary key) without rowid;
insert into db_type values ('mysql'),('elasticsearch'),('mongo'),('sqlserver');
create table element_type(parentlevel, childlevel, dbtype, primary key(parentlevel, childlevel, dbtype), foreign key(dbtype) references db_type(name)); --not using without rowid to be able to have null parent level
insert into element_type values
(null, 'connection', 'mysql'),
('connection', 'database', 'mysql'),
('database', 'table', 'mysql'),
('table', 'field', 'mysql'),
(null, 'connection', 'elasticsearch'),
('connection', 'index', 'elasticsearch'),
('index','field', 'elasticsearch'),
(null, 'connection', 'mongo'),
('connection', 'database', 'mongo'),
('database', 'collection', 'mongo'),
('collection', 'field', 'mongo'),
(null, 'connection', 'sqlserver'),
('connection', 'database', 'sqlserver'),
('database', 'schema', 'sqlserver'),
('schema', 'table', 'sqlserver'),
('table', 'field', 'sqlserver');
create table element(id integer, parentid, name, level, dbtype, primary key(id), foreign key(parentid) references element(id), foreign key(dbtype) references db_type(name));
create table element_property(parentid, name, value, primary key(parentid, name), foreign key(parentid) references element(id)) without rowid;
-- trigger to guarantee that new elements will conform hierarchy
create trigger element_insert before insert on element
begin
select iif(count(*)>0, 'ok', raise(abort,'invalid parent-child insertion')) from element_type etc join element_type etp on (etp.childlevel, etp.dbtype)=(etc.parentlevel, etc.dbtype) where (etc.dbtype, etc.parentlevel, etc.childlevel)=(new.dbtype, (select level from element ei where ei.rowid=new.parentid), new.level);
end;
-- trigger to guarantee that updated elements will conform hierarchy
create trigger element_update before update on element
begin
select iif(count(*)>0, 'ok', raise(abort,'invalid parent-child update')) from element_type etc join element_type etp on (etp.childlevel, etp.dbtype)=(etc.parentlevel, etc.dbtype) where (etc.dbtype, etc.parentlevel, etc.childlevel)=(new.dbtype, (select level from element ei where ei.rowid=new.parentid), new.level);
end;
-- trigger to guarantee that hierarchy removal must respect existing elements (no delete cascade used)
create trigger element_type_delete before delete on element_type
begin
select iif(count(*)>0, raise(abort,'can''t remove, entries found in the element table using this relationship'), 'ok') from element etc join element etp on etp.rowid=etc.parentid and etp.dbtype=etp.dbtype where etc.dbtype=old.dbtype and (etp.level,etc.level)=(old.parentlevel, old.childlevel);
end;
-- trigger to guarantee that hierarchy changes must respect existing elements
create trigger element_type_update before update on element_type
begin
select iif(count(*)>0, raise(abort,'can''t change, entries found in the element table using this relationship'), 'ok') from element etc join element etp on etp.rowid=etc.parentid and etp.dbtype=etp.dbtype where etc.dbtype=old.dbtype and (etp.level,etc.level)=(old.parentlevel, old.childlevel) and (etp.level,etc.level)!=(new.parentlevel, new.childlevel);
end;
加载代表第一个表的数据：
insert into element(name, level, dbtype) values ('remote:1234', 'connection', 'mysql');
insert into element(name, level, dbtype, parentid) values ('sales', 'database', 'mysql', (select id from element where (level, name, dbtype)=('connection', 'remote:1234', 'mysql')));
insert into element(name, level, dbtype, parentid) values ('user', 'table', 'mysql', (select id from element where (level, name, dbtype)=('database', 'sales', 'mysql')));
insert into element(name, level, dbtype, parentid) values ('name', 'field', 'mysql', (select id from element where (level, name, dbtype)=('table', 'user', 'mysql')));
insert into element(name, level, dbtype, parentid) values ('age', 'field', 'mysql', (select id from element where (level, name, dbtype)=('table', 'user', 'mysql')));
insert into element_property(name, value, parentid) values ('fieldtype', 'varchar', (select id from element where (level, name, dbtype)=('field', 'name', 'mysql')));
insert into element_property(name, value, parentid) values ('fieldlength', 80, (select id from element where (level, name, dbtype)=('field', 'name', 'mysql')));
insert into element_property(name, value, parentid) values ('fieldtype', 'integer', (select id from element where (level, name, dbtype)=('field', 'age', 'mysql')));
尝试对数据进行无效操作：
insert into element(name, level, dbtype, parentid) values ('documents', 'collection', 'mysql', (select id from element where (level, name, dbtype)=('database', 'sales', 'mysql')));
-- Error: invalid parent-child insertion
update element_type set childlevel='specialfield' where dbtype='mysql' and (parentlevel, childlevel)=('table','field');
-- Error: can't change, entries found in the element table using this relationship
漂亮地打印树：
create view elementree(path) as
with recursive cte(id, name, depth, dbtype, level) as (
select id, name, 0 as depth, dbtype, level from element where parentid is null
union all
select el.id, el.name, cte.depth+1 as depth, el.dbtype, el.level from element el join cte on el.parentid=cte.id
order by depth desc
)
select substring(' ',0,2*depth)||name||' ('||dbtype||'-'||level||')' from cte;
select * from elementree;
-- remote:1234 (mysql-connection)
-- sales (mysql-database)
-- user (mysql-table)
-- documents (mysql-table)
-- name (mysql-field)
-- age (mysql-field)
极简 DRY 图类实现 - 一张表，只有名称代表树，只有一张辅助表
这里再次使用element 表来表示树中的每个元素。与前一种情况不同的是，该表的信息较少，并且每个元素的类型——无论是database 还是table，都是隐式推断的，而不是由列显式确定的。通过简单地将user 添加为sales 的子代，推断user 是mysql table，一旦它是mysql 的子代database - sales，即adatabase因为它是 mysql connection 的子元素，它是 mysql 根元素的子元素。 dbtypes 是这棵树中的根元素，它们的所有子元素都被推断为这个 dbtype。
这里hierarchypath 表用于告诉element 树中遵循的层次结构。对于用户 confort，他只需要插入一个（> 分隔的）字符串，代表层次结构路径，从 dbtype 开始。层次结构视图会将这个字符串解构为层次结构。雇佣路径的一个示例是：mysql>connection>database>table>field。
再次注意，sqlite 的 rowid 被用作表 id。请记住，仅通过select * from table;是看不到rowid的，它默认是隐藏的，需要显式选择它：select rowid,* from table;。
create table element(name, parentrowid, foreign key(parentrowid) references element(rowid));
-- dbtypes are the root elements
insert into element(name) values ('mysql'),('elasticsearch'),('mongo'),('sqlserver');
create table hierarchypath(path);
insert into hierarchypath values
('mysql>connection>database>table>field'),
('elasticsearch>connection>index>field'),
('mongo>connection>database>collection>field'),
('sqlserver>connection>schema>database>table>field');
加载数据：
insert into element select 'remote:1234',rowid from element where (name,coalesce(parentrowid,-1))=('mysql',-1); --returning rowid; -- returning only works for sqlite 3.35+
insert into element select 'sales',rowid from element where rowid=5;
insert into element select 'user',rowid from element where rowid=6;
insert into element select 'name',rowid from element where rowid=7;
insert into element select 'age',rowid from element where rowid=7;
印刷精美：
create view hierarchy(root, depth, name) as
with recursive hierarchycte(root, depth, name, remaining) as (
select substr(path, 0, instr(path, '>')) as root, 0 as depth, substr(path, 0, instr(path, '>')) as name, substr(path, instr(path, '>')+1)||'>' as remaining from hierarchypath
union all
select root, depth+1 as depth, substr(remaining, 0, instr(remaining, '>')) as name, substr(remaining, instr(remaining, '>')+1) as remaining from hierarchycte where instr(remaining, '>') > 0
)
select root, depth, name from hierarchycte where depth>=0;
create view elementhierarchy(root, depth, name) as
with recursive elementcte(root, depth, name, rowid, parentrowid) as (
select name as root, 0 as depth, name, rowid, parentrowid from element where parentrowid is null
union all
select elcte.root, elcte.depth+1, el.name, el.rowid, el.parentrowid from elementcte elcte join element el on el.parentrowid=elcte.rowid
order by depth desc
)
select root, depth, name from elementcte;
create view elementree as
with recursive elementcte(root, depth, name, rowid, parentrowid) as (
select name as root, 0 as depth, name, rowid, parentrowid from element where parentrowid is null
union all
select elcte.root, elcte.depth+1, el.name, el.rowid, el.parentrowid from elementcte elcte join element el on el.parentrowid=elcte.rowid
order by depth desc
)
select substring(' ',0,2*h.depth-2)||eh.name||' ('||h.root||'-'||h.name||')' from (select *,row_number() over () as originalorder from elementhierarchy) eh join hierarchy h on (eh.root,eh.depth)=(h.root,h.depth) where h.depth>0 order by originalorder;
select * from elementree;
-- remote:1234 (mysql-connection)
-- sales (mysql-database)
-- user (mysql-table)
-- age (mysql-field)
-- name (mysql-field)
这里没有实现触发器，但这样做会很好。一个例子是避免插入超过允许的级别。
将层次结构存储在视图上看到的解构形式中会更明智
层次结构，通过在插入时间而不是每个选择查询中进行解构来避免 CPU 消耗。在这里，它以这种方式与其他实现区分开来。
这里是最后一级实体，field 没有之前实现中显示的属性。在此模型中，需要向层次结构添加一个或两个额外级别：...table>field>fieldpropertyandvalue 或 ...table>field>fieldproperty>fieldpropertyvalue，在第一种情况下，fieldpropertyandvalue 的示例将是 datatype=integer，而分离的属性和值的示例将分别为datatype 和integer。这种任何属性都是图中新节点的方法更接近 RDF 存储使用的方法。
最后必须说明的是，可以使用专门的图形数据库，使用它们自己的查询语言，例如 neo4j 中的 cypher 和其他语言中的 sparql，但由于图形设计总体上很简单，因此关系数据库满足我们的需要。