一种解决方案是执行以下操作：
1) 将名称拆分为一些临时表，以便比较容易进行
2) 构造一个查询，尝试根据某个距离查找匹配项
1) 分词
设置
-- drop table Table1
create table Table1
(
Id1 INT NOT NULL CONSTRAINT PK_Table1 PRIMARY KEY IDENTITY (1, 1),
Column1 NVARCHAR(200) NOT NULL
)
GO
insert into Table1 (Column1)
VALUES ('Tom Hawky'), ('Antony Hendric Formen'), ('Cathy Cassy'), ('Bill Gates'), ('Mary Diore')
GO
-- drop table Table2
create table Table2
(
Id2 INT NOT NULL CONSTRAINT PK_Table2 PRIMARY KEY IDENTITY (1, 1),
Column2 NVARCHAR(200) NOT NULL
)
GO
insert into Table2 (Column2)
VALUES ('Christopher Fridricson'), ('Ken Lovely'), ('Tom Hawky'), ('Anthony Foreman'), ('Chati Cassei'), ('Tom X')
GO
select * from Table1
GO
select * from Table2
GO
拆分功能
有几个split functions可以使用，我选择了XML方式：
CREATE FUNCTION dbo.SplitStrings_XML
(
@List NVARCHAR(MAX),
@Delimiter NVARCHAR(255)
)
RETURNS TABLE
WITH SCHEMABINDING
AS
RETURN
(
SELECT Item = y.i.value('(./text())[1]', 'nvarchar(4000)')
FROM
(
SELECT x = CONVERT(XML, '<i>'
+ REPLACE(@List, @Delimiter, '</i><i>')
+ '</i>').query('.')
) AS a CROSS APPLY x.nodes('i') AS y(i)
);
GO
分词
drop table #T1Words
Go
create table #T1Words (Id1 INT NOT NULL, Word NVARCHAR(100))
GO
insert into #T1Words
select T1.Id1, X1.Item
from Table1 T1
cross apply dbo.SplitStrings_XML (T1.Column1, N' ') X1
GO
drop table #T2Words
GO
create table #T2Words (Id2 INT NOT NULL, Word NVARCHAR(200))
GO
insert into #T2Words
select T2.Id2, X2.Item
from Table2 T2
cross apply dbo.SplitStrings_XML (T2.Column2, N' ') X2
GO
使用一定距离选择
一个可以使用的距离是Levenshtein。要想在SQL中使用，必须在CLR中实现，否则很慢。像这样的：
[Microsoft.SqlServer.Server.SqlFunction(IsDeterministic = true, IsPrecise = false)]
public static int Levenshtein(SqlString S1, SqlString S2)
{
if (S1.IsNull)
S1 = new SqlString("");
if (S2.IsNull)
S2 = new SqlString("");
int maxLen = 4096;
// keeping only the first part of the string (performance reasons)
String SC1 = S1.Value.ToUpper();
String SC2 = S2.Value.ToUpper();
if (SC1.Length > maxLen)
SC1 = SC1.Remove(maxLen);
if (SC2.Length > maxLen)
SC2 = SC2.Remove(maxLen);
int n = SC1.Length;
int m = SC2.Length;
short[,] d = new short[n + 1, m + 1];
int cost = 0;
if (n + m == 0)
{
return 0;
}
else if (n == 0)
{
return 0;
}
else if (m == 0)
{
return 0;
}
for (short i = 0; i <= n; i++)
d[i, 0] = i;
for (short j = 0; j <= m; j++)
d[0, j] = j;
for (int i = 1; i <= n; i++)
{
for (int j = 1; j <= m; j++)
{
if (SC1[i - 1] == SC2[j - 1])
cost = 0;
else
cost = 1;
d[i, j] = (short) System.Math.Min(System.Math.Min(d[i - 1, j] + 1, d[i, j - 1] + 1), d[i - 1, j - 1] + cost);
}
}
// double percentage = System.Math.Round((1.0 - ((double)d[n, m] / (double)System.Math.Max(n, m))) * 100.0, 2);
// return percentage;
return d[n, m];
}
-- SQL to actually create scalar function that calls CLR code
ALTER FUNCTION dbo.Levenshtein(@S1 nvarchar(max), @S2 nvarchar(max))
RETURNS INT as EXTERNAL NAME ClrUtils.StoredFunctions.Levenshtein
GO
-- CLR must be enabled for database
sp_configure 'clr enabled', 1
GO
RECONFIGURE
GO
2) 查询
select T1.Id1, T1.Column1, T2.Id2, T2.Column2
from Table1 T1
cross join Table2 T2
where EXISTS (
SELECT 1
FROM #T1Words T1W
JOIN #T2Words T2W ON [dbo].[Levenshtein](T2W.Word, T1W.Word) < 3 -- T2W.Word = T1W.Word
WHERE T1W.Id1 = T1.Id1
AND T2W.Id2 = T2.Id2
)
当然，您必须根据可接受的差异设置阈值。