如何找到无向图的所有连通子图

Question

I need some help for a problem that i am struggling to solve.

Example table:

ID |Identifier1 | Identifier2 
---------------------------------
1  |      a     | c         
2  |      b     | f         
3  |      a     | g         
4  |      c     | h        
5  |      b     | j         
6  |      d     | f         
7  |      e     | k  
8  |      i     |          
9  |      l     | h    

I want to group identifiers that are related with each other between two columns and assign a unique group id.

Desired Output:

Identifier | Gr_ID    |    Gr.Members                 
---------------------------------------------------
a       |      1      |   (a,c,g,h,l)  
b       |      2      |   (b,d,f,j)       
c       |      1      |   (a,c,g,h,l)  
d       |      2      |   (b,d,f,j)       
e       |      3      |   (e,k)                 
f       |      2      |   (b,d,f,j)       
g       |      1      |   (a,c,g,h,l)  
h       |      1      |   (a,c,g,h,l)  
j       |      2      |   (b,d,f,j)       
k       |      3      |   (e,k)                 
l       |      1      |   (a,c,g,h,l)  
i       |      4      |   (i)  

Note:the column Gr.Members is not necessary, mostly is used for a clearer view.

So the definition for a group is: A row belongs to a group if it shares at least one identifier with at least one row of this group

But the group id has to be assigned to each identifier(selected by the union of the two columns) not to the row.

Any help on how to build a query to give the desired output?

Thank you.

---

Update: Below are some extra sample sets with their expected output.

---

Given table:

Identifier1 | Identifier2   
----------------------------
    a       |   f
    a       |   g
    a       |  NULL
    b       |   c
    b       |   a
    b       |   h
    b       |   j
    b       |  NULL
    b       |  NULL
    b       |   g
    c       |   k
    c       |   b
    d       |   l
    d       |   f
    d       |   g
    d       |   m
    d       |   a
    d       |  NULL
    d       |   a
    e       |   c
    e       |   b
    e       |  NULL

Expected output: all the records should belong to the same group with group ID = 1.

---

Given Table:

Identifier1 | Identifier2
--------------------------
a           |   a
b           |   b
c           |   a
c           |   b
c           |   c

Expected output: The records should be in the same group with group ID = 1.

Answer 1

Here is a variant that doesn't use cursor, but uses a single recursive query.

Essentially, it treats the data as edges in a graph and traverses recursively all edges of the graph, stopping when the loop is detected. Then it puts all found loops in groups and gives each group a number.

See the detailed explanations of how it works below. I recommend you to run the query CTE-by-CTE and examine each intermediate result to understand what it does.

Sample 1

DECLARE @T TABLE (ID int, Ident1 char(1), Ident2 char(1));
INSERT INTO @T (ID, Ident1, Ident2) VALUES
(1, 'a', 'a'),
(2, 'b', 'b'),
(3, 'c', 'a'),
(4, 'c', 'b'),
(5, 'c', 'c');

Sample 2

I added one more row with z value to have multiple rows with unpaired values.

DECLARE @T TABLE (ID int, Ident1 char(1), Ident2 char(1));
INSERT INTO @T (ID, Ident1, Ident2) VALUES
(1, 'a', 'a'),
(1, 'a', 'c'),
(2, 'b', 'f'),
(3, 'a', 'g'),
(4, 'c', 'h'),
(5, 'b', 'j'),
(6, 'd', 'f'),
(7, 'e', 'k'),
(8, 'i', NULL),
(88, 'z', 'z'),
(9, 'l', 'h');

Sample 3

DECLARE @T TABLE (ID int, Ident1 char(1), Ident2 char(1));
INSERT INTO @T (ID, Ident1, Ident2) VALUES
(1, 'a', 'f'),
(2, 'a', 'g'),
(3, 'a', NULL),
(4, 'b', 'c'),
(5, 'b', 'a'),
(6, 'b', 'h'),
(7, 'b', 'j'),
(8, 'b', NULL),
(9, 'b', NULL),
(10, 'b', 'g'),
(11, 'c', 'k'),
(12, 'c', 'b'),
(13, 'd', 'l'),
(14, 'd', 'f'),
(15, 'd', 'g'),
(16, 'd', 'm'),
(17, 'd', 'a'),
(18, 'd', NULL),
(19, 'd', 'a'),
(20, 'e', 'c'),
(21, 'e', 'b'),
(22, 'e', NULL);

Query

WITH
CTE_Idents
AS
(
    SELECT Ident1 AS Ident
    FROM @T

    UNION

    SELECT Ident2 AS Ident
    FROM @T
)
,CTE_Pairs
AS
(
    SELECT Ident1, Ident2
    FROM @T
    WHERE Ident1 <> Ident2

    UNION

    SELECT Ident2 AS Ident1, Ident1 AS Ident2
    FROM @T
    WHERE Ident1 <> Ident2
)
,CTE_Recursive
AS
(
    SELECT
        CAST(CTE_Idents.Ident AS varchar(8000)) AS AnchorIdent 
        , Ident1
        , Ident2
        , CAST(',' + Ident1 + ',' + Ident2 + ',' AS varchar(8000)) AS IdentPath
        , 1 AS Lvl
    FROM 
        CTE_Pairs
        INNER JOIN CTE_Idents ON CTE_Idents.Ident = CTE_Pairs.Ident1

    UNION ALL

    SELECT 
        CTE_Recursive.AnchorIdent 
        , CTE_Pairs.Ident1
        , CTE_Pairs.Ident2
        , CAST(CTE_Recursive.IdentPath + CTE_Pairs.Ident2 + ',' AS varchar(8000)) AS IdentPath
        , CTE_Recursive.Lvl + 1 AS Lvl
    FROM
        CTE_Pairs
        INNER JOIN CTE_Recursive ON CTE_Recursive.Ident2 = CTE_Pairs.Ident1
    WHERE
        CTE_Recursive.IdentPath NOT LIKE CAST('%,' + CTE_Pairs.Ident2 + ',%' AS varchar(8000))
)
,CTE_RecursionResult
AS
(
    SELECT AnchorIdent, Ident1, Ident2
    FROM CTE_Recursive
)
,CTE_CleanResult
AS
(
    SELECT AnchorIdent, Ident1 AS Ident
    FROM CTE_RecursionResult

    UNION

    SELECT AnchorIdent, Ident2 AS Ident
    FROM CTE_RecursionResult
)
SELECT
    CTE_Idents.Ident
    ,CASE WHEN CA_Data.XML_Value IS NULL 
    THEN CTE_Idents.Ident ELSE CA_Data.XML_Value END AS GroupMembers
    ,DENSE_RANK() OVER(ORDER BY 
        CASE WHEN CA_Data.XML_Value IS NULL 
        THEN CTE_Idents.Ident ELSE CA_Data.XML_Value END
    ) AS GroupID
FROM
    CTE_Idents
    CROSS APPLY
    (
        SELECT CTE_CleanResult.Ident+','
        FROM CTE_CleanResult
        WHERE CTE_CleanResult.AnchorIdent = CTE_Idents.Ident
        ORDER BY CTE_CleanResult.Ident FOR XML PATH(''), TYPE
    ) AS CA_XML(XML_Value)
    CROSS APPLY
    (
        SELECT CA_XML.XML_Value.value('.', 'NVARCHAR(MAX)')
    ) AS CA_Data(XML_Value)
WHERE
    CTE_Idents.Ident IS NOT NULL
ORDER BY Ident;

Result 1

+-------+--------------+---------+
| Ident | GroupMembers | GroupID |
+-------+--------------+---------+
| a     | a,b,c,       |       1 |
| b     | a,b,c,       |       1 |
| c     | a,b,c,       |       1 |
+-------+--------------+---------+

Result 2

+-------+--------------+---------+
| Ident | GroupMembers | GroupID |
+-------+--------------+---------+
| a     | a,c,g,h,l,   |       1 |
| b     | b,d,f,j,     |       2 |
| c     | a,c,g,h,l,   |       1 |
| d     | b,d,f,j,     |       2 |
| e     | e,k,         |       3 |
| f     | b,d,f,j,     |       2 |
| g     | a,c,g,h,l,   |       1 |
| h     | a,c,g,h,l,   |       1 |
| i     | i            |       4 |
| j     | b,d,f,j,     |       2 |
| k     | e,k,         |       3 |
| l     | a,c,g,h,l,   |       1 |
| z     | z            |       5 |
+-------+--------------+---------+

Result 3

+-------+--------------------------+---------+
| Ident |       GroupMembers       | GroupID |
+-------+--------------------------+---------+
| a     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| b     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| c     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| d     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| e     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| f     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| g     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| h     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| j     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| k     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| l     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
| m     | a,b,c,d,e,f,g,h,j,k,l,m, |       1 |
+-------+--------------------------+---------+

How it works

I'll use the second set of sample data for this explanation.

CTE_Idents

CTE_Idents gives the list of all Identifiers that appear in both Ident1 and Ident2 columns. Since they can appear in any order we UNION both columns together. UNION also removes any duplicates.

+-------+
| Ident |
+-------+
| NULL  |
| a     |
| b     |
| c     |
| d     |
| e     |
| f     |
| g     |
| h     |
| i     |
| j     |
| k     |
| l     |
| z     |
+-------+

CTE_Pairs

CTE_Pairs gives the list of all edges of the graph in both directions. Again, UNION is used to remove any duplicates.

+--------+--------+
| Ident1 | Ident2 |
+--------+--------+
| a      | c      |
| a      | g      |
| b      | f      |
| b      | j      |
| c      | a      |
| c      | h      |
| d      | f      |
| e      | k      |
| f      | b      |
| f      | d      |
| g      | a      |
| h      | c      |
| h      | l      |
| j      | b      |
| k      | e      |
| l      | h      |
+--------+--------+

CTE_Recursive

CTE_Recursive is the main part of the query that recursively traverses the graph starting from each unique Identifier. These starting rows are produced by the first part of UNION ALL . The second part of UNION ALL recursively joins to itself linking Ident2 to Ident1 . Since we pre-made CTE_Pairs with all edges written in both directions, we can always link only Ident2 to Ident1 and we'll get all paths in the graph. At the same time the query builds IdentPath - a string of comma-delimited Identifiers that have been traversed so far. It is used in the WHERE filter:

CTE_Recursive.IdentPath NOT LIKE CAST('%,' + CTE_Pairs.Ident2 + ',%' AS varchar(8000))

As soon as we come across the Identifier that had been included in the Path before, the recursion stops as the list of connected nodes is exhausted. AnchorIdent is the starting Identifier for the recursion, it will be used later to group results. Lvl is not really used, I included it for better understanding of what is going on.

+-------------+--------+--------+-------------+-----+
| AnchorIdent | Ident1 | Ident2 |  IdentPath  | Lvl |
+-------------+--------+--------+-------------+-----+
| a           | a      | c      | ,a,c,       |   1 |
| a           | a      | g      | ,a,g,       |   1 |
| b           | b      | f      | ,b,f,       |   1 |
| b           | b      | j      | ,b,j,       |   1 |
| c           | c      | a      | ,c,a,       |   1 |
| c           | c      | h      | ,c,h,       |   1 |
| d           | d      | f      | ,d,f,       |   1 |
| e           | e      | k      | ,e,k,       |   1 |
| f           | f      | b      | ,f,b,       |   1 |
| f           | f      | d      | ,f,d,       |   1 |
| g           | g      | a      | ,g,a,       |   1 |
| h           | h      | c      | ,h,c,       |   1 |
| h           | h      | l      | ,h,l,       |   1 |
| j           | j      | b      | ,j,b,       |   1 |
| k           | k      | e      | ,k,e,       |   1 |
| l           | l      | h      | ,l,h,       |   1 |
| l           | h      | c      | ,l,h,c,     |   2 |
| l           | c      | a      | ,l,h,c,a,   |   3 |
| l           | a      | g      | ,l,h,c,a,g, |   4 |
| j           | b      | f      | ,j,b,f,     |   2 |
| j           | f      | d      | ,j,b,f,d,   |   3 |
| h           | c      | a      | ,h,c,a,     |   2 |
| h           | a      | g      | ,h,c,a,g,   |   3 |
| g           | a      | c      | ,g,a,c,     |   2 |
| g           | c      | h      | ,g,a,c,h,   |   3 |
| g           | h      | l      | ,g,a,c,h,l, |   4 |
| f           | b      | j      | ,f,b,j,     |   2 |
| d           | f      | b      | ,d,f,b,     |   2 |
| d           | b      | j      | ,d,f,b,j,   |   3 |
| c           | h      | l      | ,c,h,l,     |   2 |
| c           | a      | g      | ,c,a,g,     |   2 |
| b           | f      | d      | ,b,f,d,     |   2 |
| a           | c      | h      | ,a,c,h,     |   2 |
| a           | h      | l      | ,a,c,h,l,   |   3 |
+-------------+--------+--------+-------------+-----+

CTE_CleanResult

CTE_CleanResult leaves only relevant parts from CTE_Recursive and again merges both Ident1 and Ident2 using UNION .

+-------------+-------+
| AnchorIdent | Ident |
+-------------+-------+
| a           | a     |
| a           | c     |
| a           | g     |
| a           | h     |
| a           | l     |
| b           | b     |
| b           | d     |
| b           | f     |
| b           | j     |
| c           | a     |
| c           | c     |
| c           | g     |
| c           | h     |
| c           | l     |
| d           | b     |
| d           | d     |
| d           | f     |
| d           | j     |
| e           | e     |
| e           | k     |
| f           | b     |
| f           | d     |
| f           | f     |
| f           | j     |
| g           | a     |
| g           | c     |
| g           | g     |
| g           | h     |
| g           | l     |
| h           | a     |
| h           | c     |
| h           | g     |
| h           | h     |
| h           | l     |
| j           | b     |
| j           | d     |
| j           | f     |
| j           | j     |
| k           | e     |
| k           | k     |
| l           | a     |
| l           | c     |
| l           | g     |
| l           | h     |
| l           | l     |
+-------------+-------+

Final SELECT

Now we need to build a string of comma-separated Ident values for each AnchorIdent . CROSS APPLY with FOR XML does it. DENSE_RANK() calculates the GroupID numbers for each AnchorIdent .

Answer 2

This script produces the outputs for test sets 1, 2 and 3 as required. Notes on the algorithm as comments in the script.

Be aware:

• This algorithm destroys the input set. In the script the input set is #tree . So using this script requires inserting the source data into #tree
• This algorithm does not work for NULL values for nodes. Replace NULL values with CHAR(0) when inserting into #tree using ISNULL(source_col,CHAR(0)) to circumvent this shortcoming. When selecting from the final result, replace CHAR(0) with NULL using NULLIF(node,CHAR(0)) .

Note that the answer using recursive CTEs is more elegant in that it is a single SQL statement, but for large input sets using recursive CTEs may give abysmal execution time (see this comment on that answer). The solution as described below, while more convoluted, should run much faster for large input sets.

---

SET NOCOUNT ON;

CREATE TABLE #tree(node_l CHAR(1),node_r CHAR(1));
CREATE NONCLUSTERED INDEX NIX_tree_node_l ON #tree(node_l)INCLUDE(node_r); -- covering indices to speed up lookup
CREATE NONCLUSTERED INDEX NIX_tree_node_r ON #tree(node_r)INCLUDE(node_l);
INSERT INTO #tree(node_l,node_r) VALUES
    ('a','c'),('b','f'),('a','g'),('c','h'),('b','j'),('d','f'),('e','k'),('i','i'),('l','h'); -- test set 1
    --('a','f'),('a','g'),(CHAR(0),'a'),('b','c'),('b','a'),('b','h'),('b','j'),('b',CHAR(0)),('b',CHAR(0)),('b','g'),('c','k'),('c','b'),('d','l'),('d','f'),('d','g'),('d','m'),('d','a'),('d',CHAR(0)),('d','a'),('e','c'),('e','b'),('e',CHAR(0)); -- test set 2
    --('a','a'),('b','b'),('c','a'),('c','b'),('c','c'); -- test set 3 

CREATE TABLE #sets(node CHAR(1) PRIMARY KEY,group_id INT); -- nodes with group id assigned
CREATE TABLE #visitor_queue(node CHAR(1)); -- contains nodes to visit
CREATE TABLE #visited_nodes(node CHAR(1) PRIMARY KEY CLUSTERED WITH(IGNORE_DUP_KEY=ON)); -- nodes visited for nodes on the queue; ignore duplicate nodes when inserted
CREATE TABLE #visitor_ctx(node_l CHAR(1),node_r CHAR(1)); -- context table, contains deleted nodes as they are visited from #tree

DECLARE @last_created_group_id INT=0;

-- Notes:
-- 1. This algorithm is destructive in its input set, ie #tree will be empty at the end of this procedure
-- 2. This algorithm does not accept NULL values. Populate #tree with CHAR(0) for NULL values (using ISNULL(source_col,CHAR(0)), or COALESCE(source_col,CHAR(0)))
-- 3. When selecting from #sets, to regain the original NULL values use NULLIF(node,CHAR(0))
WHILE EXISTS(SELECT*FROM #tree)
BEGIN
    TRUNCATE TABLE #visited_nodes;
    TRUNCATE TABLE #visitor_ctx;

    -- push first nodes onto the queue (via #visitor_ctx -> #visitor_queue)
    DELETE TOP (1) t
    OUTPUT deleted.node_l,deleted.node_r INTO #visitor_ctx(node_l,node_r)
    FROM #tree AS t;

    INSERT INTO #visitor_queue(node) SELECT node_l FROM #visitor_ctx UNION SELECT node_r FROM #visitor_ctx; -- UNION to filter when node_l equals node_r
    INSERT INTO #visited_nodes(node) SELECT node FROM #visitor_queue; -- keep track of nodes visited

    -- work down the queue by visiting linked nodes in #tree; nodes are deleted as they are visited
    WHILE EXISTS(SELECT*FROM #visitor_queue)
    BEGIN
        TRUNCATE TABLE #visitor_ctx;

        -- pop_front for node on the stack (via #visitor_ctx -> @node)
        DELETE TOP (1) s
        OUTPUT deleted.node INTO #visitor_ctx(node_l)
        FROM #visitor_queue AS s;

        DECLARE @node CHAR(1)=(SELECT node_l FROM #visitor_ctx); 
        TRUNCATE TABLE #visitor_ctx;

        -- visit nodes in #tree where node_l or node_r equal target @node; 
        -- delete visited nodes from #tree, output to #visitor_ctx
        DELETE t
        OUTPUT deleted.node_l,deleted.node_r INTO #visitor_ctx(node_l,node_r)
        FROM #tree AS t
        WHERE t.node_l=@node OR t.node_r=@node;

        -- insert visited nodes in the queue that haven't been visited before
        INSERT INTO #visitor_queue(node) 
        (SELECT node_l FROM #visitor_ctx UNION SELECT node_r FROM #visitor_ctx) EXCEPT (SELECT node FROM #visited_nodes);

        -- keep track of visited nodes (duplicates are ignored by the IGNORE_DUP_KEY option for the PK)
        INSERT INTO #visited_nodes(node)
        SELECT node_l FROM #visitor_ctx UNION SELECT node_r FROM #visitor_ctx;
    END

    SET @last_created_group_id+=1; -- create new group id

    -- insert group into #sets
    INSERT INTO #sets(group_id,node)
    SELECT group_id=@last_created_group_id,node 
    FROM #visited_nodes;
END

SELECT node=NULLIF(node,CHAR(0)),group_id FROM #sets ORDER BY node; -- nodes with their assigned group id

SELECT g.group_id,m.members  -- groups with their members
FROM
    (SELECT DISTINCT group_id FROM #sets) AS g
    CROSS APPLY (
        SELECT members=STUFF((
                SELECT ','+ISNULL(CAST(NULLIF(si.node,CHAR(0)) AS VARCHAR(4)),'NULL')
                FROM #sets AS si 
                WHERE si.group_id=g.group_id
                FOR XML PATH('')
            ),1,1,'')
     ) AS m
ORDER BY g.group_id;

DROP TABLE #visitor_queue;
DROP TABLE #visited_nodes;
DROP TABLE #visitor_ctx;
DROP TABLE #sets;
DROP TABLE #tree;

---

Output for set 1:

+------+----------+
| node | group_id |
+------+----------+
| a    |        1 |
| b    |        2 |
| c    |        1 |
| d    |        2 |
| e    |        4 |
| f    |        2 |
| g    |        1 |
| h    |        1 |
| i    |        3 |
| j    |        2 |
| k    |        4 |
| l    |        1 |
+------+----------+

---

Output for set 2:

+------+----------+
| node | group_id |
+------+----------+
| NULL |        1 |
| a    |        1 |
| b    |        1 |
| c    |        1 |
| d    |        1 |
| e    |        1 |
| f    |        1 |
| g    |        1 |
| h    |        1 |
| j    |        1 |
| k    |        1 |
| l    |        1 |
| m    |        1 |
+------+----------+

---

Output for set 3:

+------+----------+
| node | group_id |
+------+----------+
| a    |        1 |
| b    |        1 |
| c    |        1 |
+------+----------+

Answer 3

My suggestion is to use stored procedure with cursor. It is easy to implement and relatively fast. Only two steps:

• First, create sp_GetIdentByGroup
• Second, INSERT related identifiers in a temporary table #PairIds and call sp [dbo].[sp_GetIdentByGroup] and you will get Identifiers with the same GroupID as related items.

Query:

CREATE TABLE #PairIds
(
    Ident1 VARCHAR(10),
    Ident2 VARCHAR(10)
)

INSERT INTO #PairIds
VALUES ('a', 'c'),
('b', 'f'),
('a', 'g'),
('c', 'h'),
('b', 'j'),
('d', 'f'),
('e', 'k'),
('l', 'h')


exec [dbo].[sp_GetIdentByGroup]

Result:

Ident | GroupID --------------------------------------------------- a | 1 | b | 2 | c | 1 | d | 2 | e | 3 | f | 2 | g | 1 | h | 1 | j | 2 | k | 3 | l | 1 |

Code for creating stored procedure:

CREATE PROCEDURE [dbo].[sp_GetIdentByGroup]
AS
BEGIN

    DECLARE @message VARCHAR(70);
    DECLARE @IdentInput1 varchar(20)
    DECLARE @IdentInput2 varchar(20)
    DECLARE @Counter INT
    DECLARE @Group1 INT
    DECLARE @Group2 INT
    DECLARE @Ident varchar(20)
    DECLARE @IdentCheck1 varchar(20)
    DECLARE @IdentCheck2 varchar(20)

    SET @Counter = 1

    DECLARE @IdentByGroupCursor TABLE (
    Ident varchar(20) UNIQUE CLUSTERED,
    GroupID INT  
    );


    -- Use a cursor to select your data, which enables SQL Server to extract
    -- the data from your local table to the variables.
    declare ins_cursor cursor for
    select  Ident1, Ident2 from #PairIds



    open ins_cursor
    fetch next from ins_cursor into @IdentInput1, @IdentInput2 -- At this point, the data from the first row
     -- is in your local variables.

    -- Move through the table with the @@FETCH_STATUS=0
    WHILE @@FETCH_STATUS=0
    BEGIN

        SET @Group1 = null
        SET @Group2 = null

        SELECT TOP 1  @Group1 = GroupID,  @IdentCheck1 = Ident
        FROM @IdentByGroupCursor
        WHERE Ident in (@IdentInput1)

        SELECT TOP 1  @Group2 = GroupID,  @IdentCheck2 = Ident
        FROM @IdentByGroupCursor
        WHERE Ident in (@IdentInput2)

        IF (@Group1 IS NOT NULL AND @Group2 IS NOT NULL)
        BEGIN
            IF @Group1 > @Group2
            BEGIN
                UPDATE @IdentByGroupCursor
                SET GroupID = @Group2
                WHERE
                GroupID = @Group1
            END

            IF @Group2 > @Group1
            BEGIN
                UPDATE @IdentByGroupCursor
                SET GroupID = @Group1
                WHERE
                GroupID = @Group2
            END
        END
        ELSE IF @Group1 IS NOT NULL
        BEGIN
            UPDATE @IdentByGroupCursor
            SET GroupID = @Group1
            WHERE
            Ident IN (@IdentInput1)
        END
        ELSE IF @Group2 IS NOT NULL
        BEGIN
            UPDATE @IdentByGroupCursor
            SET GroupID = @Group2
            WHERE
            Ident IN (@IdentInput2)
        END

        IF (@Group1 IS NOT NULL AND @Group2 IS NOT NULL)
        BEGIN
            IF @Group1 > @Group2
            BEGIN
                UPDATE @IdentByGroupCursor
                SET GroupID = @Group2
                WHERE
                GroupID = @Group1
            END

            IF @Group2 > @Group1
            BEGIN
                UPDATE @IdentByGroupCursor
                SET GroupID = @Group1
                WHERE
                GroupID = @Group2
            END

        END

            IF @Group1 IS NULL
            BEGIN

                INSERT INTO @IdentByGroupCursor (Ident, GroupID)
                VALUES (@IdentInput1, ISNULL(@Group2, @Counter))

            END

            IF @Group2 IS NULL
            BEGIN
                INSERT INTO @IdentByGroupCursor (Ident, GroupID)
                VALUES (@IdentInput2, ISNULL(@Group1, @COunter))
            END

            IF (@Group1 IS NULL OR @Group2 IS NULL)
            BEGIN

            SET @COunter =  @COunter  +1

        END

        -- Once the execution has taken place, you fetch the next row of data from your local table.
        fetch next from ins_cursor into @IdentInput1, @IdentInput2

    End


    -- When all the rows have inserted you must close and deallocate the cursor.
    -- Failure to do this will not let you re-use the cursor.    
    close ins_cursor
    deallocate ins_cursor


    SELECT Ident ,DENSE_RANK() OVER( ORDER BY GroupID ASC) AS GroupID
    FROM @IdentByGroupCursor
    ORDER BY Ident

END
GO

Sp_GetIdentByGroup has an index for speed and with the use of a cursor, it prepares desired result set. The stored procedure expects #PairIds table to exist.
More information on SQL How to group identifiers that are related with each other in specific groups .

Answer 4

sp_GetIdentByGroup is fantastic approch I was searching for few days similar solution using CTE functions but they were too slow.Like for example 20 record we done in 5 sec, 30 records in 1:40 min and 35 was running for ages.

Your procedure managed to rank 150 item is group with split of the seconds. Thanks!