T-SQL - What's the most efficient way to loop through a table until a condition is met

You should try to avoid loops generally. They are normally less efficient than set based solutions as well as less readable.

The below should be pretty efficient.

Even more so if the name and weight columns could be INCLUDE-d in the index to avoid the key lookups.

It can scan the unique index in order of turn and calculate the running total of the Weight column - then use LEAD with the same ordering criteria to see what the running total in the next row will be.

As soon as it finds the first row where this exceeds 1000 or is NULL (indicating there is no next row) then it can stop the scan.

WITH T1
     AS (SELECT *,
                SUM(Weight) OVER (ORDER BY turn ROWS UNBOUNDED PRECEDING) AS cume_weight
         FROM   [dbo].[line]),
     T2
     AS (SELECT LEAD(cume_weight) OVER (ORDER BY turn) AS next_cume_weight,
                *
         FROM   T1)
SELECT TOP 1 name
FROM   T2
WHERE  next_cume_weight > 1000
        OR next_cume_weight IS NULL
ORDER  BY turn

Execution Plan

enter image description here

In practice it seems to read a few rows ahead of where is strictly necessary - it looks like each window spool/stream aggregate pair causes two additional rows to be read.

For the sample data in the question ideally it would only need to read two rows from the index scan but in reality it reads 6 but this is not a significant efficiency issue and it does not degrade as more rows are added to the table (as in this demo)

For those interested in this issue an image with the rows output by each operator (as shown by the query_trace_column_values extended event) is below, the rows are output in row_id order (starting at 47 for the first row read by the index scan and finishing at 113 for the TOP)

Click the image below to make it larger or alternatively see the animated version to make the flow easier to follow.

Pausing the animation at the point where the Right hand stream aggregate has emitted its first row (for gary - turn = 1). It seems apparent that it was waiting to receive its first row with a different WindowCount (for Jo - turn = 2). And the window spool doesn't release the first "Jo" row until it has read the next row with a different turn (for thomas - turn = 3)

So the window spool and stream aggregate both cause an additional row to be read and there are four of these in the plan - hence 4 additional rows.

enter image description here

An explanation of the columns shown in the above follows (based on info here)

  • NodeName: Index Scan, NodeId: 15, ColumnName: id base table column covered by index
  • NodeName: Index Scan, NodeId: 15, ColumnName: turn base table column covered by index
  • NodeName: Clustered Index Seek, NodeId: 17, ColumnName: weight base table column retrieved from lookup
  • NodeName: Clustered Index Seek, NodeId: 17, ColumnName: name base table column retrieved from lookup
  • NodeName: Segment, NodeId: 13, ColumnName: Segment1010 Returns 1 at start of new group or null otherwise. As no Partition By in the SUM only the first row gets 1
  • NodeName: Sequence Project, NodeId: 12, ColumnName: RowNumber1009 row_number() within group indicated by Segment1010 flag. As all rows are in the same group this is ascending integers from 1 to 6. Would be used for filtering right frame rows in cases like rows between 5 preceding and 2 following. (or as for LEAD later)
  • NodeName: Segment, NodeId: 11, ColumnName: Segment1011 Returns 1 at start of new group or null otherwise. As no Partition By in the SUM only the first row gets 1 (Same as Segment1010)
  • NodeName: Window Spool, NodeId: 10, ColumnName: WindowCount1012 Attribute that groups together rows belonging to a window frame. This window spool is using the "fast track" case for UNBOUNDED PRECEDING. Where it emits two rows per source row. One with the cumulative values and one with the detail values. Though there is no visible difference in the rows exposed by query_trace_column_values I assume that cumulative columns are there in reality.
  • NodeName: Stream Aggregate, NodeId: 9, ColumnName: Expr1004 Count(*) grouped by WindowCount1012 according to plan but actually a running count
  • NodeName: Stream Aggregate, NodeId: 9, ColumnName: Expr1005 SUM(weight) grouped by WindowCount1012 according to plan but actually the running sum of weight (i.e. cume_weight)
  • NodeName: Segment, NodeId: 7, ColumnName: Expr1002 CASE WHEN [Expr1004]=(0) THEN NULL ELSE [Expr1005] END - Don't see how COUNT(*) can be 0 so will always be running sum (cume_weight)
  • NodeName: Segment, NodeId: 7, ColumnName: Segment1013 No partition by on the LEAD so first row gets 1. All remaining get null
  • NodeName: Sequence Project, NodeId: 6, ColumnName: RowNumber1006 row_number() within group indicated by Segment1013 flag. As all rows are in the same group this is ascending integers from 1 to 4
  • NodeName: Segment, NodeId: 4, ColumnName: BottomRowNumber1008 RowNumber1006 + 1 as the LEAD requires the single next row
  • NodeName: Segment, NodeId: 4, ColumnName: TopRowNumber1007 RowNumber1006 + 1 as the LEAD requires the single next row
  • NodeName: Segment, NodeId: 4, ColumnName: Segment1014 No partition by on the LEAD so first row gets 1. All remaining get null
  • NodeName: Window Spool, NodeId: 3, ColumnName: WindowCount1015 Attribute that groups together rows belonging to a window frame using the previous row numbers. The window frame for LEAD has max 2 rows (the current one and the next one)
  • NodeName: Stream Aggregate, NodeId: 2, ColumnName: Expr1003 LAST_VALUE([Expr1002]) for the LEAD(cume_weight)

Just as a curiosity (since the question states T-SQL) it is also possible to solve this problem efficiently using SQLCLR.

The idea is to read rows one at a time in turn order until the weight exceeds 1000 (or we run out of rows), then to return the last name read.

The source code is:

using Microsoft.SqlServer.Server;
using System.Data;
using System.Data.SqlClient;
using System.Data.SqlTypes;

public partial class UserDefinedFunctions
{
    [SqlFunction(DataAccess = DataAccessKind.Read,
        SystemDataAccess = SystemDataAccessKind.None,
        IsDeterministic = true, IsPrecise = true)]
    [return: SqlFacet(IsFixedLength = false, IsNullable = true, MaxSize = 255)]
    public static SqlString Elevator()
    {
        const string query =
            @"SELECT L.[name], L.[weight]
            FROM dbo.line AS L
            ORDER BY L.turn;";

        using (var con = new SqlConnection("context connection = true"))
        {
            con.Open();
            using (var cmd = new SqlCommand(query, con))
            {
                var rdr = cmd.ExecuteReader(CommandBehavior.SingleResult);
                var name = SqlString.Null;
                var total = 0;

                while (rdr.Read() && (total += rdr.GetInt32(1)) <= 1000)
                {
                    name = rdr.GetSqlString(0);
                }
                return name;
            }
        }
    }
}

The compiled assembly and T-SQL function:

CREATE ASSEMBLY Elevator AUTHORIZATION [dbo]
FROM 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WITH PERMISSION_SET = SAFE;
GO
CREATE FUNCTION dbo.Elevator ()
RETURNS nvarchar(255)
AS EXTERNAL NAME Elevator.UserDefinedFunctions.Elevator;

Getting the result:

SELECT dbo.Elevator();

Tags:

Sql Server

T Sql

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