The ‘FIFO Stock Inventory’ SQL Problem

Question

Phil Factor SQL Speed Phreak Competition: No 2

alt text

This competition is now over, but the winner, Dave, got an Amazon Voucher for $60, and the privilege of being able to display the 'Phil Factor SQL Speed Phreak' award on their own site

It was quite a struggle with some close competition from many of those who participated in this competition. However, Dave came up with a clever solution that produced an FIFO calculation from a million rows in a just a few seconds. The third Phil Factor Speed Phreak competition will soon be held on here. Watch out!

(here is the original preamble.)

This competition is to calculate current items in stock and current stock value in FIFO order.
I'll tell you the business rules for the algorithm and provide a sample cursor-based routine that generates the correct result, but slowly (about 40 minutes).

I have seen many different algorithms to do this and most of them involve a cursor. Can it be done more quickly without, or even with, a cursor? In other words, what is the fastest way in SQL Server (any version) to provide this stock inventory report?
It is a reasonable request. We have a stock transaction list (1,000,001 records, 17.6MB zipped) with 15,002 unique articles and we need to do a stock inventory report that gives the current breakdown of the ArticleID, the number of items in stock and the current stock value according to FIFO rules. The list should be in ArticleID order. The sample stock transaction list will include two running totals so you can check the results of your routine. They are NOT part of the competition, and you are not allowed to use them in your calculation.

Beware that the sample file includes the two extra columns; CurrentItems (INT) and CurrentValue (MONEY) !
If you want a smaller subset to test on, import all records and remove all articles but two or three. These are the samples for which all suggestions will be measured with.

The table is in this form (simplified from the way we'd do it in a real system of course).
In this made-up but realistic problem, you have an existing table and database design which you can’t do anything about. (we can all relate to that!) You have an existing cursor-based solution that is taking several minutes to run. (Yes, we all relate to that). The database is performing badly, and you need to take effective steps to remedy this. The only thing you can do is to come up with a better-performing routine. Redesigning the database isn’t an option very often, in the real world, because this requires team sign-in. This is a competition based on the real, sometimes imperfect, world: not an exposition of database design. The point is that we are faced with designs like this and we have to heal them. The competition is all about making stuff go faster.

CREATE TABLE    dbo.Stock
                (
                    StockID INT IDENTITY(1, 1) NOT NULL,
                    ArticleID SMALLINT NOT NULL,
                    TranDate DATETIME NOT NULL,
                    TranCode VARCHAR(3) NOT NULL,
                    Items INT NOT NULL,
                    Price MONEY NULL,
                    CONSTRAINT [PK_Stock] PRIMARY KEY CLUSTERED 
                    (
                        StockID ASC
                    )
                )  

CREATE NONCLUSTERED INDEX IX_Input ON dbo.Stock (TranCode, ArticleID)
--INCLUDE (TranDate, Items, Price) -- Remove comment for SQL Server 2005 and later
--WHERE TranCode IN ('IN', 'RET')   -- Remove comment for SQL Server 2008

CREATE NONCLUSTERED INDEX IX_Output ON dbo.Stock (TranCode, ArticleID)
-- INCLUDE (TranDate, Items) -- Remove comment for SQL Server 2005 and later
--WHERE TranCode = 'OUT'  -- Remove comment for SQL Server 2008

You are welcome to change the two nonclustered indexes to suit your solution. You can download the complete sample data here. I have an idea of my own of the way to do this but I don’t know if it is the fastest.

Explanation of FIFO rules (example, abbreviated)

StockID ArticleID TranDate TranCode Items  Price CurrentItems CurrentValue
   4567     10000 10:45:07 IN         738 245.94          738   181,503.72
  21628     10000 12:05:25 OUT        600                 138    33,939.72
  22571     10000 14:39:27 IN          62 199.95          200    46,336.62
  30263     10000 16:14:13 OUT        165                  35     6,998.25
  42090     10000 18:18:58 RET          5                  40     7,998.00
  58143     10000 20:18:54 IN         500 135.91          540    75,953.00

a) First IN add 738 items (each $245.94) to the stock, for a total of $181,503.72
b) Then we take out 600 items (each 245.94) from the stock, leaving a total of $33,939.72
c) Then we insert 62 items (each 199.95) to the stock, for a total of $46,336.62
d) Then we take out 165 items (138 each 245.94 and 27 each 199.95), leaving a total of $6,998.25
e) Then we return 5 items. We can’t track at which price we took them out; so all returns are priced at the price of the latest ones inserted before the return. Even if there should be items left for the price of 245.94, the returned items are valued for 199.95. After the return, the current stock value is $7,998.00
f) The final insert adds $67,995.00 to the stock value, for a total of $75,953.00

As mentioned before, the CurrentItems and CurrentValue columns in the sample data are only included for you to validate your routines.

Here are some guidelines for your entries:

1) Include a header in your suggestion. Make sure your name and date is present.
2) Include an edition number. First edition is 1. If you later improve your current suggestion post it again as version 2. Example: “Peso 1” and if improved, “Peso 1b”, “Peso 1c” etc.
3) If you are trying a new algorithm, change the edition to “Peso 2”. If you improve this algorithm, change the version to “Peso 2b”, “Peso 2c” etc. This will save Phil hours of work in the test harness!
4) If you create a temp table, make sure you delete it in the script.
5) Keep the order of columns in output as ArticleID, CurrentItems, CurrentValue

I will allow you to use an existing tally number table (make sure it starts with 0). You can use any kind of object for this competition, except SQLCLR. If you are using a fixed tally number table, it has to be named dbo.TallyNumbers and the column named Number.
The time taken for their creation will not be included in the timings. The time measured is the “Main” script/procedure. If you want to call sub-procedures, go ahead.

The winner will be amongst the tied fastest entrants (generally there is a group of these) and it will be the one with the highest number of votes. We'll announce the winner in three week's time on 16th November.

For a starter, here is a common cursor based solution that you will find in production in many places.

CREATE TABLE    #Work
                (
                    RowID INT IDENTITY(1, 1) PRIMARY KEY CLUSTERED,
                    Price MONEY
                )  

DECLARE @ArticleID INT = 1,
        @PrevID INT = 0,
        @TranCode VARCHAR(3),
        @Items INT,
        @Price MONEY,
        @Loop INT = 0,
        @StockID INT,
        @LatestPrice MONEY,
        @Total INT = (SELECT COUNT(*) FROM dbo.Stock)

DECLARE curYak CURSOR FORWARD_ONLY FOR
                SELECT      ArticleID,
                            TranCode,
                            Items,
                            Price,
                            StockID
                FROM        dbo.Stock
                ORDER BY    ArticleID,
                            TranDate

OPEN    curYak

FETCH   NEXT
FROM    curYak
INTO    @ArticleID,
        @TranCode,
        @Items,
        @Price,
        @StockID

WHILE @@FETCH_STATUS = 0
    BEGIN
        IF @ArticleID > @PrevID
            BEGIN
                TRUNCATE TABLE  #Work

                SET @LatestPrice = NULL
            END

        IF @TranCode = 'IN'
            BEGIN
                INSERT  #Work
                        (
                            Price
                        )
                SELECT  @Price
                FROM    dbo.TallyNumbers
                WHERE   Number < @Items

                SET     @LatestPrice = @Price
            END

        IF @TranCode = 'RET'
            INSERT  #Work
                    (
                        Price
                    )
            SELECT  @LatestPrice
            FROM    dbo.TallyNumbers
            WHERE   Number < @Items

        IF @TranCode = 'OUT'
            DELETE  w
            FROM    (
                        SELECT      TOP(@Items)
                                    RowID
                        FROM        #Work
                        ORDER BY    RowID
                    ) AS w

        UPDATE      s
        SET         s.CurrentItems = w.CurrentItems,
                    s.CurrentValue = COALESCE(w.CurrentValue, 0)
        FROM        dbo.Stock AS s
        INNER JOIN  (
                        SELECT  COUNT(*) AS CurrentItems,
                                SUM(Price) AS CurrentValue
                        FROM    #Work
                    ) AS w ON s.StockID = @StockID

        SELECT  @PrevID = @ArticleID,
                @Loop += 1

        IF @Loop % 1000 = 0
            RAISERROR('Now updating record %d of %d.', 10, 1, @Loop, @Total) WITH NOWAIT

        FETCH   NEXT
        FROM    curYak
        INTO    @ArticleID,
                @TranCode,
                @Items,
                @Price,
                @StockID
    END

DROP TABLE  #Work

CLOSE       curYak
DEALLOCATE  curYak

The above is already done. Here is the code to produce the final resultset.

SELECT      ArticleID,
            CurrentItems,
            CurrentValue
FROM        (
                SELECT  ArticleID,
                        CurrentItems,
                        CurrentValue,
                        ROW_NUMBER() OVER (PARTITION BY ArticleID ORDER BY TranDate DESC) AS recID
                FROM    dbo.Stock
            ) AS d
WHERE       recID = 1
ORDER BY    ArticleID

Good luck to you all!

Peter Larsson

Answer 1

Dave Ballantyne - Phil Factor Challenge Entry 3.d

Peso had adding some index hints and shuffled a calculation to my initial 3.a. So this is 3.a(+) with comments

with 3.d doing the TotalStock sum in one operation shaves some more time off

“A problem well stated is a problem half solved” - Charles F. Kettering

Let us think about what has been asked within the challenge.

We have a warehouse which starts empty , the data contains the stock movements in (including returns) and out. The stock movements ALWAYS happen in a first in first out basis. With this we know that if the present stock level (sum(in's) - sum(out's) is 50 that will be the last 50 that have entered the warehouse. The key to this query is to efficiently find the cost of those 50 items.

    CREATE NONCLUSTERED INDEX [IX_Dave_General] ON [dbo].[Stock]
    (
            [ArticleID] ASC,
        	  [TranDate] DESC,
            [TranCode] ASC
    )
    INCLUDE ( [Items],
    [Price]) WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]

    GO
    CREATE NONCLUSTERED INDEX [IX_Dave_Items] ON [dbo].[Stock]
    (
            [ArticleID] ASC,
            [TranDate] ASC
    )
    INCLUDE ( [Items])
    WHERE ([TranCode] IN ('IN', 'RET'))
    WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]

    GO

    CREATE NONCLUSTERED INDEX [IX_Dave_Price] ON [dbo].[Stock]
    (
            [ArticleID] ASC,
            [TranDate] ASC
    )
    INCLUDE ( [Price])
    WHERE ([TranCode]='IN')
    WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON, FILLFACTOR = 100) ON [PRIMARY]

    GO

   /* Sum up the ins and outs to calculate the remaining stock level */
;WITH cteStockSum 
AS      (

      SELECT  ArticleID,
            SUM(CASE  WHEN TranCode = 'OUT' THEN 0-Items
                      ELSE Items END) AS TotalStock
            FROM  dbo.Stock
      GROUP BY  ArticleID
), 
/* Perform a rolling balance ( in reverse order ) through the stock movements in */
cteReverseInSum
AS      (
   SELECT  s.ArticleID,
           s.TranDate,
           (
               SELECT SUM(i.Items)
                 FROM dbo.Stock AS i WITH (INDEX (IX_Dave_Items))
                WHERE i.ArticleID = s.ArticleID
                  AND i.TranCode IN ('IN', 'RET')
                  AND i.TranDate >= s.TranDate
           /*   SELECT SUM(i.Items)
                 FROM dbo.vwStockIn as i with (index (idxStockInArtTrans))
                WHERE i.ArticleID = s.ArticleID
                  AND i.TranDate >= s.TranDate*/

           ) AS RollingStock,
           s.Items AS ThisStock
     FROM  dbo.Stock AS s
    WHERE  s.TranCode IN ('IN', 'RET')

), 
/* Using the rolling balance above find the first stock movement in that meets (or exceeds) our required stock level */
/* and calculate how much stock is required from the earliest stock in */
cteWithLastTranDate
AS      (
  SELECT   w.ArticleID,
           w.TotalStock,
           LastPartialStock.TranDate,
           LastPartialStock.StockToUse,
           LastPartialStock.RunningTotal,
           w.TotalStock - LastPartialStock.RunningTotal + LastPartialStock.StockToUse AS UseThisStock

      FROM cteStockSum AS w
           CROSS APPLY  ( SELECT TOP(1)  
                                 z.TranDate,
                                 z.ThisStock AS StockToUse,
                                 z.RollingStock AS RunningTotal
                            FROM cteReverseInSum AS z
                           WHERE z.ArticleID = w.ArticleID
                             AND z.RollingStock >= w.TotalStock
                        ORDER BY z.TranDate DESC ) AS LastPartialStock

)
/*  Sum up the cost of 100% of the stock movements in after the returned stockid and
    for that stockid we need 'UseThisStock' items' */
SELECT y.ArticleID,
       y.TotalStock as CurrentItems ,
       SUM(CASE WHEN e.TranDate = y.TranDate THEN y.UseThisStock
                ELSE e.Items
                END * Price.Price) AS CurrentValue
  FROM cteWithLastTranDate AS y
 INNER JOIN  dbo.Stock AS e  WITH (INDEX (IX_Dave_Items)) 
    ON e.ArticleID = y.ArticleID
   AND e.TranDate >= y.TranDate
   AND e.TranCode IN ('IN', 'RET')
 CROSS APPLY  (
       /* Find the Price of the item in */
       SELECT TOP(1)        
              p.Price
         FROM dbo.Stock AS p WITH (INDEX (IX_Dave_Price))
        WHERE p.ArticleID = e.ArticleID
          AND p.TranDate <= e.TranDate
          AND p.TranCode = 'IN'
        ORDER BY p.TranDate DESC
      ) AS Price
GROUP BY  y.ArticleID,
          y.TotalStock
ORDER BY   y.ArticleID
go

Answer 2

0

What do you think?
Am I allowed to compete, since all rules are known?

Please comment here what you think.

answered Oct 23 '09 at 05:32 PM

Peso
1.6k ● 4 ● 6 ● 8

Wow, have I been there, Peso. It's probably Phil's call, but my feeling is NO. I say this knowing that I may be in your position too in the near future (hopefully :-)). The problem is that no matter how fair you are, sooner or later someone is going to feel cheated because you were both a competitor and the Question Asker (or worse, Tester/Judge). What I would recommend is just throwing you solution in at the end, in the final measurements, as an example non-competing entry. I.e., non-eligible to win.

Oct 23 '09 at 05:41 PM RBarryYoung

I respect that. If this is the consensus, I will post my set-based solution very last before deadline so that no-one can steal my thunder :-)

Oct 23 '09 at 05:51 PM Peso

Oh boy! Someone already voted this as an unhelpful post grin

Oct 23 '09 at 05:59 PM Peso

I think the series would be more fun if we disallow the current winner from entering, since it gives other people a chance! Actually, I think we should be allowed to steal Peso's thunder too at some point!

Oct 24 '09 at 05:23 AM Phil Factor

Well, I'm upvoting it, so they should cancel out, ;-)

Oct 24 '09 at 03:24 PM RBarryYoung

(comments are locked)

Answer 3

Here will the preliminary timings be presented. I write preliminary since Phil is (will be) away for a few days, so I will do the preliminary timings on a similar machine as Phil has.

Current standings

 1 - Dave 3d                       1.3 seconds
 2 - Dave 3c                       1.5 seconds
   - Matt 1a                       1.8 seconds (correct items, wrong value)
 3 - Dave 3b                       2.1 seconds
 4 - Gianluca 1a                   3   seconds
 5 - Steve 1a                      5   seconds
 6 - Gianluca 2a                   5   seconds
 7 - Scot 1                        6   seconds
 8 - Barry 2d                      7   seconds
   - Andriy 1a                     7   seconds (correct items, wrong value)
 9 - Herman 1d                     9   seconds
10 - Herman 1c                    12   seconds
   - Peso "Cursor"                12   seconds (not in competition)
11 - Barry 2c                     18   seconds
12 - Andriy 1c                    22   seconds
13 - Dave 2b                      26   seconds
   - Matt CLR                     44   seconds (not in competition) 
14 - Barry 2                      50   seconds   
15 - Dave 1b                      96   seconds
16 - Barry 1b                     97   seconds   
17 - Herman 1a                   172   seconds  
   - Article code             ~2,400   seconds (not in competition)

Answer 4

Well, I know this answer will be disqualified, but I thought it might be interesting to see how a CLR Type would help with this. Here is my code, which runs in about 45 seconds on my box. I also think the idea of a quirky update using a CLR type is funny!

CREATE ASSEMBLY [SqlClassLibrary]
AUTHORIZATION [dbo]
FROM
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WITH PERMISSION_SET = SAFE
GO
ALTER ASSEMBLY [SqlClassLibrary]
WITH VISIBILITY = ON
GO
CREATE TYPE [dbo].[StockStack]
EXTERNAL NAME [SqlClassLibrary].[StockStack]
GO
CREATE TABLE #StockWork (ArticleID [int] NOT NULL, TranDate [datetime] NOT NULL, OpCode [tinyint] NOT NULL, items [int] NOT NULL, Price [money] NOT NULL, IsFirst [bit] NOT NULL, totalItems [int] NOT NULL, totalPrice [money] NOT NULL)
CREATE CLUSTERED INDEX IX_StockWork_1 ON #StockWork (ArticleID, TranDate)
INSERT INTO #StockWork (ArticleID, TranDate, OpCode, Items, Price, IsFirst, totalItems, totalPrice)
SELECT [ArticleID],
       [TranDate],
       CASE [TranCode] WHEN 'IN' THEN 1 WHEN 'OUT' THEN 2 WHEN 'RET' THEN 3 END,
       [Items],
       [Price], 0, 0, 0.0 FROM [dbo].[Stock]

DECLARE @PrevArticleID [int], @PrevStack [dbo].[StockStack], @PrevIsFirst bit
SET @PrevArticleID = -1
SET @PrevStack = StockStack::GetInitialisedStack(0.0, 0);

UPDATE #StockWork
   SET @PrevIsFirst = IsFirst = CASE WHEN @PrevArticleID != ArticleID THEN 1 ELSE 0 END,
       @PrevStack = @PrevStack.ProcessOpCode(ArticleID, @PrevArticleID, OpCode, Price, Items),
       totalItems = @PrevStack.TotalCount,
       totalPrice = @PrevStack.TotalPrice,
       @PrevArticleID = ArticleID
  FROM #StockWork WITH(INDEX(0),TABLOCKX)
OPTION (MAXDOP 1)

SELECT      ArticleID,
            CurrentItems,
            CurrentValue
FROM        (
                SELECT  ArticleID,
                        totalItems AS CurrentItems,
                        totalPrice AS CurrentValue,
                        ROW_NUMBER() OVER (PARTITION BY ArticleID ORDER BY TranDate DESC) AS recID
                FROM    #StockWork
            ) AS d
WHERE       recID = 1
ORDER BY    ArticleID

DROP TABLE #StockWork
GO
DROP TYPE [dbo].[StockStack]
GO
DROP ASSEMBLY [SqlClassLibrary]
GO

The source code for the assembly type is (no comments as yet - I might come back and fix this):

using System;
using System.Data;
using System.Data.SqlClient;
using System.Data.SqlTypes;
using Microsoft.SqlServer.Server;
using System.Collections.Generic;
using System.Text;

[Serializable]
[Microsoft.SqlServer.Server.SqlUserDefinedType(Format.UserDefined, MaxByteSize=4000)]
public struct StockStack : INullable, IBinarySerialize
{
    public override string ToString()
    {
        StringBuilder sb = new StringBuilder(1024);
        for (short i = _firstIndex; i <= _lastIndex; i++)
        {
            StockStackItem ssi = _stackItems[i];
            sb.Append(ssi.Value);
            sb.Append(" x ");
            sb.AppendLine(ssi.Count.ToString());
        }
        sb.Append("---");
        sb.Append(TotalPrice.ToString());
        sb.Append(" - ");
        sb.Append(TotalCount.ToString());
        return sb.ToString();
    }

    public bool IsNull
    {
        get
        {
            return _null;
        }
    }

    public StockStack ProcessOpCode(int ArticleID, int LastArticleID, int OpCode, SqlMoney Value, int Count)
    {
        if (ArticleID == LastArticleID)
        {
            switch (OpCode)
            {
                case 1:
                {
                    Decimal d = (Decimal)Value;
                    _stackItems.SetValue(new StockStackItem(d, Count), ++_lastIndex);
                    _totalCount += Count;
                    _totalPrice += d * Count;
                    return this;
                }
                case 2:
                {
                    int itemsLeft;
                    bool itemEmpty;
                    while (true)
                    {
                        StockStackItem newItem = _stackItems[_firstIndex].RemoveStock(Count, out itemsLeft, out itemEmpty);

                        if (itemEmpty)
                        {
                            _firstIndex++;
                        }
                        else
                        {
                            _stackItems.SetValue(newItem, _firstIndex);
                        }
                        if (itemsLeft == 0)
                        {
                            _totalPrice = 0;
                            _totalCount = 0;
                            for (int i = _firstIndex; i <= _lastIndex; i++)
                            {
                                StockStackItem ssi = _stackItems[i];
                                _totalCount += ssi.Count;
                                _totalPrice += ssi.TotalValue;
                            }
                            return this;
                        }
                        Count = itemsLeft;
                    }
                }
                case 3:
                {
                    StockStackItem ssi = _stackItems[_lastIndex];
                    _stackItems.SetValue(ssi.ReturnStock(Count), _lastIndex);
                    _totalCount += Count;
                    _totalPrice += ssi.Value * Count;
                    return this;
                }
                default:
                throw new InvalidOperationException("Invalid OpCode");
            }
        }
        else
        {
            StockStack ss = new StockStack();
            ss._stackItems = new StockStackItem[1];
            ss._stackItems.SetValue(new StockStackItem((Decimal)Value, Count), 0);
            return ss;
        }
    }

    public static StockStack Null
    {
        get
        {
            StockStack ss = new StockStack();
            ss._null = true;
            return ss;
        }
    }

    public StockStack ReturnStock(int Count)
    {
        _stackItems.SetValue(_stackItems[_lastIndex].ReturnStock(Count), _lastIndex);
        return this;
    }

    public StockStack AddStock(SqlMoney Price, int Count)
    {
        _stackItems.SetValue(new StockStackItem((Decimal)Price, Count), ++_lastIndex);
        return this;
    }

    public StockStack RemoveStock(int Count)
    {
        int itemsLeft = 0;
        bool itemEmpty = false;
        while (true)
        {
            if (_firstIndex > _lastIndex)
            {
                throw new InvalidOperationException("Cannot remove more stock from the stack than exists.");
            }
            StockStackItem newItem = _stackItems[_firstIndex].RemoveStock(Count, out itemsLeft, out itemEmpty);

            if (itemEmpty)
            {
                _firstIndex++;
            }
            else
            {
                _stackItems.SetValue(newItem, _firstIndex);
            }
            if (itemsLeft == 0)
            {
                return this;
            }
            Count = itemsLeft;
        }
    }

    public int TotalCount
    {
        get
        {
            return _totalCount;
        }
    }


    public SqlMoney TotalPrice
    {
        get
        {
            return _totalPrice;
        }
    }

    public static StockStack GetInitialisedStack(SqlMoney Price, int Count)
    {
        StockStack ss = new StockStack();
        ss._stackItems = new StockStackItem[2];
        ss._stackItems.SetValue(new StockStackItem((Decimal)Price, Count), 0);
        return ss;
    }

    public static StockStack Empty
    {
        get
        {
            StockStack ss = new StockStack();
            ss._stackItems = new StockStackItem[0];
            return ss;
        }
    }

    public static StockStack Parse(SqlString s)
    {
        if (s.IsNull)
            return Null;
        // no implementation of from-string for this type
        return StockStack.Empty;
    }

    // Nullability tracker
    private bool _null;

    private short _firstIndex;
    private short _lastIndex;

    int _totalCount;
    Decimal _totalPrice;

    // List of items in the stock stack
    private StockStackItem[] _stackItems;

    private struct StockStackItem
    {
        Decimal _stackItemValue;
        int _stackItemCount;

        public StockStackItem ReturnStock(int Count)
        {
            return new StockStackItem(_stackItemValue, _stackItemCount + Count);
        }

        public int Count
        {
            get
            {
                return _stackItemCount;
            }
        }

        public Decimal Value
        {
            get
            {
                return _stackItemValue;
            }
        }

        public Decimal TotalValue
        {
            get
            {
                return _stackItemValue * _stackItemCount;
            }
        }

        public StockStackItem RemoveStock(int Count, out int RemainingItems, out bool IsEmpty)
        {
            if (_stackItemCount > Count)
            {
                RemainingItems = 0;
                IsEmpty = false;
                return new StockStackItem(_stackItemValue, _stackItemCount - Count);
            }
            else 
            {
                RemainingItems = Count - _stackItemCount;
                IsEmpty = true;
                return new StockStackItem(0, 0);
            }
        }

        public StockStackItem(Decimal StackItemValue, int StackItemCount)
        {
            _stackItemValue = StackItemValue;
            _stackItemCount = StackItemCount;
        }
    }

    #region IBinarySerialize Members

    void IBinarySerialize.Read(System.IO.BinaryReader r)
    {
        byte b = r.ReadByte();
        _null = (b & 0x80) > 0;
        int stackCount = b & 0x7F;
        _stackItems = new StockStackItem[stackCount + 1];
        _lastIndex = (short)(stackCount - 1);
        for (int i = 0; i < stackCount; i++)
        {
            Decimal value = r.ReadDecimal();
            int count = r.ReadInt32();
            _totalCount += count;
            _totalPrice += count * value;
            _stackItems.SetValue(new StockStackItem(value, count), i);
        }
    }

    void IBinarySerialize.Write(System.IO.BinaryWriter w)
    {
        byte b = (byte)(((_lastIndex + 1) - _firstIndex) & 0x7F);
        if (_null)
        {
            b += 0x80;
        }
        w.Write(b);
        for (int i = _firstIndex; i <= _lastIndex; i++)
        {
            StockStackItem ssi = _stackItems[i];
            w.Write(ssi.Value);
            w.Write(ssi.Count);
        }
    }

    #endregion
}

Answer 5

RBarryYoung_1b: Naive, Pure Set-Based Solution

OK, just to get things rolling, here is a straight-forward Set-based solution, with no T-SQL tricks (though there is a very important algorithmic trick in cteOverlapValue).

CREATE PROC SscFIFO_RBarryYoung_1b AS
/*
    Naive pure Set-based solution to SSC FIFO inventory challenge.

    - RBarryYoung, Oct-24, 2009
*/
;WITH
-- the base CTE, (just an easy way to Alias to other version of the test table)
 cteStock AS ( SELECT * FROM Stock )
-- Just the 'IN' records:
, cteStockIN AS ( 
    SELECT * 
    FROM cteStock
    WHERE TranCode = 'IN' 
    )
-- Fill in the Last IN records date for lookups later:
, cteLastINDate AS (
    SELECT * 
    , CASE TranCode WHEN 'IN' THEN TranDate
        ELSE (
            SELECT MAX(s3.TranDate)
            FROM cteStockIN s3
            WHERE s.ArticleID = s3.ArticleID
            AND  s.TranDate > s3.TranDate
            ) END AS LastINDate
    FROM cteStock s
    )
-- Carry-forward the last price for RET records:
, cteLastPriceDate AS (
    SELECT * 
    , COALESCE(Price, (
        SELECT Price 
        FROM cteStockIN s2
        WHERE s.ArticleID = s2.ArticleID
        AND  s.LastINDate =  s2.TranDate
        )) AS LastPrice
    FROM cteLastINDate s
    )
-- Build running sums of InItems and OutItems (same column, but separate counts)
, cteRunningItems AS (
    SELECT *
    , CASE WHEN TranCode IN('IN','RET') THEN (
            SELECT SUM(Items) 
            FROM cteLastPriceDate p2
            WHERE p2.TranCode IN('IN','RET')
            AND   p2.ArticleID = p.ArticleID
            AND   p2.TranDate <= p.TranDate
            )
        WHEN TranCode = 'OUT' THEN (
            SELECT SUM(Items) 
            FROM cteLastPriceDate p2
            WHERE p2.TranCode = 'OUT'
            AND   p2.ArticleID = p.ArticleID
            AND   p2.TranDate <= p.TranDate
            )
        END AS InOutItems
    , CASE WHEN TranCode IN('IN','RET') THEN (
            SELECT SUM(p2.Items*p2.LastPrice) 
            FROM cteLastPriceDate p2
            WHERE p2.TranCode IN('IN','RET')
            AND   p2.ArticleID = p.ArticleID
            AND   p2.TranDate <= p.TranDate
            ) END AS TotalValueIN
    FROM cteLastPriceDate p
    )
-- Map each OUT record to the (IN,RET) records that it will be consuming:
, cteOutMapIn AS (
    SELECT t1.*
    , t2.Items AS InItems
    , t2.LastPrice AS InPrice
    , t2.InOutItems AS TotalIn
    FROM cteRunningItems t1
    LEFT JOIN cteRunningItems t2
        ON  t1.ArticleID = t2.ArticleID
        AND t1.TranCode = 'OUT'
        AND t2.TranCode IN('IN','RET')
        AND t1.InOutItems-t1.Items <= t2.InOutItems
        AND t1.InOutItems >= t2.InOutItems-t2.Items
    )
-- Calculate the OUT consumed values, 
--based on how the OUT items overlap the (IN,RET) items:
, cteOverlapValue AS (
    SELECT *
    , CASE WHEN TranCode = 'OUT' THEN
        CASE 
            WHEN InOutItems >= TotalIn  AND (InOutItems-Items) <= (TotalIn-InItems)
                THEN InItems            -- OUT consumes all the INs
            WHEN InOutItems >= TotalIn  -- OUT consumes only the upper part of the INs
                THEN (TotalIn - (InOutItems-Items)) 
            WHEN (InOutItems-Items) <= (TotalIn-InItems)    -- OUT consumes the lower INs
                THEN (InOutItems - (TotalIn-InItems)) 
            ELSE Items  END             -- All OUTs consume an interior slice of IN
      END AS ItemsConsumed
    , CASE WHEN TranCode = 'OUT' THEN
        CASE
            WHEN InOutItems >= TotalIn  AND (InOutItems-Items) <= (TotalIn-InItems)
                THEN InItems * InPrice  -- OUT consumes all the INs
            WHEN InOutItems >= TotalIn  -- OUT consumes only the upper part of the INs
                THEN (TotalIn - (InOutItems-Items)) * InPrice
            WHEN (InOutItems-Items) <= (TotalIn-InItems)    -- OUT consumes the lower INs
                THEN (InOutItems - (TotalIn-InItems)) * InPrice
            ELSE Items * InPrice END    -- All OUTs consume an interior slice of IN
      END AS ConsumedValue
    FROM cteOutMapIn 
    )
-- Total everything up for each ArticleID:
, cteArticleTotals AS (
    SELECT t1.ArticleID
    , SUM( CASE WHEN TranCode='OUT' THEN -ItemsConsumed ELSE Items END ) AS CurrentItems
    , MAX( TotalValueIN ) - COALESCE(SUM( ConsumedValue ),0) AS CurrentValue
    FROM cteOverlapValue t1
    GROUP BY t1.ArticleID
    )
-- Output the results:
SELECT *
FROM cteArticleTotals t1
ORDER BY t1.ArticleID

~~Performance is not good, 9 seconds on the 5000 row (75 Articles) test set, and about 18 minutes on the full set.~~

Oops! I got those numbers completely wrong,...

In reality, performance is OK, but not great. it takes 9 seconds on 100,000 rows (about 1500 Articles) and 90 seconds on the full set. Not bad for virtually no optimizations.

1b: OK, I have made the corrections Requested by Peso (ORDER BY and Fixed NULLS on Article 25001). My current timings for it are 9sec on 100k rows and 95sec on 1M rows.