I need to query a table for the latest version of a record for all available dates (end of day time-series). The example below illustrates what I am trying to achieve.
My question is whether the table's design (primary key, etc.) and the LEFT OUTER JOIN
query is accomplishing this goal in the most efficient manner.
CREATE TABLE [PriceHistory]
(
[RowID] [int] IDENTITY(1,1) NOT NULL,
[ItemIdentifier] [varchar](10) NOT NULL,
[EffectiveDate] [date] NOT NULL,
[Price] [decimal](12, 2) NOT NULL,
CONSTRAINT [PK_PriceHistory]
PRIMARY KEY CLUSTERED ([ItemIdentifier] ASC, [RowID] DESC, [EffectiveDate] ASC)
)
INSERT INTO [PriceHistory] VALUES ('ABC','2016-03-15',5.50)
INSERT INTO [PriceHistory] VALUES ('ABC','2016-03-16',5.75)
INSERT INTO [PriceHistory] VALUES ('ABC','2016-03-16',6.25)
INSERT INTO [PriceHistory] VALUES ('ABC','2016-03-17',6.05)
INSERT INTO [PriceHistory] VALUES ('ABC','2016-03-18',6.85)
GO
SELECT
L.EffectiveDate, L.Price
FROM
[PriceHistory] L
LEFT OUTER JOIN
[PriceHistory] R ON L.ItemIdentifier = R.ItemIdentifier
AND L.EffectiveDate = R.EffectiveDate
AND L.RowID < R.RowID
WHERE
L.ItemIdentifier = 'ABC' and R.EffectiveDate is NULL
ORDER BY
L.EffectiveDate
Follow up: Table can contain thousands of ItemIdentifiers each with dacades worth of price data. Historical version of data needs to be preserved for audit reasons. Say I query the table and use the data in a report. I store @MRID = Max(RowID)
at the time the report was generated. Now if the price for 'ABC' on '2016-03-16' is corrected at some later date, I can modify the query using @MRID and replicate the report that I ran earlier.