Data replication chores are a snap with the new MERGE T-SQL statement.
Released in August 2008, SQL Server 2008 is the latest incarnation of Microsoft's flagship database platform. While there are some cool new features for developers, there is one for DB2 developers that deserves special mention: the new Transact SQL (T-SQL) MERGE statement. MERGE will be useful to any IBM i (aka AS/400, iSeries, System i) shop that needs to replicate DB2 for i (formerly known as DB2 for i5/OS and DB2/400) data to SQL Server. This includes shops that use SQL Server for reporting, data warehousing. and application data sharing.
What Is MERGE?
The MERGE statement is a single SQL statement that allows data to be synchronized between a "source" data source and a "target" data source. In this case, we'll consider a DB2 for i database table as the source and a SQL Server database table as the target.
Traditionally, when writing a SQL Server routine to synchronize data between these two sources, a developer has a few possible approaches:
- Clear the target table and reload it entirely from the source table.
- For source tables that are "append only," simply copy the latest rows to the destination table.
- Write a combination of INSERT, UPDATE, and DELETE statements that keep the data between the two tables up to date.
Option 1 is clearly an option for small tables, such as code tables, but not so good for large tables. Option 2 works well for tables that only have new rows inserted, never updated (such as an inventory transaction history table). But what about when operating on larger tables that are not append only? Reloading entire large tables is often time-consuming on both servers. Therefore, option 3 is used to synchronize data between disparate data sources when a large amount of data is involved.
Let's look at an example of this last scenario that uses SQL Server's linked server facility to communicate with DB2. If you're not up to speed on linked servers and how to define them, see the references at the end of this tip. For this demonstration, I defined a linked server using the ODBC driver that comes with System i Access V6R1 (formerly known as iSeries Access) with service pack level SI31390 connecting to a V6R1 host. For those who prefer the IBM OLE DB providers over ODBC, I attempted to use the IBMDASQL driver but was not successful in getting it to work at this level.
For simplicity, say we have table QCUSTCDT with identical columns that exist on both DB2 for i and SQL Server. The primary key on both tables is CUSNUM. Further, we simply need to replicate all changes from DB2 to SQL Server and not the other way around. Using a linked server called DB2_ODBC (and utilizing the SQL naming convention in the ODBC setup), our T-SQL code would look like the following:
/* Update existing rows from DB2 */
Update Target
Set LSTNAM = Source.LSTNAM,
INIT = Source.INIT,
STREET = Source.STREET,
CITY = Source.CITY,
STATE = Source.STATE,
ZIPCOD = Source.ZIPCOD,
CDTLMT = Source.CDTLMT,
CHGCOD = Source.CHGCOD,
BALDUE = Source.BALDUE,
CDTDUE = Source.CDTDUE
From QCUSTCDT Target
Join OpenQuery(DB2_ODBC,'Select * From QIWS.QCUSTCDT') Source
On Target.CusNum=Source.CusNum
/* Insert new rows from DB2 */
Insert Into QCUSTCDT
Select *
From OpenQuery(DB2_ODBC,'Select * From QIWS.QCUSTCDT') Source
Where Not Exists
(Select *
From QCUSTCDT Target
Where Target.CUSNUM=Source.CusNum)
/* Delete rows that are not in DB2 */
Delete From QCUSTCDT
Where Not Exists
(Select *
From OpenQuery(DB2_ODBC,'Select * From QIWS.QCUSTCDT') Source
Where QCUSTCDT.CUSNUM=Source.CusNum)
If this was a large table and had additional columns for timestamp added and updated, we'd probably want to add some additional criteria to the INSERT and UPDATE statements based on these values to limit the number of rows being processed.
MERGE is essentially a statement that allows a developer to specify a source (which can be a query, table, or view) and a target (which can be a table or updateable view) and define any combination of INSERT, UPDATE, and DELETE statements all rolled into one. Below is an example MERGE statement that replaces the three statements shown above:
MERGE dbo.QCUSTCDT AS Customer_Target
USING OpenQuery(DB2_ODBC,
'Select * From QIWS.QCUSTCDT') AS Customer_Source
ON (Customer_Target.CusNum = Customer_Source.CusNum)
WHEN MATCHED THEN
UPDATE
SET Customer_Target.LSTNAM=Customer_Source.LstNam,
Customer_Target.Init=Customer_Source.Init,
Customer_Target.Street=Customer_Source.Street,
Customer_Target.City=Customer_Source.City,
Customer_Target.State=Customer_Source.State,
Customer_Target.ZipCod=Customer_Source.ZipCod,
Customer_Target.CdtLmt=Customer_Source.CdtLmt,
Customer_Target.ChgCod=Customer_Source.ChgCod,
Customer_Target.BalDue=Customer_Source.BalDue,
Customer_Target.CdtDue=Customer_Source.CdtDue
WHEN NOT MATCHED BY TARGET THEN
INSERT (CUSNUM,LSTNAM,INIT,STREET,CITY,STATE,ZIPCOD,
CDTLMT,CHGCOD,BALDUE,CDTDUE)
VALUES (Customer_Source.CUSNUM,Customer_Source.LSTNAM,
Customer_Source.INIT,
Customer_Source.STREET,Customer_Source.CITY,
Customer_Source.STATE,Customer_Source.ZIPCOD,
Customer_Source.CDTLMT,Customer_Source.CHGCOD,
Customer_Source.BALDUE,Customer_Source.CDTDUE)
WHEN NOT MATCHED BY SOURCE THEN
DELETE
OUTPUT $action, /* Reserved Keyword */
inserted.CusNum AS SourceCusNum,
deleted.CusNum AS TargetCustNum
; /* Merge needs a semicolon terminator! */
Let's go over the MERGE statement's clauses:
•· MERGE is a clause used to specify the name of a table or an updateable view as the target of the merge operation. Unfortunately, remote data sources are not allowed here.
•· USING specifies the data source for the merge, including tables, views, or a valid T-SQL query. In this case, the OpenQuery table function is used to retrieve data from DB2 for i.
•· ON is the search condition that correlates the data in the source and target tables. Generally, this should specify column name(s) that uniquely identify the rows between the data sources. The documentation warns against adding additional filtering criteria to this clause; save that task for the WHEN clauses!
•· WHEN MATCHED THEN is an optional clause that instructs MERGE how to handle a row in the target table that matches the current row in the source table. The options here are to issue an abbreviated UPDATE or DELETE command against the target.
•· WHEN NOT MATCHED BY TARGET THEN is an optional clause that instructs MERGE how to handle the situation when the source has a row that the target does not have. Generally, this is when an INSERT is done against the target. Note in the example the abbreviated SQL syntax used for an INSERT.
•· WHEN NOT MATCHED BY SOURCE THEN is an optional clause that instructs MERGE how to handle the case when there is a row in the target that is not in the source. Usually, if anything, a DELETE against the target is issued at this time. Please note that a search condition may be added to any of the WHEN clauses. Also, the abbreviated INSERT, UPDATE, and DELETE statements lack the table or view name (already specified in the MERGE clause) and lack criteria (done in the ON and WHEN clauses.)
•· OUTPUT is an elective clause that is useful for debugging or auditing. When OUTPUT is specified, each row that is modified by MERGE is added to a result set returned by the statement. As with T-SQL triggers, the "inserted" and "deleted" tables are special temporary tables that are used to track data from INSERT and UPDATE operations and UPDATE and DELETE operations, respectively. "$action" is a system function that contains a value of INSERT, UPDATE, or DELETE, depending on the action taken by MERGE. Further, OUTPUT can direct merge results to a table for auditing purposes.
MERGE is extremely versatile in that the source columns on the INSERT and UPDATE statements can contain expressions. Also, additional criteria can be specified before doing any of the data modification operations. For example, if a timestamp column is available, we can require that a target row is over one year old before deleting it. Or, before updating a row, SQL Server can be made to check for a change in the data before using resources to perform an update:
WHEN MATCHED AND
(Customer_Target.LstNam<>Customer_Source.LstNam
Or Customer_Target.Street<>Customer_Source.Street
Or Customer_Target.ZipCod<>Customer_Source.ZipCod) THEN
In this example, data is updated only if the last name, street, or ZIP code change.
Unfortunately, when working with linked servers, MERGE is unidirectional. That is, it can merge data only to a local SQL Server table. Merging from a SQL Server source to a linked server target is not allowed. Therefore, MERGE should be used only when moving data in one direction--from DB2 to SQL Server.
Performance
To get an idea of how MERGE performs against individually written statements, I decided to export data from the SQL Server Adventure Works sample database to our trusty AS/400. I picked a single table called SalesOrderDetail that contains 121317 rows. The table has an 8-byte composite primary key and contains about 120 bytes per row. To give the MERGE statement some work to do, I...
•· added about 30K bogus records that it would have to delete
•· changed data in about 30K rows that it would have to update
•· deleted about 30K rows that it would have to insert
•· left about 30K alone that it should ignore
All in all, MERGE would have about 90K rows to update for this test. For three trials, MERGE averaged about 39 seconds (although neither the test workstation nor the AS/400 has impressive specs!). For comparison, I ran three trials against individual INSERT, UPDATE, and DELETE statements, which averaged 49 seconds. So in this case, MERGE offered about a 20 percent performance improvement when accessing a remote data source.
The T-SQL statements used in the trial are shown at the end of this tip.
MERGE Ahead!
MERGE statements should prove easier to maintain and debug. If a column is added to the primary key of your merge tables, for instance, you only need to change the correlation once in the ON clause instead of changing it in multiple statements. Also, since MERGE is T-SQL-based, you don't have to worry about the complexity of adding an integration services package to move the data. Finally, MERGE offers better performance over writing individual distributed query SQL statements. When moving data from DB2 to SQL Server, MERGE is an efficient, easy way to go.
References
-
"DB2 Integration with SQL Server 2005, Part I: Linked Server Enhancements" (MC Mag Online, March 2006)
-
"Patch Those Leaky Interfaces" (MC Mag Online, June 2003)
-
"Running Distributed Queries with SQL/400 and SQL Server 7.0" (AS/400 Network Expert, September/October 2000)
Trial T-SQL Statements
--T-SQL Script comparing MERGE vs distributed query statement performance
--
-- Step 1 - Mangle the data to give MERGE/statements
-- something to do.
-- (assumes SQL Server table is sync'd with
-- AS/400 table to begin with)
--
--
-- Delete every fourth row to give Merge
-- something to Insert
--
Delete
From Sales.SalesOrderDetail
Where (SalesOrderDetailID % 4)=0
GO
--
-- Update a few columns on every 3rd row
-- to force Merge to update existing data
--
Update Sales.SalesOrderDetail
Set OrderQty=OrderQty+5,
CarrierTrackingNumber=CarrierTrackingNumber+''
Where (SalesOrderDetailID % 3)=0
GO
--
-- Insert some bad rows that will have to be
-- deleted by Mere
--
SET IDENTITY_INSERT Sales.SalesOrderDetail ON
GO
INSERT INTO Sales.SalesOrderDetail
(SalesOrderID,SalesOrderDetailId,CarrierTrackingNumber,
OrderQty,ProductID,SpecialOfferID,
UnitPrice,UnitPriceDiscount,rowguid,
ModifiedDate)
Select -SalesOrderID,SalesOrderDetailId,CarrierTrackingNumber,
OrderQty,ProductID,SpecialOfferID,
UnitPrice,UnitPriceDiscount,rowguid,
ModifiedDate
From Sales.SalesOrderDetail
Where SalesOrderDetailID % 2=0
GO
SET IDENTITY_INSERT Sales.SalesOrderDetail OFF
GO
--
-- Step 2 -- OK Merge, do your stuff!
--
-- Change the updated rows, delete the new bad rows
-- and re-insert the deleted rows
--
SET IDENTITY_INSERT Sales.SalesOrderDetail ON
GO
MERGE Sales.SalesOrderDetail AS Target
USING OpenQuery(DB2_ODBC,
'Select * From AdvWorks.SalesOrderDetail') AS Source
ON (Target.SalesOrderId=Source.SalesOrderId
And Target.SalesOrderDetailId=Source.SalesOrderDetailId)
WHEN MATCHED AND
(Target.CarrierTrackingNumber<>Source.CarrierTrackingNumber
Or Target.OrderQty<>Source.OrderQty
Or Target.ProductID<>Source.ProductID
Or Target.SpecialOfferID<>Source.SpecialOfferID
Or Target.UnitPrice<>Source.UnitPrice
Or Target.UnitPriceDiscount<>Source.UnitPriceDiscount)THEN
UPDATE
SET CarrierTrackingNumber = Source.CarrierTrackingNumber,
OrderQty = Source.OrderQty,
ProductID = Source.ProductID,
SpecialOfferID = Source.SpecialOfferID,
UnitPrice = Source.UnitPrice,
UnitPriceDiscount = Source.UnitPriceDiscount,
rowguid = Source.rowguid,
ModifiedDate = Source.ModifiedDate
WHEN NOT MATCHED BY TARGET THEN
INSERT
(SalesOrderID,SalesOrderDetailId,CarrierTrackingNumber,
OrderQty,ProductID,SpecialOfferID,
UnitPrice,UnitPriceDiscount,rowguid,
ModifiedDate)
VALUES
(Source.SalesOrderID,Source.SalesOrderDetailId,
Source.CarrierTrackingNumber,Source.OrderQty,
Source.ProductID,Source.SpecialOfferID,
Source.UnitPrice,Source.UnitPriceDiscount,
Source.rowguid,Source.ModifiedDate)
WHEN NOT MATCHED BY SOURCE THEN
DELETE
;
SET IDENTITY_INSERT Sales.SalesOrderDetail OFF
GO
-- TRIAL 1 -- 41 SECONDS
-- TRIAL 2 -- 36 SECONDS
-- TRIAL 3 -- 39 SECONDS
-- ~ 39 seconds
--
-- Step 3 - Use individual statements to
-- synchronize data
--
-- (The data in the SQL Server table needs to be
-- reset again - run Step 1)
--
-- Using individual statements, change the updated rows,
-- delete the new bad rows and insert the deleted rows
--
UPDATE Target
SET CarrierTrackingNumber = Source.CarrierTrackingNumber,
OrderQty = Source.OrderQty,
ProductID = Source.ProductID,
SpecialOfferID = Source.SpecialOfferID,
UnitPrice = Source.UnitPrice,
UnitPriceDiscount = Source.UnitPriceDiscount,
rowguid = Source.rowguid,
ModifiedDate = Source.ModifiedDate
From Sales.SalesOrderDetail Target
Join OpenQuery(DB2_ODBC,'Select * From ADVWORKS.SalesOrderDetail') Source
On Target.SalesOrderDetailID=Source.SalesOrderDetailID
And Target.SalesOrderID=Source.SalesOrderID
Where (Target.CarrierTrackingNumber<>Source.CarrierTrackingNumber
Or Target.OrderQty<>Source.OrderQty
Or Target.ProductID<>Source.ProductID
Or Target.SpecialOfferID<>Source.SpecialOfferID
Or Target.UnitPrice<>Source.UnitPrice
Or Target.UnitPriceDiscount<>Source.UnitPriceDiscount)
SET IDENTITY_INSERT Sales.SalesOrderDetail ON
GO
INSERT INTO Sales.SalesOrderDetail
(SalesOrderID,SalesOrderDetailId,CarrierTrackingNumber,
OrderQty,ProductID,SpecialOfferID,
UnitPrice,UnitPriceDiscount,rowguid,
ModifiedDate)
Select SalesOrderID,SalesOrderDetailId,CarrierTrackingNumber,
OrderQty,ProductID,SpecialOfferID,
UnitPrice,UnitPriceDiscount,rowguid,
ModifiedDate
From OpenQuery(DB2_ODBC,'Select * From ADVWORKS.SalesOrderDetail ORDER BY SalesOrderDetailId') Source
Where Not Exists
(Select *
From Sales.SalesOrderDetail Target
Where Target.SalesOrderDetailID=Source.SalesOrderDetailID
And Target.SalesOrderID=Source.SalesOrderID)
Order By SalesOrderDetailId
GO
SET IDENTITY_INSERT Sales.SalesOrderDetail OFF
GO
Delete From Sales.SalesOrderDetail
Where Not Exists
(Select *
From OpenQuery(DB2_ODBC,'Select SalesOrderId,SalesOrderDetailId
From ADVWORKS.SalesOrderDetail') Source
Where Sales.SalesOrderDetail.SalesOrderDetailID=Source.SalesOrderDetailID
And Sales.SalesOrderDetail.SalesOrderID=Source.SalesOrderID)
-- trial 1 - 47 seconds
-- trial 2 - 51 seconds
-- trial 3 - 49 seconds
-- Avg - 49 seconds
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