Return to Horizontal and Vertical Partitioning in Replication
Horizontal and Vertical Partitioning in Replication
Written by Guest Authors on 30 January 2003
This article was written by Lynn Zhu and Demico Quinn. They write "Before coming up with the solution that this article will describe, we decided that this would be a great topic to write about and share our experiences with others. We also found that there were not a lot of articles out there that focused on Replication. More specifically, articles that chronicled case studies where column and row filters were being used as an integral part of the solution. It is our hope that you will find this article to be helpful and inspire readers to write more articles about Replication."
Using Replication’s Horizontal and Vertical partitioning capabilities to manage pubications in a distributed database environment
There are times that you may find yourself on a project where you have one data source
and need to publish to many subscribing databases. Often times, Replication is not looked
at as a viable solution to achieving this goal. We can only attribute this to the
“blood sweat and tears” that it took to get Replication in SQL 6.5 to work smoothly.
Fortunately those days are gone and Microsoft has only improved the way Replication
works in SQL 2000. For this project, we will demonstrate the way we utilized the
Horizontal and Vertical partitioning capabilities that Microsoft has added to the
Replication utility.
To begin, we have company A, which sells it’s products based on district as the following
scheme illustrates:
In this scenario a products given retail price may differ depending upon whether the
product was purchased using the website or sold at one of our store locations.
Additionally, a product can also have different discount prices in different districts,
and be sold on either the web or in the store. Often times the discounts that are
found on the website may or may not be applicable to “in store sales”, and the same
rule applies to discounts found in the store.
All transactions will write to one database, which will act as the publisher to multiple
subscribing databases. The database is called CentralInfo, and as earlier stated will
act as the publishing database for our demonstration. There will be two databases that
will subscribe to publications that are based off of the CentralInfo database. The
WebSale database only needs the information about the products, web sale prices, and
discounts that will be sold through the web by districts. The StoreSale database only
needs the information about the products, store sale prices, and discounts that will
be sold through the store by districts. To meet this business requirement we had to
make some small modifications to the scheme. In order to restrict the rows and columns
that will be defined in the publications, we added two columns (Use4WebSale and
Use4StoreSale) to the Products and Products2District tables as row filters.
(After adding Use4WebSale, and Use4StoreSale columns)
The filters are defined as integer data types and the default value for columns
Use4WebSale and Use4StoreSale is 0. If a given product is for web sales then the value
of column Use4WebSale will be updated to 1. If a given product is for store sales then
the value of column Use4StoreSale will be updated to 1. For products that are meant for
both web and store sales the value of both Use4WebSale and Use4StoreSale are set to 1.
The following chart illustrates the possible scenarios.
Product2Distirct:
| productid |
districtid |
websaleprice |
storesaleprice |
discountid |
discountstartdate |
discountenddate |
use4websale |
use4storesale |
| 3 |
2 |
20 |
15 |
1 |
12/16/2002 |
7/31/2003 |
0 |
1 |
| 4 |
2 |
30 |
25 |
2 |
12/25/2002 |
1/15/2003 |
1 |
1 |
| 5 |
2 |
25 |
20 |
1 |
12/16/2002 |
7/31/2003 |
1 |
0 |
Products:
| productid |
productname |
productmodel |
warehouseid |
producttypeid |
use4websale |
productcost |
use4storesale |
| 3 |
Oil filter |
RS-300 |
2 |
1 |
1 |
$7.99 |
1 |
| 4 |
Side mirror |
PA-100 |
2 |
2 |
0 |
$19.99 |
1 |
| 5 |
Door Bulb |
DB-022 |
1 |
3 |
1 |
$15.99 |
0 |
| 6 |
Window Bulb |
BW-012 |
1 |
3 |
0 |
$6.99 |
0 |
Publications and Subscribers
There will be two publications and two subscribers to be set up.
1a. Store publication configurations
Now that we have established what changes needed to be made to the scheme, we can now
start defining our publications. We will define store publication and identify the
articles that will be used in the publication. To create the publication the “Create
Publication wizard” was used. And defined as follows:
Publication Name: CentralInfo_to_StoreSale
Publishing Database: CentralInfo
Articles:
| Products |
| Products2Districts |
| Districts |
| States |
| WareHouses |
| Discounts |
| ProductType |
Snapshot Options : The following options refer to the initial snapshot.
- Drop existing tables and recreate
- Uncheck “Include declared referential integrity”
- Uncheck Clustered indexes
- Uncheck Non-clustered indexes
After initial snapshot has been applied, the filters can be added to the articles and
re-initialization occurs on the publication. You must also change the snapshot property
to “ Delete data in the existing tables that match the row filter statement”. In the
case where you have populated your CentralInfo database with data, you can apply all
filters prior to the initial snapshot. This will eliminate the need to run the
initialization snapshot a second time. Filters are defined as follows:
For the Products article add this row filter (table) Row Filter: Use4StoreSale =1
Syntax: SELECT <published_columns>
FROM <<TABLE>>
WHERE <TABLE>>.Use4StoreSale = 1
For the Products2Districts article add this row filter(table) Row Filter and Column
Filter: Use4StoreSale =1
Under the Column filter tab for the article “Products2Districts”, uncheck column
WebSalePrice
Syntax: SELECT <published_columns>
FROM <<TABLE>>
WHERE <<TABLE>>.Use4StoreSale = 1
1b. Store subscriber configurations
The following describes the subscriber options that define how the StoreSale database
will receive data from CentralInfo Database. The subscribing database can be created
during the subscription process or pre-exist.
Subscription name: Server name: StoreSale
Type: Push
Publish Interval: Optional
Scheme: Scheme is created by the Snapshot agent
Subscriber StoreSale:
2a. Web publication configurations
Now, we will define the web publication and identify the articles that will be used.
To create the publication the “Create Publication wizard” was used. And defined as
follows:
Publication Name: CentralInfo_to_WebSale
Publishing Database: CentralInfo
Articles:
| Products |
| Products2Districts |
| Districts |
| States |
| WareHouses |
| Discounts |
| ProductType |
Note: The articles in this publication are the same as defined in our StoreSale
publication. Repeat all steps in this publication as you did for the StoreSale
publication, the only exception will be to filter on the column; “Use4WebSale”.
2b. Web subscriber configurations
The following describes the subscriber options that define how the WebSale database
will receive data from CentralInfo Database. The subscribing database can be created
during the subscription process or pre-exist.
Name: SQLSERVERNAME: WebSale
Type: Push
Publish Interval: Optional
Scheme: Scheme is created by the Snapshot agent
Summary of implementation steps
The following is a step-by-step summary of the tasks
performed in order to implement this solution.
1. Run script to create the database scheme (CentralInfo).
2. Create Transactional Publication which includes the following sub tasks:
2.1 Create StoreSale database
2.2 Define articles with article options
2.3 No article filters
3. Run Snapshot
4. Run distribution
5. Modify Transactional publication which includes the following sub tasks:
5.1 Add filter to each article with the following “Use4StoreSale =1”
5.2 Update Snapshot option to “ Delete data in the existing tables
that match the row filter statement”
5.3 Re-initialize the publication
6. Create Transactional Publication which includes the following sub tasks:
6.1 Create WebSale database
6.2 Define articles with article options
6.3 No article filters
7. Run Snapshot
8. Run Distribution
9. Modify Transactional publication which includes the following sub tasks:
9.1 Add filter to each article with the following “Use4WebSale =1”
9.2 Update Snapshot option to “ Delete data in the existing
tables that match the row filter statement”
10. Re-initialize the publication
11. Run Snapshot (Once data has been mapped via the Customer Care department)
12. Run Distribution
13. Run scripts to load data into the CentralInfo database.
14. Once data has been published to the subscribers, check
to insure that the filters are working as expected.
Lynn Zhu is the Lead Developer of Western Wireless Corporation and is responsible for SQL Server database design and development. She is an MCDBA. Demico Quinn is the SQL Server DBA for the Western Wireless Corporation where he is responsible for SQL Server database servers and database applications.
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